Bohlin came up with one very simple invention: the modern seat belt.

Within a year, Volvo began equipping their cars with seat belts as standard, and — as a result of its importance to safety — opened up the patent so that other manufacturers could do the same. Volvo claims that Bohlin’s invention has saved over a million lives. That would make Bohlin one of the highest-impact people in history, alongside David Nalin, the inventor of oral rehydration therapy for diarrhoea.

We’d guess Bohlin’s impact wasn’t quite that large. For one thing, seat belts already existed: in 1951, a Y-shaped three-point seat belt was patented that avoided the risks of internal injuries from simple lap belts. Bohlin’s innovation was doing this with just one strap, making it simple and convenient to use. For another thing, it seems likely that someone else would have come up with Bohlin’s design eventually.

Nevertheless, a simple estimate suggests that Bohlin saved hundreds of lives at the very least² — incredible for such a simple piece of engineering.

Thanks to Jessica Wen and Sean Lawrence at High Impact Engineers for their help with this article. Much of the content is based on their website.

Why are engineering skills valuable?

Bohlin’s story shows that engineering — by which we mean all kinds of engineering other than software engineering, which we cover separately — can clearly be hugely valuable for the world. But we think it’s most valuable when:

• You can really speed up development. This might be because you’re working on something that’s relatively neglected by others, or because you’re working in an area where you have high personal fit, so you can make particularly helpful contributions (or, ideally, both).
• You’re producing something which will practically be used to help people. One reason Bohlin had such a large impact — and Griswold, the inventor of the Y-shaped three-point seat belt didn’t — is that Volvo opened up the patent for use by other manufacturers.
• You’re working on a particularly pressing problem. For example, vaccines for common and deadly diseases — like malaria — are much more useful for the world than vaccines for rare diseases.

Ultimately, many of the potential solutions to the top problems we recommend working on include developing and deploying technology — and this often requires engineers.

Below, we look more closely at how engineering could be used to solve some of the world’s most pressing problems.

Jobs in engineering are often highly paid and in-demand. So learning engineering skills can give you great back-up options, and — depending on the specific discipline — can be a decent choice for earning to give.

Good pay combined with intellectually rewarding work means that engineers often have high job satisfaction (although we’d expect job satisfaction to be lower in academia than in industry).

Finally, it’s worth noting that it’s possible to accidentally cause harm through engineering. While we’re generally hugely in favour of technological development, many of the risks we’re most concerned about arise directly from the development of future technologies. Many technologies are dual use and could have both positive and negative applications. So it’s worth thinking carefully about the work you’re doing and whether it could be used to cause harm. (For an example of how you might think about this, see this article on whether it’s good to work on advancing AI capabilities. This example primarily applies to software engineers, but could also apply more broadly — to computer hardware engineers for instance.)

What specific discipline of engineering is most valuable?

There are many different types of engineering. Typically, you’ll eventually specialise in one (often during an undergraduate degree).

There are ways of using any engineering discipline to have an impact.

That said, we’re most excited about:

• Biomedical engineering
• Chemical engineering
• Electrical and electronic engineering.

That’s because these areas are most relevant to some of our top problems, in particular preventing catastrophic pandemics and reducing the risk of an AI-related catastrophe.

Some engineering disciplines also pay much better than others. In particular, nuclear, aerospace, petroleum and computer hardware engineers are paid best (although we wouldn’t generally recommend becoming a petroleum engineer, as we’d worry it causes harm), while agricultural and civil engineers are paid least.

What does using an engineering skill set typically involve?

An engineering skill set usually involves developing technologies faster and deploying existing technologies in novel ways. (This is in contrast with research skills, which focus on finding answers to unanswered questions, although there’s a fair bit of overlap between the two.)

Engineers typically do one of the following:

• Work in academia
• Work in industry
• Work at small startups (or found them)

Work in academia

Work in academia tends to focus on more speculative, early-stage technology (e.g. using ultraviolet light to sterilise rooms). This work is much more similar to research, so if you’re interested we’d suggest looking at our articles on research skills and working in academia. This route almost always involves getting a PhD in a subfield of engineering.

Academic research can be difficult for many people. It often involves long deadlines, self-driven work, and very little structure. Beyond engineering, academic work is also likely to include grant applications, teaching courses, publishing papers, mentoring students, and other responsibilities.

(We’ll look more at what to consider when choosing to do a PhD below.)

Work in industry or startups

As the technology becomes more viable, businesses tend to get involved — either startups or large engineering firms, or both. There are also some nonprofits focused on high-impact technology.

When working on engineering in industry, you can choose to become a subject matter expert (more similar to research) or instead become a manager, increasing the scope of your responsibilities. Either way, you can try learning faster by getting temporary placements in other parts of a company, taking part in engineering competitions, or working towards professional registration (which can be a helpful credential for engineering careers).

Generally, the work you focus on will be dictated by the business needs of the company, and, compared to academia, you’re more likely to have a standard 9-5 workday (rather than more flexible hours). Deadlines are often much shorter than in academia.

If you choose to become a manager or work for a small startup, you’ll be using organisation-building skills alongside your engineering skill set.

How to evaluate your fit

How to predict your fit in advance

You’ll need a quantitative background, and ideally you’ll have studied (or plan to study) engineering or a highly related subject at undergraduate level.

If you’re considering doing an engineering degree (or otherwise moving your career into engineering), signs you’d be a great fit could include:

• You’re comfortable working on scientific subjects.
• You’re good at practical, hands-on work: in many areas of engineering, you’ll end up working with physical objects in a lab.
• You enjoy understanding how and why physical things work.
• You enjoy fixing or building things, for example, around your home.
• You are good at “systems thinking”: for example, you’d notice when people ask you similar questions multiple times and then think about how to prevent the issue from coming up again.
• You might also be good at learning quickly and have high attention to detail.

With academic engineering, you’ll need to be comfortable with the academic research environment and generally happy to be self-motivated while working on things with few clear deadlines. If you’re doing a degree, you could try doing some sort of academic research (like a summer research project) and think about how that goes. (Read more about evaluating your fit for research.)

If you want to become a manager or work for a startup, you’ll probably need more social skills (including things like clear communication and people management skills).

Assessing your fit for different disciplines of engineering

One way to start is to think about which of the natural sciences you most enjoy learning about. Some examples:

Another way to determine what kind of engineering you might be good at is to figure out where you lie on the spectrum from scientist to engineer. If you enjoy the more theoretical, abstract, or precise side of physics or mathematics, then something like materials science or electrical engineering could be a better fit. If you lean more towards optimisation, application of knowledge, or practicalities, then civil or chemical engineering might be more interesting. If you are somewhere in the middle, then mechanical engineering could be for you.

However, don’t place too much weight on these crude tests — all these areas involve design testing and innovation, as well as research and studying new phenomena.

Your discipline also may not matter that much when it comes to getting a job. For example, many larger companies will hire graduate engineers from a range of different disciplines for the same role, relying on on-the-job training for specialisation.

How to tell if you’re on track

Within industry, the stages here look like an organisation-building career, and you can also assess your fit by looking at your rate of progression through the organisation.

Within academia, there’s generally very defined progression (e.g. completing a PhD, getting a postdoc, etc.).

In both cases, it’s worth trying to find some engineers whose work you respect, and who you trust to be honest with you, to give you feedback on how you’re getting along.

How to get started building engineering skills

Getting an engineering degree

The main way to get started is to do an undergraduate degree in engineering — although if you have a different quantitative degree, you may well be able to get an engineering job. (Read our advice on how to spend your time while at college.)

Engineering degrees are usually in a particular discipline of engineering. However, it can often be fairly easy to switch between engineering courses at university if you find that you’re not enjoying one kind of engineering.

Some universities may offer a ‘general first year’ for engineering in which you can take classes from different engineering disciplines to get a feel for what you enjoy.

Universities may have a range of student clubs or teams that work together to design, fabricate, test, and operate a complex vehicle or device in a national or worldwide competition with other universities. Examples include Formula SAE, the University Rover Challenge, UAS challenge, rocketry competitions (e.g. Australian Universities Rocket Competition), and human-powered vehicle challenges.

These sorts of competitions teach important skills that are invaluable in an engineering career — but they do typically require a large time commitment. Employers often view participation in these sorts of student teams very favourably, so it can give you a leg up in getting a job after graduating.

If you can, do internships in industry. Most large engineering companies run summer internships, and they are a good opportunity to see how industry works and gain some career capital. You could also do an engineering research project over the summer with a research group or join a startup. If all else fails, using the summer to create something also gives you valuable skills and experience — plus it lets you test out how much you like it.

Going into academia

If you want to do engineering in academia, you probably need to do a PhD.

Many people find PhDs very difficult. They can be isolating and frustrating, and take a very long time (4–6 years). What’s more, both your quality of life and the amount you’ll learn will depend on your supervisor — and it can be really difficult to figure out in advance whether you’re making a good choice.

So, if you’re considering doing a PhD, here are some things to consider:

• The topic of your research: It’s easy to let yourself be tied down to a PhD topic you’re not confident in. If the PhD you’re considering would let you work on something that seems relevant to a pressing problem you want to work on, it’s probably — all else equal — better for your career, and the research itself might have a positive impact as well.
• Mentorship: What are the supervisors or managers like at the opportunities open to you? You might be able to find engineering roles in industry where you could learn much more than you would in a PhD — or vice versa. When picking a supervisor, try reaching out to the current or former students of a prospective supervisor to ask them some frank questions. You can also use your final year undergraduate research project to evaluate your fit with a supervisor. (Also, see this article on how to choose a PhD supervisor.)
  Your fit for the work environment: Doing a PhD could mean working on your own with very little supervision or feedback for long periods of time. Some people thrive in these conditions! But some people really don’t and find PhDs extremely difficult.

PhD competitiveness varies by field. To get into any PhD, you’ll probably need high undergraduate grades and some research experience — including a reference from one or more professors. More competitive PhDs might require you to have published papers or extremely strong references. To get those, you might need to spend 1–3 years as a research assistant before applying for PhDs.

Entering industry

You can likely use an undergraduate degree to get an entry-level position in anything ranging from large engineering companies to startups.

In some countries (like the UK), large engineering companies offer graduate programs where you do rotations in different teams in the company. These allow you to build up lots of different skills and knowledge quickly (your ability to choose your rotation depends on the company, the department, and your manager).

Large companies are also likely to have a structured professional development scheme with training, assigned mentors, and regular check-ins to set you up for professional registration as an engineer.

Joining a startup generally means that you have a lot of responsibilities very quickly and less structure around you. This might mean more freedom with what you can do and lots of variety. You might learn a ton, but you won’t get much feedback or mentorship, and there will also be more stress and uncertainty.

Find jobs that use engineering

If you think you might be a good fit for this skill and you’re ready to start looking at job opportunities that are currently accepting applications, see our curated list of opportunities:

View all opportunities

Once you have an engineering skill set, how can you best apply it to have an impact?

Having a big impact as an engineer means finding a particularly pressing global issue and finding a way to use engineering to develop solutions.

Below is a list of pressing global problems and how engineers can help with each.

If you’re already an engineer, you can read through to see if any of these issues appeal to you — and then aim to speak to some people in each area about how your skills could be applied and what the current opportunities are.

You could also apply to speak to our team or get in touch with High Impact Engineers.

Preventing catastrophic pandemics

A future pandemic that is much worse than COVID-19 could pose a significant risk to society.

There’s a key role for bioengineers and chemical engineers to play in mitigating these risks, including:

• Developing vaccine platform technologies to help us rapidly produce new vaccines in response to novel threats
• Developing and implementing metagenomic sequencing to improve our ability to detect new pandemics

Other engineering disciplines are also needed. For example, engineers could:

• Help design better pathogen containment systems for labs and systems to reduce pathogen spread in buildings or vehicles. (There are roles here for materials, civil, industrial, aerospace, and HVAC engineers, among others.)
• Help improve stockpiling and management of PPE (personal protective equipment), such as gloves and masks. (There are possibly roles here for industrial engineers.)
• Help improve technologies for monitoring pathogens, like systems for sampling environments and processes for managing and examining samples. (There are roles here for industrial, mechanical, and automation engineers, among others.)

To learn more, take a look at Biosecurity needs engineers by Will Bradshaw and this overview of using engineering in biosecurity from High Impact Engineers.

AI alignment

We expect AI hardware to be a crucial component of the development of AI. Given the importance of positively shaping the development of AI, experts in AI hardware could be in a position to have a substantive positive impact.

Useful disciplines include:

• Electrical, electronic, and computer engineering (probably the most relevant discipline for AI hardware)
• Materials engineering with a focus on semiconductors
• Industrial engineering with a focus on the semiconductor supply chain

To learn more, read our full career review on becoming an expert in AI hardware.

If you have hardware expertise, you might also consider moving into AI policy. Read our career review of AI governance and coordination to learn more.

Improving civilisational resilience

One very neglected potential way to reduce existential threats is through generally increasing the resilience of our society to catastrophes.

All kinds of engineers can play a big role in this issue — for example by developing alternative foods, refuges, and knowledge stores that will be able to survive a near-apocalypse.

For instance, David Denkenberger is an engineer developing alternative foods that could be rapidly scaled up in the event of a global famine, perhaps caused by nuclear winter or a major volcanic eruption. We have two podcasts with him:

• Using paper mills and seaweed to feed everyone in a catastrophe
• We could feed all eight billion people through a nuclear winter

To learn more about refuges, see this review by Open Philanthropy. Or learn about how to increase the chance of recovery from a catastrophic event in two of our podcast episodes:

• Luisa Rodriguez on why global catastrophes seem unlikely to kill us all
• Paul Christiano on whether we should leave messages for future civilisations

Fight climate change

We think further developing and rolling out green energy is one of the best ways to tackle climate change, and engineers have a major role to play in this. This includes not just generating more green electricity, but also things like ensuring that there is enough electricity to meet seasonal changes in electricity demand and trying to find ways to make other forms of energy greener (like replacing fossil fuel use in blast furnaces or transportation).

You can further increase your impact by focusing on technology that’s either not widely known (e.g. hot rock geothermal) or unsexy (e.g. decarbonising cement rather than developing electric cars).

We have more notes on how to most effectively tackle climate change. We’d also recommend What can a technologist do about climate change? by Bret Victor.

Other problem areas that need engineers

In addition to the top problems mentioned above, there are many other pressing areas where engineers are needed. For example, you could:

• Create alternative proteins through chemical engineering to help reduce meat consumption and prevent the suffering of animals in factory farms.
• Work on tech and logistics for global health, like producing and rolling out vaccines for polio and malaria.
• Try to develop products for people living in poverty — see more about why that can be impactful in our interview with SendWave.

Options outside engineering that can use engineering aptitude

Engineers often have a systems mindset that can make them a particularly good fit for operations management or entrepreneurship. If that work interests you, it’s worth considering whether to spend some time building the skills you’d need to make the transition.

Some engineers may also excel at other options that require good quantitative abilities, such as:

• Working on AI safety technical research
• Software engineering
• Earning to give in a high-paying role, such as quantitative trading

Engineers may be able to easily develop skills in translating technically complex topics to less technical audiences, such as policymakers, which means you could also consider building a policy skill set. For example, TechCongress aims to get engineers, and other technologists, involved as technical advisors for policymakers.

Career paths we’ve reviewed that use engineering skills

• Expert in AI hardware
• Impactful climate solutions
• Biomedical research

Learn more about engineering

• High Impact Engineers
• Will Bradshaw on why biosecurity needs engineers and materials scientists
• A list of potential projects in biosecurity

Read next:  Explore other useful skills

Want to learn more about the most useful skills for solving global problems, according to our research? See our list.

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Could extreme climate change directly lead to the extinction of humanity?

We’re going to review the three most common ways people say climate change might directly cause human extinction: high temperatures, rising water, and disruption to agriculture.

Worst case climate scenarios look very bad in terms of lives disrupted and lost. We’re focusing on extinction because, for reasons we discuss here, we think reducing existential threats should be among humanity’s biggest priorities – in part due to their significance for all future generations.

In short, most scientists think it’s pretty close to impossible for climate change to directly cause the extinction of humanity.

In this generally grim area, this is a piece of good news people don’t always appreciate.

That said, we shouldn’t be unconcerned about climate change — not only does it pose grave dangers short of extinction, we also think climate change indirectly raises the risk of extinction via making other threats worse, which we’ll cover in the next section.

How hot could it get?

The hotter the Earth gets, the worse we can expect effects from climate change to be.

So, to figure out whether climate change could directly cause extinction, we need to know how much we expect temperatures to rise. To figure that out, we first need to have some idea of how much greenhouse gas we’re going to emit, as well as how much of a temperature rise that will produce. We’ll look at each in turn.

How much greenhouse gas could we emit?

The IPCC Sixth Assessment Report considered many illustrative scenarios, including:

• The world meets the goals of the Paris Agreement from COP-21, to limit warming to 1.5°C. (SSP1-1.9)
• The world takes enough action to limit warming to 2°C. (SSP1-2.6)
• There are modest mitigation efforts, with slightly lower emissions than what current policies might suggest. (SSP2-4.5)
• There is a reversal of some current policies, which increases warming. For example, this could happen if countries are competing against each other for growth. (SSP3-7.0)
• There is significant policy reversal. The world decides to use fossil fuels to cause rapid development even if they are more expensive than renewable energy. (SSP5-8.5)

These are the most likely scenarios. But what about the most extreme scenario? What if we tried to burn literally all the fossil fuel in the ground?

The IPCC estimates that there are 18,635 gigatonnes of carbon in the Earth’s fossil fuel reserves.¹

Luckily, fossil fuel extraction methods don’t allow you to extract all the fossil fuels in a deposit — especially with coal. So the question is not how much fossil fuel there is, but how much might ultimately be recoverable with future technology.

The highest estimate we’ve seen on the quantity of recoverable fossil fuels is 2,860 gigatonnes of carbon.²

Releasing 3,000 gigatonnes of carbon would take us to carbon dioxide concentrations in the atmosphere of around 2,000 parts per million (for comparison, pre-industrial carbon dioxide concentrations were 278 parts per million, and current concentrations are 415 parts per million).³

How much warming could happen as a result?

The warming caused by our greenhouse gas emissions will occur in the decades and centuries after the emissions, and is effectively caused by the total amount of carbon emitted.

But actually predicting the total amount of warming caused by some quantity of greenhouse gas is difficult, because there are feedback loops.

Here’s an example of one of those feedback loops: when you heat a metal enough, it glows red. Things at much lower temperatures glow in infrared — that’s why you can see people at night using infrared cameras. The hotter something is, the more energy it releases through this glow (known as black-body radiation). So as the Earth’s temperature increases, it radiates more infrared radiation back into space. This reduces the effect of emissions on global temperatures.

But there are also feedback loops that could make things worse, which we’ll go through here. In the worst cases, these are associated with tipping points, where once a certain amount of greenhouse gas has been released, it triggers some feedback loop that results in an extremely significant and permanent increase in temperature.

The runaway greenhouse effect

We could theoretically see very extreme temperature rises through a runaway greenhouse effect.

We know this is possible because it appears to have happened before: on Venus. Soon after it formed, Venus may have been habitable, with a large water ocean. But Venus formed closer to the Sun than the Earth did, and this slight increase in temperature led to the gradual evaporation of its ocean. Water vapour is a greenhouse gas, so this led to further heating, and further evaporation, eventually moving Venus from a habitable world to one where surface temperatures reach 462°C (864°F), hot enough to melt lead.

Luckily, most models suggest that it’s just not possible, even in principle, for anthropogenic carbon dioxide emissions to reach levels high enough to trigger a runaway greenhouse effect on a Venus-like scale.⁴

And even if we did eventually lose all the oceans to space, this would take hundreds of millions of years. So we’d be very likely to be able to stop the process or find other ways to survive (if something else doesn’t kill us in the meantime).

Cloud feedbacks

One study found that if carbon dioxide concentrations in the atmosphere reach around 1,300 parts per million (which is unfortunately plausible under worst-case scenarios), clouds that shade large parts of the oceans and reflect light back into space could break up.

Many scientists think that the model involved is far too simple to be plausible.

However, there isn’t consensus on this. If the modelling in this study is right, cloud feedbacks would cause an extra 8°C of warming on top of the expected 6–7°C associated with that quantity of emissions. That would bring us into the extreme regions of the effects listed below.

Methane clathrates

Methane clathrate is a substance formed of methane within a crystal of solid water molecules — basically ice with methane trapped in it. There are large quantities of methane clathrates under the ocean floor.

When oceans warm, they could melt these clathrates, releasing further methane into the atmosphere.

The IPCC’s Sixth Assessment Report estimates that there is the equivalent of 1,500–2,000 gigatonnes of carbon dioxide trapped in methane clathrates (approximately twice as much as we have emitted so far). However, they expect any release of clathrates to occur over centuries or millennia, which would give us substantially more time to adapt to any changes.

So the IPCC thinks it’s unlikely that clathrate emissions will cause substantial warming in the next few centuries.⁵

Research into methane clathrate release appears underdeveloped, so there’s a lot we don’t know — and this contributes to our overall uncertainty on how hot it will get.

Melting permafrost

There are permanently frozen layers in the Arctic and other cold regions of Earth. The IPCC estimates that there are 1,460–1,600 gigatonnes of carbon dioxide (or equivalent quantities of other greenhouse gases) stored in permafrost.⁶

Some of this permafrost is already melting, releasing greenhouse gases.

Abrupt thawing could cause up to half of these trapped greenhouse gases to be released immediately, with the rest released more gradually over decades.

The IPCC report says that for each 1ºC of warming, permafrost emissions will increase by 18 gigatonnes of carbon dioxide, with a 5% to 95% range of 3 to 42 gigatonnes. At the upper end of models, we could see up to 600 gigatonnes of carbon dioxide released from permafrost, warming the planet by about an extra degree (on top of the 6ºC we’d already see from human emissions in these scenarios).

Summing up: what is the range of possible temperature increases from climate change?

Given some amount of greenhouse gas we emit, we need to know what the possible temperatures are that Earth could reach.⁷

There’s clearly a minimum possible temperature change; it’s virtually certain that temperatures will go up.⁸

The Sixth Assessment Report gives estimates of how much temperatures will go up under the emission pathways we looked at earlier (which range from meeting the terms of the Paris Agreement to an extreme fossil-fuel burning scenario).

While these estimates do incorporate uncertainty around which feedback loops are plausible (more on that below), they show 90% confidence intervals. That is, (roughly) there’s a 10% chance that temperature changes in each scenario could be higher than the top of the thin lines, or below the bottom of the thin lines (representing the confidence intervals).

In a scenario worse than the IPCC’s worst case, where all the recoverable fossil fuels are burned, there’s a 1 in 6 chance we’d see greater than 9ºC of warming by 2100.⁹ And it looks like there’s an extremely small, but real, chance that this would be enough to cause the worst-case cloud feedback loops.

In total, that would lead to something like 13°C of warming relative to pre-industrial levels. We’d reach that 13°C in the years or decades after we trigger the cloud feedback tipping point — and then there could be additional warming in the centuries and millennia after that. This 13°C of warming would be a humanitarian disaster of unprecedented scale.

As far as we can tell, reaching 13°C is very unlikely, and about as hot as our models suggest it could possibly get on short timescales we might not be able to adapt to.¹⁰

Now we’ll turn to whether this warming could directly cause human extinction — via pure heat stress, sea level rise, or agricultural collapse.

Could climate change simply make it too hot for humans to survive?

On the hottest and most humid days, you’d walk outside and it felt immediately like someone pressed a hot wet towel, like you sometimes get on airplanes, over your entire head. I wear glasses, and they’d immediately fog up. You sweat instantly. People just avoid being outside in any way they can. In the summers, my friends and I would become nocturnal as a way to beat the heat.

John Hagner, on living in Dharan, Saudi Arabia (one of the most heat-stressed inhabited places in the world)

If temperatures rise high enough, it becomes too hot for humans to survive for more than a few hours — even in the shade. In places with high humidity, like the tropics, it’s harder to cool through sweating, so this effect is even worse.

This could make significant parts of the planet uninhabitable (at least outdoors, or without air conditioning) for significant portions of the year. This map shows the number of days per year we’d get surface temperatures greater than 35°C (95°F) in various regions on Earth, if we had around 7°C of warming. This is a good illustration of the sorts of areas that might become too hot for humans to survive with more than 7°C of warming.¹¹

If there were 12°C of warming, a majority of land where humans currently live would be too hot for humans to survive at least a few days a year.¹² An increase of 13°C would make working outdoors impossible for most of the year in the tropics, and around half the year in currently temperate regions.

But even with the cloud feedback loop, it would take decades for global temperatures to reach this level, and while this worst-case scenario would cause extraordinary suffering and death, it seems very likely that we could adapt to avoid extinction (for example, by building better buildings and widespread air conditioning, as well as building more in the cooler areas of the Earth).

Moreover, it would be hard for this to lead directly to extinction even if we didn’t adapt, given that a large chunk of land on Earth would remain habitable, even with 13°C of warming. We would have to live in a much smaller area, but civilisation would survive.

Could the world sink under water?

The IPCC’s Sixth Assessment Report projects a sea level rise of around one metre by 2100 if we see 5°C of warming above pre-industrial levels — in worst-case scenarios, this could be up to two metres.

This map shows the areas that will be below high tide by 2100 if there were 5°C of warming, assuming a 95th percentile worst-case scenario. (That is, there are various proposed effects that could help reduce the amount the seas will rise, and this map assumes that these largely won’t occur.)

Modelling sea level rise is difficult, so there’s large uncertainty on how bad it could get. And over centuries, sea level rise could be much higher. The IPCC says that, in the worst emissions scenario we’ve considered with around 6°C of warming, “sea level rise greater than 15m [by 2300] cannot be ruled out.”

We haven’t seen any modelling on sea level rise with 13°C of warming. As an upper bound, we can consider what would happen if the polar ice caps melted completely. The highest estimate we’ve seen is that this would produce sea level rise of around 80 metres. Fifty of the world’s major cities would flood, but the vast majority of land would remain above water.

As with heat stress, we’ll probably be able to adapt to these changes, particularly through building new infrastructure like homes or flood defences. And the fact that it will take centuries for sea levels to rise completely means this adaptation will likely be much easier.

It seems that a one-metre sea level rise would, without adaptation, displace around half a billion people from their homes. But with adaptation (like building flood defences), the number of people displaced would be much smaller: the IPCC estimates that hundreds of thousands of people would in reality be displaced due to a two-metre sea level rise, far fewer than half a billion.

We know this adaptation is possible because we’ve seen adaptation to rapid sea level rise before. Tokyo is sinking into the ocean, and experienced effectively four metres of sea level rise in the 20th century.¹³ This rise happened at a rate of about 40 millimetres per year, which is similar to what we’d expect with the IPCC’s worst-case projections.

So sea level rise will cause substantial suffering and disruption to our society, particularly in developing countries. And our adaptation will be expensive — the IPCC projects that, with 4–5°C of warming, we’ll be spending over 1% of our GDP adapting to floods.

But, as with heat stress, sea level rise does not pose an extinction risk.

Could climate change destroy global agriculture?

The IPCC’s Special Report on Climate Change and Land reports that hundreds of millions of additional people will likely be at risk of hunger by 2050 as a result of climate change.

On top of extreme events like hurricanes or droughts disrupting agriculture, we can expect temperature changes, changes in rainfall, and other weather-related changes to significantly harm our ability to grow food.

There may also be some positive effects of climate change on agriculture — for example, we’ll be able to grow crops in areas that are currently too cold. It’s possible that these effects would be enough to completely mitigate the negative effects on agriculture.

With more extreme warming, higher temperatures will directly affect agriculture.

The chemical reactions plants need to survive (including photosynthesis and respiration) can’t operate if temperatures are too high.

As a result, more than 10°C of warming would be likely to destroy agriculture in India and regions with similar climates.

We could also see substantial changes in precipitation levels that, under extreme scenarios, would significantly harm agriculture. This map shows changes in precipitation by 2050 in various regions, under a high-emissions scenario.¹⁴

(In general, predictions about precipitation and other weather changes, like the frequency of extreme weather events, are difficult to make and vary significantly between models — so take all these figures with a grain of salt!)

But even with all these likely disruptions, we should still be able to adapt — due to increasing agricultural productivity. Over the past few centuries, food prices have fallen as technology makes it cheaper and cheaper to produce large quantities of food.

So it is against this backdrop of rapidly improving productivity that climate change will act — and even if temperatures rise a lot, it’ll take some time (decades or maybe centuries) for that to happen. As a result, the IPCC expects (with high confidence) that we’ll be able to adapt to climate change in such a way that risks to food security will be mitigated.

One expert we spoke to did say that their best guess is that a 13°C warmer world would lead — through droughts and the disruption of agriculture — to the deaths of hundreds of millions of people. But even this horrific scenario is a long way from human extinction or the kind of catastrophic event that could directly lead to humanity being unable to ever recover.

How would extreme climate change affect biodiversity?

It’s possible that climate change could lead to ecosystem collapse. Many ethical views put intrinsic value on biodiversity — and even if you don’t, ecosystem collapse could affect people and nonhuman animals in other ways.

Estimates on the proportion of species that could go extinct from climate change vary, but in the worst cases, models predict up to 40% of species could be “committed to extinction” by the middle of the century.¹⁵

So extreme climate change could have significant negative effects on biodiversity. What about the instrumental importance of biodiversity? Could reduced biodiversity exacerbate the effects of extreme warming on agriculture? In order for this to happen, we’d have to see something crucial to our food chain go extinct. One plausible possibility here is that pollinators — whose populations are already in decline — could go extinct. But models suggest our agricultural production would drop by only around 10% if we didn’t have pollinators.¹⁶ Kareiva and Carranza at the Cambridge Centre for the Study of Existential Risk looked into this in more detail and concluded that ecosystem collapse is extremely unlikely to pose risks to human existence.¹⁷

There are, of course, many other benefits to biodiversity, like the development of new medicines. But overall, biodiversity loss seems like it won’t cause the collapse of civilisation.

Summing up: why climate change almost definitely won’t directly cause human extinction

If we follow current policies, we’ll probably end up seeing around 2–3°C of warming by 2100. It’s also possible that we’ll see a reversal of current attempts to reduce emissions. This could happen if sectors of the economy that we can’t decarbonise grow rapidly, such as if we develop new technology that uses large quantities of energy, or if something like a large war incentivises high-carbon activities.

In a worse scenario, we’ll burn fossil fuels even though they’re more expensive than renewable energy. And in the worst-case, but extremely unlikely, scenario, we could burn all the recoverable fossil fuels and reach 7°C of warming.

There’s also a very small chance that in these unlikely scenarios where we rapidly burn far more fossil fuels than we are currently on track to, that cloud feedback tipping points could be reached. This could lead to something like 13°C of warming.

Though this would be a humanitarian disaster of unprecedented proportions, humanity would still have land cool enough to live on, it won’t all be submerged in the ocean, and we will still be able to grow food in many places, though not all. In other words, humanity would survive.

But does this conclusion adequately take uncertainty into account?

After all, any time we try to use what we’ve discovered so far to make predictions about the future, we have to be aware that there could be things we don’t know which could make things worse than we expect.

We saw above that one source of uncertainty is the possible emission pathways that we will follow in the future. We tried to take that into account by considering a wide range of scenarios – including us burning all ultimately recoverable fossil fuels.

We’ve also seen structural uncertainty: that is, uncertainty in our predictions because there are things we don’t know about how the system works — for example, whether methane clathrates will cause substantial warming in the next few centuries.

The IPCC’s Sixth Assessment Report, building on Sherwood et al.’s assessment of the Earth’s climate sensitivity attempts to account for structural uncertainty and unknown unknowns. Roughly, they find it’s unlikely that all the various lines of evidence are biased in just one direction — for every consideration that could increase warming, there are also considerations that could decrease it.¹⁸

This means we should expect unknowns mostly to cancel out, and be surprised if they point in one direction or the other.

There are a few caveats:

• The higher our emissions are, the further they get from the sorts of baseline assumptions the IPCC used to come to this conclusion. So if we’re really very wrong about the amount of carbon emissions we’re likely to emit, things could still get very bad (but it seems unlikely we’re very wrong about that).
• There is much more uncertainty about how other things will change. For example, it’s hard to predict how high sea levels will rise or how precipitation patterns will change (although even then we don’t think these things will change in ways that increase the direct risk of extinction).

But overall, despite our lack of knowledge about some relevant feedbacks, this makes for a very small chance that model uncertainty means things could be radically worse.

As a result, it’s extremely unlikely (we’d guess less than a 1 in 1,000,000 chance) that we’ll see the temperature changes necessary for climate change to have the kinds of effects that would directly lead to extinction.

How climate change could cause extinction indirectly anyway

We’ve argued that climate change is very, very unlikely to directly cause human extinction.

But climate change seems to contribute to the risk of human extinction anyway, by making other existential threats worse.

Here we’ll go over the common factors people put forward to argue that climate change might increase extinction risk, and how big a contributor we think each factor really is.

Climate change will likely increase migration, which could lead to instability

As we’ve seen, higher temperatures and rising sea levels will significantly affect where people are able to live. And other factors (like changes to agriculture) will affect where people are able to make a living, also leading to more migration.

According to the IPCC’s Fifth Assessment Report, a half-metre sea level rise (without governments implementing adaptive measures) implies the displacement of 72 million people; a two-metre sea level rise (something like the IPCC’s worst-case scenario) would displace 2.5% of the world’s population. These figures assume we wouldn’t act to prevent this displacement — measures like building protective dikes could reduce this to less than half a million people.

If there’s more extreme warming, we’ll see more extreme migration. At 6°C of warming, warmer areas without air conditioning could become unlivable, causing migrations of potentially hundreds of millions of people.

It’s often claimed that displaced populations can increase resource scarcity and the risk of conflict in countries that they move to. Forced displacement also arguably increases the spread of infectious diseases and general political tensions. But it’s very difficult to estimate the size of these effects — and from there, to estimate the implications of these effects for the rest of society.

How might this increase extinction risk? The biggest route is through increasing conflict and therefore the risk of great power war, which seems like a significant risk factor for extinction.

We’ll turn directly to that factor now.

Will climate change increase global conflicts?

Climate change’s clear ability to create economic shocks, migration crises, and resource scarcity makes it completely plausible that there will be (as there have already been¹⁹) conflicts at least partially caused by climate change.

Lots of this conflict is likely to be civil conflict in areas that are already unstable and are particularly vulnerable to climate change (the IPCC’s Fifth Assessment Report focuses on civil war in Africa).

There’s also the possibility of much larger wars. If climate change significantly affects the fortunes of Russia, China, India, Pakistan, the EU, or the US, this could cause a great power war. Migration crises, heat stress, sea level rise, changes to agriculture, or broader economic effects on these countries could all contribute to the chances of conflict.

This is all pretty speculative, but we still think it’s worth taking seriously.

Conflict makes it harder to solve coordination problems. For example, it incentivises dangerous arms races, which are even more dangerous when they’re between great powers. Because of this, it stands to reason that conflict — especially between powerful nations — increases existential risk.

Climate change could make society less stable in other ways

There are many other proposed pathways for climate change to make our society generally less stable. For example:

• Reduction in tax revenues because of changes to the economy (e.g. if a country’s agricultural land becomes less productive) can make people in power less able to act. This changes the relative strengths of political factions, making changes in governments more likely.
• Climate change could hurt people’s economic prospects, which can create desperation and violence. This can be a key cause of civil unrest and civil war.
• When climate change causes hardship, populations may (correctly or incorrectly) blame their governments, increasing political instability.

It’s also possible that we could be driven to develop destabilising technology to change our climate with the intention of averting catastrophe — e.g. solar geoengineering. But this poses its own risks, as it will be near impossible to carry out experiments on the global scale we’d need to act in order to verify the safety of our technology. And technology to change the weather could in turn lead to conflict between (or within) states over things like induced droughts or rainfall.

Summing up: how climate change makes global catastrophic risks worse

Risks to humanity (like nuclear war or pandemics) don’t just affect particular groups or countries, so we shouldn’t be surprised if many of the most promising solutions require global cooperation.

Fortunately, if we have the ability to cooperate to reduce these risks, we expect that we will. After all, if we don’t, the consequence is global catastrophe! But actually having this ability is vital.

Unfortunately, it seems like climate change will reduce our ability to cooperate.

For example, it’s been suggested that increased resource scarcity (in particular water scarcity) caused by climate change could increase the risk of conflict in Kashmir, one of the most important flashpoints for great power and potentially nuclear war (in this case, between India and Pakistan, even though both sides have an interest in avoiding war). We’re not sure this is right, but it doesn’t seem impossible.

General instability also increases the risk of individual actors like terrorist groups unilaterally acting to cause a catastrophe. And this sort of deliberate harm is one of the key ways we could succumb to a global catastrophic biological risk.

We think that the 21st century could plausibly be humanity’s most important due to rapid technological progress, especially in artificial intelligence. If that’s true, we’re going to want to be very careful to ensure it goes well. Lots of unpredictable things will happen, and climate change will be a key cause of many of them. And the worse climate change becomes, the more unpredictable these things will be. That in itself might be a strong reason to dedicate your career to working on climate change.

That said, we still think this risk is relatively low. If climate change poses something like a 1 in 1,000,000 risk of extinction by itself, our guess is that its contribution to other existential risks is at most a few orders of magnitude higher — so something like 1 in 10,000.²⁰

So yes, climate change makes other existential risks worse. But humanity is still much, much more likely to survive climate change than not.

What about global catastrophes that aren’t extinction?

Even if climate change is very unlikely to cause humanity to go extinct (directly or indirectly), could it still cause a global catastrophe on such a scale as to cause the deaths of a significant proportion of the population (say, more than 10%)?

We haven’t thought about this possibility as much, but the same reasons we think climate change won’t lead to extinction suggest it won’t lead to a catastrophic event of this size. In short: even in the worst-case warming scenarios, a lot of humans will still be able to live on the land and grow food.

Even in the top 1% of worst scenarios, our guess is that it is extremely unlikely for premature deaths due to climate change to exceed a billion people, and this loss would likely be gradual (e.g. over a century) and due to things like declining economic productivity, rather than an all-at-once catastrophic collapse. This is still an immense amount of death and suffering, and we hope global leaders will ensure this does not come to pass.

However, gradual problems in general seem easier to adapt to, meaning the risk that humanity doesn’t ever recover from the effects of catastrophic (but not immediate-extinction-level) climate change seem very low — lower than, for example, an all-out nuclear war.

Again, the indirect threat from climate change seems greater here. For example, perhaps international tensions worsened by climate-related stressors will lead to such a war.

All in all, we think the risk of a sub-extinction-level global catastrophe that kills a billion or more people from climate change is still very low.

How else could climate change affect the long-term future?

Even if you don’t agree with our focus on existential risks (perhaps because you think we’re nearly guaranteed to survive the next few centuries), you might still wonder how else climate change could affect generations long into the future.

Carbon dioxide can stay in the atmosphere for thousands of years, which means that warming can continue for hundreds of thousands of years after we stop emitting — and this warming could continue to have negative effects on our society.

For example, if we have a one-metre sea level rise in the next 100 years, we can expect to see 10 metres of sea level rise over the next 10,000 years.

This means that, if we avoid existential catastrophe and humanity continues to live on Earth, future generations could be dealing with the negative effects of climate change for a long time.

Moreover, if climate change gets very bad, that probably means we burned through our fossil fuel reserves. This isn’t an effect of climate change per se, but rather an effect of us not doing enough to prevent it by reducing fossil fuel use. Besides causing climate change and everything that that entails, using up our fossil fuel reserves would mean that if humanity does suffer a (different) global catastrophe that leads to a civilisational collapse, it might be harder to rebuild.

This is because fossil fuels are one of the densest and most accessible forms of energy. Imagine, for example, we were in a nuclear winter after a global nuclear war, and needed to get everything back up and running after losing the technology and know-how we’ve built over the last 100 years. It would be extremely useful in that case to be able to temporarily burn fossil fuels in order to redevelop society. But if we’ve burned them all already, we won’t be able to do that. (Listen to our podcast with Luisa Rodriguez on how we might recover from a global civilisational collapse for more.)

Should you work on climate change or another global issue?

There are lots of global issues that deserve more attention than they currently get. This includes climate change, but also others that seem to pose a more material risk of extinction — like catastrophic pandemics or nuclear war.

If you want to make the biggest difference you can with your career, and like us, you think that reducing existential threats is a top priority, which should you focus on?

Reasons to work on climate change

Even if it’s not an extinction risk, our discussion above shows that climate change could still be hugely important for the present and future of life on Earth. The worse it gets, the more likely it is to reduce biodiversity, displace people around the world, destroy people’s livelihoods, and destabilise society. That alone is a reason to work on it.

But something being important isn’t necessarily a decisive reason to work on it. Our framework for comparing global problems suggests you should also consider:

• How solvable is climate change?
• How neglected is working on climate change?
• And how does it compare to other issues you could work on instead?

Climate change seems unusually solvable for a global issue: there is a clear measure of our success (how much greenhouse gas we are emitting), plus lots of experience seeing what works — so there is clear evidence on how to move ahead.

There’s also a lot of opportunity to work on climate change. Europeans and many Americans agree that climate change is one of the most important issues of the 21st century, and there are therefore many opportunities to work on the issue in government, business, and academia.

This means that if you are able to get into a position of power, you can leverage a lot of resources.

Because lots of people think climate change is important, the easiest ways of making a big difference have likely already been taken (more on that just below).

However, some important work on climate change does appear to be relatively neglected. Not much research is focused on how climate change interacts with other potential catastrophic risks. And working on clean energy tech also seems neglected relative to its importance for solving the problem, though it still gets a lot of resources.

Your work also might have positive side effects. For example, reducing our reliance on burning fuels might also reduce air pollution, which causes millions of deaths per year. Working on extreme climate change could indirectly help promote positive values, such as caring about future generations, and it’s possible that finding effective ways of mitigating climate change could serve as a blueprint for future efforts to tackle global threats.

Reasons not to work on climate change

It’s not as neglected as other issues

Climate change as a whole gets a lot of attention and funding. In particular, it gets much more attention than many other pressing global issues.

The US federal budget included about $23 billion of climate change spending in the 2021 fiscal year. The UK spent about £4 billion in the 2021–22 financial year. And several hundred million dollars are spent each year by foundations.²¹ Philanthropic spending on climate change is $5–10 billion a year. On top of this, many businesses and universities around the world work on general climate change research or technologies designed to reduce emissions. The Climate Policy Initiative counted over $600 billion in climate-related spending in 2020.

In comparison, biosecurity in general receives around $3 billion per year, preventing catastrophic pandemics in particular receives around $1 billion, and reducing risks from artificial intelligence receives between $10 million and $50 million.²²

If a problem is less neglected, it will be harder for an additional person to make as much of a difference working on it.

Other existential threats seem considerably greater

Another consideration is that, for all that climate change is a serious problem, there appear to be other risks that pose larger threats to humanity’s long-term thriving.

Experts studying risks of human extinction usually think nuclear war, great power conflict in general, and certain dangerous advances in machine learning or biotechnology all have a higher likelihood of causing human extinction than climate change.

This seems roughly right to us.

You might think that, for the reasons discussed above, climate change is a substantial enough factor contributing to other risks to be worth prioritising. That wouldn’t be an unreasonable view.

But these other, often more direct threats to humanity often also act as contributing factors. For example, pandemics can increase geopolitical tensions, and thus risks of conflict. And some of them — especially engineered pandemics and risks from misaligned AI — seem to be direct extinction threats themselves on top of that.

So, if you agree that we face substantially more direct existential threats, then to think climate change is more important you need to think that climate change is a much larger risk factor than other things — so much larger that this outweighs the difference in direct risk. We think it probably doesn’t.

That said, there are other factors that determine what you should work on — in particular, it’s important to consider your personal fit for jobs in an area (and we’ve definitely spoken to people who are best suited to working on climate change rather than any other issue). But in our experience, it seems like many people underestimate their ability to, with a bit of training, work on issues they’re less familiar with. People also seem to underestimate the range of positions — and therefore the different kinds of work they could excel at — in different cause areas.

As a result, while we agree that it’s crucial we work on reducing existential threats to humanity, and agree that climate change increases those threats, we usually recommend people interested in safeguarding humanity’s future focus on bigger and more direct existential threats if they can.

But given that many people will work on climate change in their careers (and in absolute terms, we hope that more people do, even if we also hope many of our readers will prioritise more direct risks), we’d like to say something about how to do that as effectively as possible.

What are the best ways of working to solve climate change?

Many popular approaches to working on climate change and other environmental problems probably aren’t actually that helpful.

For example, the increased land use from organic farming means it could actually increase emissions compared to regular farming. And eating locally produced food — a popular idea for reducing your carbon footprint — is far less important than what food you choose to eat, because transportation is such a minor part of the emissions from food.

The same applies in government policy. Governments across the world have attempted to disincentivise the use of disposable plastic bags (in favour of non-disposable alternatives), but this may have actually increased emissions:

Other things work but could be really expensive (costing $100 or more per tonne of carbon dioxide removed from or prevented from going into the atmosphere). For example, planting trees sounds like it could be effective, but trees’ slow growth, risks of things like wildfires, and the high cost of land may make this a particularly expensive way of reducing greenhouse gases.

We’ll talk about ideas for cutting emissions that seem more cost effective below.

But in general we want to note that your personal carbon footprint is largely a distraction. If you cut your emissions by 50% you’ll save 2–10 tonnes of carbon dioxide per year, whereas a carefully considered donation (for example to the Founders Pledge Climate Change Fund) of only $10 could do more to reduce emissions than that.

And spending time working on the issue could be even better.

Some considerations to help you figure out what to work on

A few key ideas shape what we think is most effective to work on to address climate change.

First, emissions in Europe and North America are declining,²³ but emissions are rising elsewhere.

Developing countries use much less energy per person and will need to keep their energy consumption growing in order to raise living standards — something people in poorer countries desperately need.²⁴

So we need to reduce emissions across the world, but without harming living standards. This puts some constraints on which interventions are most important to carry out.

Second, solutions that require coordination are difficult to achieve. This is true on both an individual level and a country level.

Reducing emissions benefits everyone more than it benefits any one individual. For example, if the US became net zero, all countries would benefit from reduced harms from climate change, but the US would only get a fraction of the overall benefit from their actions (while bearing the entire cost). So you should expect individuals and countries to be doing less than would be best for the world.

For this reason, focusing on developing and deploying new technology seems more likely to succeed (and has fewer downsides, and faces fewer coordination issues) than seeking to encourage individuals to voluntarily reduce their energy consumption. This is because it doesn’t cost the innovator much; they can benefit from selling their inventions.

This means low- or no-emissions technology is likely one of the biggest levers there is.

Third, spending on climate change is gigantic but may neglect key things.

We argued earlier that climate change seems less neglected overall than other areas, with spending at $640 billion a year.

This means that, if you can identify important but neglected sub-areas within climate change, advocating for more resources for those areas or shifts in the prioritisation of existing resources could be hugely impactful. Small proportional shifts can move large amounts of money.

Reducing net greenhouse gas emissions — especially through green tech innovation

We think one of the most promising ways to reduce greenhouse gas emissions is working on research and development in green energy.

Green energy has an incredible track record of returns, could help solve problems in more than just one country, and doesn’t require convincing other people to act. For example, asking people not to drive asks them to make a personal sacrifice, whereas developing emissions-free cars solves the problem without relying on that choice.

Renewable energy is now often cheaper than fossil fuels — this could be a key reason why emissions are falling in Europe and North America.

To really maximise your impact, focus on tech that is less widely known. Why? You could propel forward a field that otherwise wouldn’t get off the ground, or wouldn’t get off the ground for a long time.

For example, emissions from cars are only about four times higher than emissions from cement, but there’s much more than four times the focus on electric cars. That means there could be better opportunities to move the needle by greening cement production. We think that means working on the latter could plausibly be better — there might be low-hanging fruit you can pick (take a look at our career review of engineering).

By the same token, working on hot rock geothermal could be higher impact than working on solar or wind energy — though we don’t know because so few people are looking into it.

There’s also value in technology that increases energy efficiency, for example by reducing the costs of building better-insulated buildings. And it’s also important to look at the barriers in deploying and scaling technology that’s already been developed to find potentially neglected ways to lower costs.

You could also work on policy advocacy and leadership. While each country’s emissions are small on their own, successful policy can spread across the world, helping to reduce net emissions.

Unfortunately, we’ve too often advocated for ineffective or intractable policy.

Economists have advocated for carbon pricing for decades. From a simple economic perspective, pricing in the negative externality of emissions should optimally produce the efficient solution. But despite these decades, the net global carbon price is actually negative $10.49 per tonne²⁵ — we’re still subsidising carbon overall.

We haven’t looked into this in detail, but it seems like there could be significant political barriers to carbon pricing that are difficult to overcome.

Instead, we should focus on tractable policies with a track record of success. For example, the UK has almost completely removed its use of coal for power generation through a mix of implementable regulations and subsidies. Other countries like Sweden and France have had huge success in deploying nuclear power, and it’s possible that with appropriate advocacy this could happen elsewhere too.

If you’re interested in advocacy, you might want to read our reviews of policy careers and communications careers more broadly.

Research into carbon removal technology (but not solar geoengineering)

Carbon removal technology, like negative emissions tech or carbon capture and storage, seems pretty neglected compared to green energy (read a popular overview), and could be a crucial way of reducing the effects of our emissions on the climate.

Removing carbon in this way is a form of geoengineering — deliberate intervention in the climate. The other primary form of geoengineering is solar geoengineering (deliberately deflecting sunlight away from Earth to cool the planet down). Solar geoengineering poses potential risks to humanity in itself, given the unprecedented scale of the intervention and the fact that, once in use, solar geoengineering can’t be left untended without disastrous effects. These risks could be larger than the risks from climate change itself, so we think it’s potentially harmful to do work that could advance solar geoengineering.

Geoengineering research of all kinds is mainly done in academia. The Oxford University Geoengineering Programme conducts research into the social, ethical, and technical aspects of geoengineering.

Research on extreme risks from climate change

We don’t think that climate change is likely to cause a catastrophe by itself that would collapse society or kill a substantial proportion (>10%) of the population. But, as we’ve argued, the indirect effects of climate change could contribute to increasing existential threats.

But as we saw above, it’s hard to say exactly how much they contribute — and how to best mitigate those effects. This is because most research hasn’t been focused on extreme-risk scenarios or the interaction between climate and other existential threats.

So, increased investment in some areas in climate research may be able to better inform policymakers, as well as the public at large, about the likelihood of the extreme risks of climate change (both direct and indirect), as well as uncover strategies to reduce those risks.

What research there is on extreme climate change occurs mainly in academia and is funded by basic science funders like the US National Science Foundation. The Centre for the Study of Existential Risk at the University of Cambridge and the Global Catastrophic Risk Institute are conducting research into extreme climate change and possible responses.

For more on what this kind of work might be like, read our career review of academic research.

Find opportunities on our job board

Our job board features opportunities in climate change:

View all opportunities

Key questions we’re unsure about

It’s really difficult to come to robust conclusions about climate change, especially when you’re focusing on the worst possible outcomes.

As a result there are several questions where we’re uncertain about the answers — and, if we had a different answer, our advice could change substantially. These include:

• How hot could it really get? Is our research (or our reasoning) wrong? Would more research into this question give us more certain answers, or is it just too hard?
• How important are extra feedback loops and tipping points that aren’t usually included in climate models, or that we just haven’t thought of yet?
• How big of an indirect risk factor for human extinction is climate change? Through what pathways? Again, would more research into this question give us more certain answers, or is it just too hard?
• Which areas within climate work (e.g. extreme risks, links to other risks, or specific kinds of green tech) are most neglected relative to their impact?

Learn more

Top recommendations

• Johannes Ackva on unfashionable climate interventions that work, and fashionable ones that don’t
• John Halstead’s informal report on climate change and existential risk
• Founders Pledge‘s full report on high-impact climate philanthropy (PDF) (2021)

Further recommendations

Read next:  Explore other pressing world problems

Want to learn more about global issues we think are especially pressing? See our list of issues that are large in scale, solvable, and neglected, according to our research.

Continue →

Acknowledgements

Huge thanks to Goodwin Gibbins, Johannes Ackva, John Halstead, and Luca Righetti for their extremely thoughtful and helpful comments and conversations.

The post Climate change appeared first on 80,000 Hours.

On December 31, 2020, the four most valuable companies were: Apple, Microsoft, Amazon, and Google.

On December 31, 2019, the four most valuable companies were: Apple, Microsoft, Google, and Amazon.

And on December 31, 2018, the four most valuable companies were: Microsoft, Apple, Amazon, and Google.

If you’re anything like me, you’re starting to spot a pattern here.

Revenue in software has grown from $400 billion in 2016 to $500 billion in 2021, and is projected to reach $800 billion by 2026.

Software has an increasing and overwhelming importance in our economy — and everything else in our society. High demand and low supply makes software engineering well-paid, and often enjoyable.

But we also think that, if you’re trying to make the world a better place, software engineering could be a particularly good way to help.

This review owes a lot to helpful discussions with (and comments from) Andy Jones, Ozzie Gooen, Jeff Kaufman, Sasha Cooper, Ben Kuhn, Nova DasSarma, Kamal Ndousse, Ethan Alley, Ben West, Ben Mann, Tom Conerly, Zac Hatfield-Dodds, and George McGowan. Special thanks go to Roman Duda for our previous review of software engineering, on which this was based.

Why might software engineering be high impact?

Software engineers are in a position to meaningfully contribute directly to solving a wide variety of the world’s most pressing problems.

In particular, there is a shortage of software engineers at the cutting edge of research into AI safety.

We’ve also found that software engineers can contribute greatly to work aiming at preventing pandemics and other global catastrophic biological risks.

Aside from direct work on these crucial problems, while working for startups or larger tech companies you can gain excellent career capital (especially technical skills), and, if you choose, earn and donate substantial amounts to the world’s best charities.

How to do good as a software engineer

Even for skilled engineers who could command high salaries, we think that working directly on a problem will probably be more impactful than earning to give.

Some examples of projects where software engineering is central to their impactful work:

• Ought is an AI research lab attempting to build systems that apply machine learning to the task of helping people think.
• The Secure DNA Project is attempting to build a secure global screening system for DNA sequences that could be used to engineer a global pandemic.
• Momentum is a startup building donation pages that encourage recurring donations to the world’s most effective charities.
• Lightcone Infrastructure builds software-based infrastructure for longtermist projects.
• Telis Bioscience is a startup attempting to radically accelerate drug development to mitigate risks from future pandemics.
• Anthropic is a research company working to build reliable, interpretable, and steerable AI systems.
• Redwood Research conducts applied research into the challenge of aligning artificial intelligence.
• Wave is a startup building a way for people in developing countries to access financial services.

Most organisations, even ones that don’t focus on developing large software products, need software engineers to manage computer systems, apps, and websites. For example:

• Effective Altruism Funds provides expert-managed funds to facilitate donors maximising the impact of their donations. They use software engineers to design and maintain their online platform.
• Our World in Data, founded by Max Roser, collects and presents data on many of the world’s most pressing problems. They use software engineers to maintain their website, analyse data, and develop their open-source data visualisation tool.
• Here at 80,000 Hours, our team includes two software engineers working on our website and other technology.
• The Centre for Effective Altruism‘s tech team supports a variety of projects across the effective altruism community, such as the Effective Altruism Forum.

Many people we’ve spoken to at these and other organisations have said that they have real difficulty hiring extremely talented software engineers. Many nonprofits want to hire people who believe in their missions (just as they do with operations staff), which indicates that talented, altruistic-minded software engineers are sorely needed and could do huge amounts of good.

Smaller organisations that don’t focus on engineering often only have one or two software engineers. And because things at small organisations can change rapidly, they need unusually adaptable and flexible people who are able to maintain software with very little help from the wider team.¹

It seems likely that, as the community of people working on helping future generations grows, there will be more opportunities for practical software development efforts to help. This means that even if you don’t currently have any experience with programming, it could be valuable to begin developing expertise in software engineering now.

Software engineers can help with AI safety

We’ve argued before that artificial intelligence could have a deeply transformative impact on our society. There are huge opportunities associated with this ongoing transformation, but also extreme risks — potentially even threatening humanity’s survival.

With the rise of machine learning, and the huge success of deep learning models like GPT-3, many experts now think it’s reasonably likely that our current machine learning methods could be used to create transformative artificial intelligence.

This has led to an explosion in empirical AI safety research, where teams work directly with deep neural networks to identify risks and develop frameworks for mitigating them. Examples of organisations working in empirical AI safety research include Redwood Research, DeepMind, OpenAI, and Anthropic.

These organisations are doing research directly with extremely large neural networks, which means each experiment can cost millions of dollars to run. This means that even small improvements to the efficiency of each experiment can be hugely beneficial.

There’s also often overlap between experimental results that will help further AI safety and results that could accelerate the development of unsafe AI, so it’s also important that the results of these experiments are kept secure.

As a result, it’s likely to remain incredibly valuable to have talented engineers working on ensuring that these experiments are as efficient and safe as possible. Experts we spoke to expect this to remain a key bottleneck in AI safety research for many years.

However, there is a serious risk associated with this route: it seems possible for engineers to accidentally increase risks from AI by generally accelerating the technical development of the field. We’re not sure of the more precise contours of this risk (e.g. exactly what kinds of projects you should avoid), but think it’s important to watch out for. That said, there are many more junior non-safety roles out there than roles focused specifically on safety, and experts we’ve spoken to expect that most non-safety projects aren’t likely to be causing harm. If you’re uncertain about taking a job for this reason, our team may be able to help you decide.

Software engineer salaries mean you can earn to give

In general, if you can find a job you can do well, you’ll have a bigger impact working on a problem directly than you would by earning money and donating. However, earning to give can still be a high-impact option, especially if you focus on donating to the most effective projects that could use the extra funds.

If you’re skilled enough to work at top companies, software engineering is a well-paid career. In the US, entry-level software engineer salaries start at around $110,000. Engineers at Microsoft start at $150,000, and engineers at Google start at around $180,000 (including stock and bonuses). If you’re successful, after a few years on the job you could be earning over $500,000 a year.

Pay is generally much lower in other countries. Median salaries in Australia are around 20% lower than salaries in the US (approximately US$80,000), and around 40% lower in the UK, Germany, Canada, and Japan (approximately US$60,000). While much of your earnings as a software engineer come from bonuses and equity, rather than just your salary, these are also lower outside the US.

If you do want to make a positive difference through donating part of your income as a software engineer, you may be able to increase your impact by using donation-matching programmes, which are common at large tech companies (although these are often capped at around US$10,000 per year).

You can read more about salaries at large tech companies below.

It’s important to note that many nonprofit organisations, including those focusing on AI safety, will offer salaries and benefits that compete with those at for-profit firms.

If you work at or found a startup, your earnings will be highly variable. However, the expected value of your earnings — especially as a cofounder — could be extremely high. For this reason, if you’re a particularly good fit, founding a tech startup and donating your earnings could be hugely impactful, as you could earn and donate extraordinary amounts.

What does a software engineering career involve?

Ultimately, the best ways to have an impact with software engineering are probably things like working at an AI lab or a particularly effective nonprofit.

To get there, there are two broad paths that you could follow to build software engineering skills (and, given the high salaries in software engineering, you can earn to give along the way):

1. Working for a large, stable company (e.g. Microsoft, Google, Amazon)
2. Working for a small, fast-growing startup

In general, you will gain broadly transferable skills through either of these options. To gain experience as quickly and effectively as possible, look for roles that offer good management and mentorship opportunities. You should also make sure you gain a really deep understanding of the basics of software development.

Working at a top-tier tech company also holds comparable prestige to working in finance or consulting, and gives you the opportunity to make connections with wealthy and influential people, many of whom are impact-minded and interested in doing good.

You’ll need different skills, and work at different jobs, depending on whether you want to be a front-end, back-end (including machine learning), or full-stack developer.

Working for a large software company

The best way to develop software skills is to practise writing code and building software through years of experience. Direct one-on-one mentorship is extremely valuable when developing skills, and this is often provided through software engineering jobs at large tech companies.

Top firms (e.g. Microsoft, Google, Amazon) are particularly good at providing training to develop particular skill sets, such as management and information security. After talking with people who have experience in training at both tech giants and elsewhere, we think that this internal training is likely the best way to develop knowledge in software engineering (other than on-the-job practice), and will be better than training provided outside of these big tech companies.

However, it’s important to ensure that your role provides you with a variety of experiences: five years of software development experience is not the same as having the same year of experience five times over.

For example, it can be harder to gain full-stack or transferable front-end development experience at a large company. Many large mature products have a large front-end team making many small tweaks and analysing their performance in experiments. This provides good training in experiment design and analysis, but often isn’t very transferable to the sorts of front-end work you’d do at smaller companies or nonprofits, where you’ll often be working in a much smaller team with a focus on developing the experience as a whole rather than running experiments on small changes.

It generally takes around two years for new starters at big tech companies to have the experience they need to independently work on software, and another two years to reach a position where they are able to give advice and support to others in the company and manage projects.

Key career stages at large tech companies

First you’ll need some basic experience. You can get this from a relevant degree; working on a job at a smaller, less prestigious company; or from a bootcamp (see how to enter below for more).

New graduates, and other people with a couple of years of relevant experience, will start out as junior engineers. As a junior engineer, you’d complete small, clearly specified tasks and gain a preliminary understanding of the software development lifecycle. You’ll generally be given lots of guidance and support from more experienced engineers. You usually stay in this role for around three years, gradually expanding your scope. In the US, you’d be paid an entry-level compensation of $100,000 to $200,000 (as of early 2022).

Once you’ve successfully demonstrated that you can work on projects without needing much support, you’ll be given more responsibility. For a couple of years, you’ll work on more complex projects (often in one or two languages in which you’ve specialised), and with less support from others.

After five to eight years², you’ll generally progress to a senior engineer position. As a senior engineer, you write complex applications and have a deep understanding of the entire software lifecycle. You may lead small teams or projects, and you’ll be expected to provide mentorship and guidance to junior engineers. You can stay in this role for much of your career, though it becomes harder to compete with younger talent as you get older. Compensation in 2022 at this level is around $300,000 to $400,000 in the US.

At this point you may have the skills to leave and become a technical founder or CTO of a startup. This is a highly variable option (since most startups fail), but could be one of the highest expected value ways to earn to give given a chance of wild success.

Progressing past senior engineers, you’re typically responsible for defining as well as doing your job. You may go into management positions, or could become a staff engineer. Staff engineers, while still building software, also set technical direction, provide mentorship, input an engineering perspective to organisational decisions, and do exploratory work. At this level, at top firms in the US, you can earn upwards of $500,000 and sometimes more than $1,000,000 a year.

Software engineering is unusual in that you can have a senior position without having to do management, and many see this as a unique benefit of the career. (To learn more about post-senior roles, we recommend The Staff Engineer’s Path by Tanya Reilly and the StaffEng website.)

Working for a startup as a software engineer

Working for a startup can give you a much broader range of experience, including problem-solving, project management, and other ‘soft’ skills — because unlike in large companies, there is no one else at the organisation to do these things for you. You can gain a strong understanding of the entire development process as well as general software engineering principles.

Startups often have a culture that encourages creative thinking and resourcefulness. This can be particularly good experience for working in small software-focused nonprofits later in your career.

However, the experience of working in small organisations varies wildly. You’ll be less likely to have many very senior experienced engineers around to give you the feedback you need to improve. At very small startups, the technical cofounder may be the only experienced engineer, and they are unlikely to provide the level of mentorship provided at big tech companies (in part because there’s so much else they will need to be doing). That said, we’ve spoken to some people who have had great mentorship at small startups.

You also gain responsibility much faster at a fast-growing startup, as there is a desperate need for employees to take on new projects and gain the skills required. This can make startups a very fertile learning ground, if you can teach yourself what you need to know.

Pay at startups is very variable, as you will likely be paid (in large part) in equity, and so your earnings will be heavily tied to the success of the organisation. However, the expected value of your earnings may be comparable to, and in some cases higher than, earnings at large companies.

Many startups exit by selling to large tech companies. If this happens, you may end up working for a large company anyway.

Take a look at our list of places to find startup roles.

Moving to a direct impact software engineering role

Working in AI safety

If you are looking to work in an engineering role in an AI safety or other research organisation, you will probably want to focus on back-end software development (although there are also front-end roles, particularly those focusing on gathering data from humans on which models can be trained and tested). There are recurring opportunities for software engineers with a range of technical skills (to see examples, take a look at our job board).

If you have the opportunity to choose areas in which you could gain expertise, the experienced engineers we spoke to suggested focusing on:

• Distributed systems
• Numerical systems
• Security

In general, it helps to have expertise in any specific, hard-to-find skill sets.

This work uses a range of programming languages, including Python, Rust, C++ and JavaScript. Functional languages such as Haskell are also common.

We’ve previously written about how to move into a machine learning career for AI safety. We now think it is easier than we previously thought to move into an AI-safety-related software engineering role without explicit machine learning experience.

The Effective Altruism Long-Term Future Fund and the Survival and Flourishing Fund may provide funding for promising individuals to learn skills relevant to helping future generations, including new technologies such as machine learning. If you already have software engineering experience, but would benefit from explicit machine learning or AI safety experience, this could be a good option for you.

If you think you could, with a few weeks’ work, write a new feature or fix a bug in a major machine learning library, then you could probably apply directly for engineering roles at top AI safety labs (such as Redwood Research, DeepMind, OpenAI, and Anthropic), without needing to spend more time building experience in software engineering. These top labs offer pay that is comparable to pay at large tech firms. (Read more about whether you should take a job at a top AI lab.)

If you are considering joining an AI safety lab in the near future, our team may be able to help.

Working on reducing global catastrophic biological risks

Reducing global catastrophic biological risks — for example, research into screening for novel pathogens to prevent future pandemics — is likely to be one of the most important ways to help solve the world’s most pressing problems.

Through organisations like Telis Bioscience and SecureDNA (and other projects that might be founded in the future), there are significant opportunities for software engineers to contribute to reducing these risks.

Anyone with a good understanding of how to build software can be useful in these small organisations, even if they don’t have much experience. However, if you want to work in this space, you’ll need to be comfortable getting your hands dirty and doing whatever needs to be done, even when the work isn’t the most intellectually challenging. For this reason, it could be particularly useful to have experience working in a software-based startup.

Much of the work in biosecurity is related to handling and processing large amounts of data, so knowledge of how to work with distributed systems is in demand. Expertise in adjacent fields such as data science could also be helpful.

There is also a big focus on security, particularly at organisations like SecureDNA.

Most code in biosecurity is written in Python.

If you’re interested in working on biosecurity and pandemic preparedness as a software engineer, you can find open positions on our job board.

Other important direct work

Nonprofit organisations and altruistic-minded startups often have very few team members. And no matter what an organisation does, they almost always have some need for engineers (for example, 80,000 Hours is not a software organisation, but we employ two developers). So if you find an organisation you think is doing something really useful, working as a software engineer for them might be an excellent way to support that work.

Engineering for a small organisation likely means doing work across the development process, since there are few other engineers.

Often these organisations are focused on front-end development, with jobs ranging from application development and web development to data science and project management roles. There are often also opportunities for full-stack developers with a broad range of experience.

Founding an organisation yourself is more challenging, but can be even more impactful. And if you’ve worked in a small organisation or a startup before, you might have the broad skills and entrepreneurialism that’s required to succeed. See our profile on founding new high-impact projects for more.

Reasons not to go into software engineering

We think that most people with good general intelligence will be able to do well at software engineering. And because it’s very easy to test out (see the section on how to predict your fit in advance), you’ll be able to tell early on whether you’re likely to be a good fit.

However, there are lots of other paths that seem like particularly promising ways to help solve the world’s most pressing problems, and it’s worth looking into them. If you find programming difficult, or unenjoyable, your personal fit for other career paths may be higher. And even if you enjoy it and you’re good at it, we think that will be true for lots of people, so that’s not a good reason to think you won’t be even better at something else!

As a result, it’s important to test your fit for a variety of options. Try taking a look at our other career reviews to find out more.

How much do software engineers earn?

It’s difficult to make claims about software engineer earnings in general.

For a start, almost all of the official (especially government) data on this is on salaries rather than total compensation. By the time you’re a senior engineer, less than half of what you earn will be from your salary — the rest will be from bonuses, stock, and other benefits.

Most government data also reports median salaries, but as we saw when looking at progression in big tech firms, very senior software engineers can earn seven-figure compensations. So we should expect the distribution of total compensation to be positively skewed, or possibly even bimodal.

As a result, you should think of the figures below as representing salaries for early- to mid- career software developers.

Even given all these caveats, the figures we present here are instructive for understanding the relative salary levels (e.g. between locations), even if the absolute values given aren’t perfect.

More data is available at Levels.fyi, which collects data from people self-reporting their total compensation, and also has data on the distribution of what people earn, rather than just averages.

Software engineering salaries in the US

Here are the median US salaries for software developers, from the US Bureau of Labor Statistics:

Median US salaries for software engineers in 2020 (excluding bonuses)³

Here are the median salaries at different levels of progression, both in the US as a whole and in Mountain View and Palo Alto (i.e. Silicon Valley).⁴ In general, salaries rise quite rapidly in the early stages of the career, but then level off and grow by only a few percent per year after around a decade. However, this is probably offset by increases in other forms of compensation.

Median US salaries for software engineers in 2020 at different levels of progression

For figures on total compensation, especially at top companies, we can again look at Levels.fyi. These figures are far higher. Entry-level compensation is around $150,000, rising to $300,000 to $400,000 for senior engineers, and above $500,000 for late-career engineers. The top compensation levels reported are over $1,000,000.

Salaries also vary by location within the US; they are generally significantly higher in California (although web developers are best paid in Seattle).

Mean salary by US region in 2020⁵

These data are supported by Levels.fyi data on various locations in the US (e.g. Atlanta, New York City, Seattle, and the Bay Area).

Notably, the differences between locations in salaries at the 90th percentile is much higher than the differences in median salaries.

Compensation by US region in 2020⁶

It’s worth noting, however, that the cost of living in Silicon Valley is higher than in other parts of the US (Silicon Valley’s cost of living is 1.5 times the US national average⁷), reducing disposable income. (In general, data on average cost of living is particularly representative of the costs you’d expect to pay if you have a family or want to own a house.)

If you want to estimate your own disposable income given different scenarios, you can try these tools:

• Estimate your post-tax income
• Find out the cost of living in different cities
• Calculate your donatable income

Software engineering pay in other countries

Software engineers are paid significantly less outside the US. The UK Office for National Statistics found that the mean salary for “programmers and software development professionals” in 2020 was £46,000 (US$59,000 in 2020).⁸ Even when looking at full compensation, we see similar trends across the world.

Software engineer compensation outside the US⁶

The only countries with earnings as high as the US are Israel and Switzerland, and no countries have earnings as high as Seattle or the San Francisco Bay Area. The cost of living in major cities in Israel and Switzerland is around 20% higher than in Silicon Valley.⁹

Compensation across the world is often higher if you work from a major city.

Software engineer compensation in major cities outside the US⁶

It can be difficult to get a visa to work in the US. For example, US immigration law mandates that a maximum of 65,000 H-1B visas (one of the most common types for software engineers) are issued a year. Also, because of the cost of flying you out for an interview, there will often be a higher bar for international applicants passing phone interviews.

There are some things that can make it easier to get a visa:

• Having a degree in computer science or other field related to your job
• Applying to companies with enough capital and flexibility to bear the time and financial costs of the visa process
• Having a specific unusual skill set that may be hard to find in the US

Take a look at this blog to find out more.

Despite all of this, remote work in software development is becoming far more common. There’s a growing trend for a few companies to hire globally for remote roles, and pay US-market compensation. If you manage to get one of those roles, you can earn a lot from anywhere.

Software engineering job outlook

The future demand for software engineers is promising. The US Bureau of Labor Statistics projects 22% growth in US employment of software engineers from 2020–30, which is much higher than the growth rate for all occupations (8%). The main reason given for this growth is a large projected increase in the demand for software for mobile technology, the healthcare industry, and computer security.

The number of web development jobs is projected to grow by 13% from 2020–2030. The main reasons for this are the expected growth of e-commerce and an increase in mobile devices that access the web.

What does this mean for future salaries? Strong growth in demand provides the potential for salary growth, but it also depends on how easily the supply of engineers can keep up with demand.

Software engineering job satisfaction

The same high demand for software engineers that leads to high pay also leads to high bargaining power. As a result, job satisfaction among software engineers is high.

Many software engineers we have spoken to say the work is engaging, often citing the puzzles and problems involved with programming, and being able to enter a state of flow (which is one of the biggest predictors of job satisfaction). On the other hand, working with large existing codebases and fixing bugs are often less pleasant. Read our five interviews with software engineers for more details.

Work-life balance in software engineering is generally better than in jobs with higher or comparable pay. According to one survey, software engineers work 8.6 hours per day (though hours are likely to be longer in higher-paid roles and at startups).

Tech companies are progressive, often having flexible hours, convenient perks, remote working, and a results-driven culture. The best companies are widely regarded as among the best places to work in the world.

Examples of people pursuing this path

How to predict your fit in advance

The best way to gauge your fit is to try it out. You don’t need a computer science degree to do this. We recommend that you:

1. Try out writing code — as a complete beginner, you can write a Python program in less than 20 minutes that reminds you to take a break every two hours. Once you know the fundamentals, try taking an intro to computer science and programming class, or work through free resources. If you’re in college, you could try taking CS 101 (or an equivalent course outside the US).
2. Do a project with other people — this lets you test out writing programs in a team and working with larger codebases. It’s easy to come up with programming projects to do with friends — you can see some examples here. Contributing to open-source projects in particular lets you work with very large existing codebases.
3. Take an internship or do a coding bootcamp.

It seems likely that a few software engineers could be significantly better than average. These very best software engineers are often people who spend huge amounts of time practising. This means that if you enjoy coding enough to want to do it both as a job and in your spare time, you are likely to be a good fit.

How to enter this field

While a degree in computer science or a quantitative subject is often helpful, many entry-level jobs don’t require one, meaning that software engineering is open to people with backgrounds in humanities and social sciences.

To enter, you need some basic programming skills and to be able to demonstrate a strong interest in software engineering. We’ve seen many people with humanities and social science degrees get junior software engineer jobs with high salaries, just through learning on their own or through coding bootcamps.

Learning to program

Basic computer programming skills can be extremely useful whatever you end up doing. You’ll find ways to automate tasks or analyse data throughout your career. This means that spending a little time learning to code is a very robustly useful option.

• Learning on your own. There are many great introductory computer science and programming courses online, including: Udacity’s Intro to Computer Science, MIT’s Introduction to Computer Science and Programming, and Stanford’s Programming Methodology. Don’t be discouraged if your code doesn’t work the first time — that’s what normally happens when people code!
• Attending a coding bootcamp. We’ve advised many people who managed to get junior software engineer jobs in less than a year through going to a bootcamp. Coding bootcamps are focused on taking people with little knowledge of programming to as highly paid a job as possible within a couple of months. This is a great entry route if you don’t already have much background, though some claim the long-term prospects are not as good because you lack a deep understanding of computer science. Course Report is a great guide to choosing a bootcamp. Be careful to avoid low-quality bootcamps. To find out more, read our interview with an App Academy instructor.
• Studying computer science at university (or another subject involving lots of programming). If you’re in university, this is a great option because it allows you to learn programming while the opportunity cost of your time is lower. It will also give you a better theoretical understanding of computing than a bootcamp will (which can be useful for getting the most highly paid and intellectually interesting jobs), a good network, some prestige, and a better understanding of lower-level languages like C. Having a CS degree also makes it easier to get a US work visa if you’re not from the US.
• Doing internships. If you can find internships, ideally at your target employers (whether big tech companies or nonprofits), you’ll gain practical experience and the key skills you otherwise wouldn’t pick up from academic degrees (e.g. using version control systems and powerful text editors). Take a look at our list of software engineering (and machine learning) internships at top companies.

Getting your first job in software engineering

Larger companies will broadly advertise entry-level roles. For smaller companies, you may have to reach out directly and through your network. You can find startup positions on job boards such as AngelList, and many top venture capital firms have job boards for their portfolio companies.

Large software firms can have long and in-depth interview processes. You will be asked about general software knowledge, and later rounds of interviews are likely to give you problems around coding and algorithms, during which you will be asked to collaborate with the interviewer to solve the problem.

It’s worth practising software engineering interview questions in advance; often this means apply for companies you are less likely to want to work at first, and use these applications to get used to the process. This can be a stressful process (in part because you might face some early rejections, in part because it’s tricky to navigate applying if you don’t really want the job that much), so it’s important to take care of your mental health throughout the process.

It will also probably help to study the most popular interview guide, Cracking the Coding Interview. You can also practise by doing TopCoder problems.

We think that this guide to getting a software engineering job is particularly helpful. There are six rough steps:

1. Send a company your resume. Make it as specific as possible to the job you’re applying for, and proofread it carefully. If you can get a referral from a friend, that will significantly increase your chances of success.
2. Speak to a recruiter. Read up about the company in advance, and make sure you have questions. Be nice — it’s going to help if the recruiter is on your side.
3. Have a technical phone interview. You’ll solve some problems together. Make sure you ask questions to clarify the problem, and strategise about the best possible approach before you start writing code. Finish by checking for bugs and make sure you’re handling errors correctly. When you’re done, ask the interviewer some questions!
4. Have a three- to six-hour on-site interview. It’s key to talk out loud as you work through a problem. And again, ask your interviewer some questions about them and the company.
5. Get an offer from the recruiter. You should make sure they think you are seriously considering the company or you may not get an offer. If you don’t get an offer, ask for feedback (though it’s not always possible for companies to give detailed feedback). If you need more time to think (or to apply elsewhere), tell them in advance, and they may choose to wait to give you details when you’re more ready to go through with an offer.
6. Accept the offer!

Want one-on-one advice on pursuing this path?

If you think software engineering might be a great option for you, but you need help deciding or thinking about what to do next, our team might be able to help.

We can help you compare options, make connections, and possibly even help you find jobs or funding opportunities.

APPLY TO SPEAK WITH OUR TEAM

Learn more

Top recommendations

• The 80,000 Hours Podcast on Artificial Intelligence (a collection of 10 key AI episodes from our podcast)
• Our review of careers in information security
• Our review of being an early employee at a startup

Further recommendations

Find a job in this path

If you think you might be a good fit for this path and you’re ready to start looking for jobs, see our curated list of opportunities:

View all opportunities

Read next:  Learn about other high-impact careers

Want to consider more paths? See our list of the highest-impact career paths according to our research.

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Moore later revised his estimate to every two years, but the doubling trend held, eventually becoming known as Moore’s Law.

This technological progress in computer hardware led to consistent doublings of performance, memory capacity, and energy efficiency. This was achieved only through astonishing increases in the complexity of design and production. While Moore was looking at chips with fewer than a hundred transistors, modern chips have transistor counts in the tens of billions and can only be fabricated by some of the most complex machinery humans have invented.²

Besides personal computers and mobile phones, these enormous gains in computational resources — “compute” — have also been key to today’s rapid advances in artificial intelligence. Training a frontier model like OpenAI’s GPT-4 requires thousands of specialised AI chips with tens of billions of transistors, which can cost tens of thousands of dollars each.³

As we have outlined in our AI risk problem profile, we think dangers from advanced AI are among the most pressing problems in the world. As they progress this century, AI systems — created with and running on AI hardware — may develop advanced capabilities and features that carry profound risks for humanity’s future.

Navigating those risks will require crucial work in forecasting AI progress, researching and implementing governance mechanisms, and assisting policy makers, among other things. Expertise in AI hardware can be of use in all these activities.

We are very enthusiastic about altruistically motivated people who already have AI hardware expertise moving into the AI governance and policy space in the short term. And we’re also enthusiastic about people with the background skills and strong personal fit to succeed in this field gaining AI hardware expertise and experience that could be useful later on.

Using AI hardware expertise to reduce catastrophic risks is a relatively new field, and there is a lot of work needed right now to develop it.

It’s hard to predict how the field will evolve, but we’d guess that there will continue to be useful ways to contribute for years to come. At some point, there may be less need for conceiving governance regimes and more work needed working out implementation details of specific policies. So we’re also pretty comfortable recommending people start now on gaining hardware-related skills and experience that could be useful later on. Hardware skills and experience are highly valuable in general, so this path is likely to have good exit options anyway.

You can also read our career review of AI governance and coordination, which discusses how valuable this kind of expertise can be for policy.

Why might becoming an expert in AI hardware be high impact?

The basic argument for why being an expert in AI hardware could be impactful is:

1. Increasingly advanced AI seems likely to be very consequential this century and may carry existential risks.
2. There are various ways that expertise in AI hardware can help with (a) forecasting AI progress and (b) ensuring AI is developed responsibly.

The main reason why expertise in AI hardware can help reduce risk is that, alongside data and ideas, compute is a key input into overall AI progress.⁴

Researchers have identified scaling laws showing that, as you train AI systems using more compute and data, those systems predictably improve on many performance metrics. As a result, you now need thousands of expensive AI chips running for months to train a frontier AI model, amounting to tens of millions of dollars in compute costs alone.⁵

Credit: Epoch AI (2023)

AI chips are specialised to perform the specific calculations needed for training and running AI models. In practice, you cannot train frontier models with general-purpose chips — you need specialised chips.⁶ And to keep up, you need cutting-edge chips.⁷ AI labs that are stuck with older generations of chips pay more money and spend more time training models.

It’s possible that compute will become less important of an input into AI progress in the future or that much AI training will be done using hardware other than AI chips.⁸ But it seems very likely that access to cost-effective compute remains vitally important for at least the next five years, and probably beyond that.⁹

Some ways hardware experts could help positively shape the development of AI include:

• Providing strategic clarity on AI capabilities and progress, in particular the current and future pace and drivers of those things, in order to inform research and decisions relevant to AI governance
  • More accurately forecasting progress in the capabilities of AI systems, for example by estimating the doubling time of AI chip cost-effectiveness
  • Better understanding how AI chips are used and produced, for example by mapping out the global semiconductor supply chain
• Researching hardware-related governance mechanisms and policies, which seem promising since AI hardware is necessary, quantifiable, physical, and has a concentrated (though global) supply chain.¹⁰ (This field is sometimes called “compute governance.”)
  • Designing monitoring regimes to make compute usage more transparent, for example by researching a compute monitoring scheme for large AI models
  • Determining the feasibility and usefulness of hardware-enabled mechanisms as a tool for AI governance
  • Researching ways to limit access to compute to responsible and regulable actors
  • Developing prototypes of novel hardware security features
  • Understanding how compute governance fits into the broader geopolitical landscape
• Working in government and policy roles on all the above
  • This may be some of the most important work to be done with these skills, but there’s less clarity as of this writing about what these roles will look like.
• Doing impactful and safety-oriented work — including liaising with policymakers — from within industry
• Advising policymakers and answering researchers’ questions as an expert, while working on something else, e.g. in industry
• Though this is more speculative, you might work for third-party auditing organisations as part of a future compute governance programme.

There are currently few AI hardware experts working on these areas who are motivated by reducing existential risk that we know of. As of mid-2023, there seem to be about 3–12 existential-risk-focused full-time equivalents (FTEs) forecasting AI progress with a focus on hardware, and about 10–20 such FTEs working on other projects related to compute governance.¹¹

It’s hard to estimate how many additional AI hardware experts are needed, and the answer could change rapidly — we recommend that you do some of your own research on this and talk with people in the field.

There are ways in which this work could end up being net negative. For example, restricting certain actors’ access to compute could increase geopolitical tensions or lead to a concentration of power. Or work on AI hardware could lead to cheaper or more effective chips, accelerating AI progress. Or governance tools like compute monitoring regimes could be exploited by bad actors.

Some compute governance proposals involve monitoring how AI chips are used by companies, which can raise privacy concerns. Finding ways to implement governance while still protecting personal privacy could be valuable work.

If you do take this path, we encourage you to think carefully through the implications of your plans, ideally in collaboration with strategy and policy experts also focused on creating safe and beneficial AI. (See our article about accidental harm and tips on how to avoid it.)

Another potential downside of gaining expertise in AI hardware to reduce catastrophic risks is that roles in industry, where your impact could be ambiguous or even negative, may end up being more appealing in some ways than higher-impact but lower-paid roles in policy or research.

If you believe it might be difficult for you to switch out of high-paying industry positions and move to roles with much more potential to help others and reduce AI risk, you should carefully consider how to mitigate these challenges. You might aim to save more than usual while earning a high salary in case you later end up making less money; you could donate any earnings above a certain threshold; and you can make sure you’re a part of a community that helps you live up to your values.

What does working in high-impact AI hardware expert roles actually look like?

Compute-focused AI governance is an exciting, burgeoning field with lots of activity and many open questions to tackle. There are also relevant policy windows open or likely opening soon as public awareness of risks from AI has increased.

The most common kind of role for AI hardware experts is research, though other potentially impactful roles include working as a policymaker or staffer, as a policy analyst,¹² or communicating research to policymakers or the public.

Researcher roles are likely to involve things like:

• Investigating hardware-related governance mechanisms or forecasting AI progress, and communicating results from those investigations to decision makers or other researchers
• Interviewing experts on specific topics related to this
• Writing policy briefs
• Advising researchers working on AI governance
• Managing or mentoring others who work on this

Careers in government, especially in the US, may be highly impactful, too. However, it’s not clear yet if the state of policy development on AI has advanced to the point that the government will be aiming to hire AI hardware experts directly. It may at some point become clear to policymakers that AI hardware knowledge is extremely valuable for implementing AI policy, at which point these experts will be in high demand. We have a separate article about opportunities for getting involved in US AI policy.

Some people working in this field today do so for Washington, DC-based think tanks such as:

• Center for a New American Security (CNAS)
• Center for Security and Emerging Technology (CSET)
• Center for Strategic and International Studies (CSIS)
• RAND (in particular the Technology and Security Policy Fellows)

You can also consider research organisations with relatively less of a policy focus, such as:

• Centre for the Governance of AI (GovAI)
• Epoch AI
• Institute for AI Policy and Strategy¹³

Careers in industry (including working for chip designers like Nvidia, semiconductor firms, or cloud providers) and academia could be valuable too, though mainly for developing career capital in the form of skills, connections, and credentials, and such work could unintentionally speed up AI progress.

Knowledge in AI hardware could also be used to do grantmaking, field-building, and research or policy work on AI governance topics that aren’t centrally about AI hardware. However, for these paths, the returns to greater AI hardware expertise will likely diminish more steeply.

How to enter AI hardware expert careers

Though it’s possible to pick up some amount of hardware knowledge while working as, say, an AI governance researcher focused on other topics, the kind of expertise that’s most needed is the sort you only get after some years of studying or working with hardware.

• If you already have expertise in AI hardware, you can consider applying to research or policy fellowships or for entry-level roles like research assistant. In some cases, it’s possible to transition from a career in hardware or semiconductors directly into a more senior research or policy role, especially if you have some prior experience with AI governance.
  • Though it’s not a career, you can also usefully offer to advise people who are already working on governance and policy questions dealing with AI hardware.
  • Some of the highest-impact jobs may be at major AI labs like OpenAI, DeepMind, and Anthropic.
  • See the US policy fellowship database for a list of policy fellowships.
  • We also have AI safety and policy fellowships on our job board.
• If you have a degree (or have otherwise gained skills) related to AI hardware, but have no professional experience, you can consider building career capital by taking roles in industry or maybe academia. You’re likely to get the most useful experience working on AI hardware directly for companies like Nvidia, but other chip and semiconductor companies seem promising too.
• If you don’t yet have experience or skills related to this, it’s unclear whether AI hardware is the best thing for you to focus on. Perhaps it is if you are especially excited about it or feel that you may be an especially good fit for it.
  • Studying computer engineering at the undergraduate level is typically required to work in industry. The coursework requires strong ability in science and maths. You may also want to obtain a master’s degree in the field.
  • The state of the art in this field is constantly evolving, so you should expect to continue learning after your formal education ends. Working at the most cutting-edge companies will likely give you the best understanding of technological developments.
  • An educational background in computer and AI hardware may be sufficient to offer you significant advantages when starting out a career in AI governance, particularly in Washington, DC. Though you’ll likely want to supplement this technical expertise with some policy-related career capital, such as a prestigious fellowship.

Specific types of knowledge and experience that seem promising include knowledge and experience in AI chip architectures and design, hardware security, cryptography, cybersecurity, semiconductor manufacturing and supply chains, cloud computing, machine learning, and distributed computing. It seems especially valuable to have people who also have knowledge useful for AI governance or policy-making more broadly, though this is not necessary.

Learn more

Top recommendations

• Podcast: Lennart Heim on the compute governance era and what has to come after
• Transformative AI and compute – reading list
• Podcast: Danny Hernandez on forecasting and the drivers of AI progress

Further recommendations

The post Expert in AI hardware appeared first on 80,000 Hours.

Benjamin Todd interviewed Michael Dello-Iacovo about his attempts to do good as a geophysicist inside the Australian mining industry.

What does the job involve?

I’m a geophysicist working for a resources company in Australia. The resources industry is broad, and includes exploration, mining and oil and gas production. Roles in the resources industry include geologists, environmental scientists, engineers (of almost all types), information technology, and a host of others. All of these potentially involve some intermittent field work. I’ll focus on geophysics and geology, as these are the roles I’m most familiar with. Note that this summary is focussed on private oil & gas and mining companies, not government or research organisations. While the roles may be similar in these organisations, the culture, salary and other perks are likely not.

As a resources geophysicist, my work ranges from data processing (which is actually more enjoyable and challenging than it sounds), interpreting and developing geological models and spending time in the field, where my role becomes more one of contractor management, environmental/safety auditing and data quality management. Being in a technical role, I don’t have a lot of meetings (perhaps 2-3 formal meetings per week), and a lot of time is spent behind a computer screen.

Why did you take this job?

I first decided to enter the resources industry part-way through my university science degree because I had a long-time love of rocks and minerals, I liked physics, I wanted a career that paid well, and I wanted to do something about climate change. Many of my friends were going down the path of activism, which I do to some extent, but I decided I’d like to try changing the industry from within by getting to a position of influence and either transitioning a company from fossil fuels to renewable energy, or simply improving their environmental practices. A good example of that recently is AGL’s newly appointed CEO Andrew Vesey. AGL is an energy provider in Australia, mostly through coal plants. Under Andrew’s new leadership, the company has now announced that they will shut down all of their coal plants over the next 35 years – no small undertaking!

I also wanted to try and influence the giving culture in the workplace. I decided that if I didn’t work in the industry, someone else who probably cared less about the environment and giving would get the job instead, as the industry is not talent constrained. I think that a lot of people with this kind of mindset are turned away from the industry, which provides a negative feedback loop. Whilst there is a very small chance that one would make such a big impact, I believe it is high enough that, along with the incremental changes, it is worth considering.

Almost one year into my role, I have to say that I have had less impact than expected on the the giving and environmental culture of the company. Even in the field, it was hard to get approval to change practices. I’ve realised that you do not normally have the kind of influence required to make such changes until you reach a more senior position.

What are the main pros of this job for someone looking to make a difference?

The main pros are the income, career capital and potential for networking. There is the potential for a lot of field work in this industry, which can be good or bad depending on how much you enjoy working remotely in the field.

An entry level employee in geoscience or engineering in this field with a 4 year undergraduate degree can expect to be making over $80,000 AUD p.a. (before bonus, or $100,000 for a field based role), which quickly increases to around $100,000 over the first few years. For some field-based roles, it isn’t unusual for the starting salary to be in excess of $120,000 during resources booms, but this isn’t sustainable.

Somewhat surprising is the difference in culture and benefits between employers. Some companies, typically smaller ones, have a less rigorous focus on safety, which can make employees uncomfortable. Many companies offer dollar matching for donations made to sponsored, or all, charities. For my employer, this is capped at a maximum of only around $300, but at BHP, one of the largest mining companies in the world, donations of up to $100,000 will be doubly matched (so $100,000 = $300,000 to charity). This greatly boosts the potential to earn to give at BHP.

The skills gained in the industry range from data analysis (highly applicable across a range of careers), computing systems usage (e.g. I’ve learned how to use Linux and a range of software as part of my role), research (literature reviews can be common depending on the role) and soft skills such as project/contractor management (some roles more than others) and teamwork. If you are proactive you will have the opportunity to work with some high profile people in the industry, which can end up being valuable mentors and contacts. I’m using my skills gained from geophysics in this job to start a PhD in asteroid geophysics in 2016, which I plan to do part-time along with my job. This has been one of the biggest personal development benefits for me from working in this field.

Just as an aside regarding the PhD, I have chosen the somewhat unusual path of doing a full-time job at the same time. As a result, I’m either at work, doing my PhD or working on a side project almost all day, every day, which certainly isn’t for everyone, but I’ve had to chance to develop and gain experience and skills much faster than usual.

What are the main cons of this job?

The main cons are the potential for stress and to work in an environment with a very low cultural fit for someone seeking to maximise their impact.

Some of my colleagues in less technical roles experience high amounts of stress when meeting deadlines, making decisions and being responsible for developing assets and projects worth millions of dollars. It is a valuable experience but burnout is a concern.

It is also quite likely that someone seeking to maximise impact or with an effective altruism mindset will have a relatively low degree of cultural fit in the industry. This isn’t to say that the average person in the industry doesn’t care about doing the right thing, or that all people act in a certain way, but the average sentiment can be difficult to deal with.

For instance, I’m a vegan for a variety of ethical reasons. I’m reasonably certain that I’m the only vegan in my company of almost 6,000 employees, and vegans are extremely rare in the industry. As a result, I get a lot of casual harassment about this choice. This ranges from joking that they will make sure there’s a salad for me at the Christmas barbecue lunch to calling vegans ‘stupid hippies’ when they forget I’m in the conversation, or don’t realise I’m a vegan. Often they don’t realise that what they say could be perceived as harmful, or they laugh and expect you to laugh along with their joke.

Another example is ridiculing people for caring too much about climate change or the environment, which encourages one to tone down this attitude to fit in. I try to live modestly in order to donate more, but this too is hard when colleagues want to regularly go to restaurants for lunch or talk about other luxury spendings. Changing my own personality as a result of the job is a risk, but I believe I’m committed enough to my cause that this won’t happen.

Working in the field

Not all roles in the industry involve fieldwork or working in remote locations, but many do, and if you decide to enter the industry you should be prepared to move around the world a lot and work in the field. Typically, geoscience university degrees will involve several multi-day field trips, often involving camping out with limited amenities. This is a true make-or-break moment for most people doing the degree; they either decide they love field work and continue, or they hate it and drop out/transfer. If you have enjoyed camping, hiking or nature in the past, that may indicate a good fit for field work. You should also be prepared to possibly have to work underground. You should have a big focus on safety but also not be claustrophobic.

The type and length of fieldwork varies widely. The work can range from camping in tents with no facilities to sleeping in caravans (or ‘dongers’) or even high-tech living camps. Most camps have limited internet access these days, but in regional Australia few have phone reception (this may be different in more populated parts of the world). Rotations range from ‘8 days on 6 days off’ to ‘6 weeks on 6 weeks off’ or more and everywhere in between. Long rotations may be difficult to manage with family, friends and other roles. Having said that, during my time in the field I had at least several hours free each day to work on my PhD in geophysics or other roles.

Some negative aspects of the culture are more pronounced in the field, with people being even less tolerant of vegans and environmental activism. As the only vegan in a camp of 80 people, the food provided was at best great, but at worst steamed vegetables and rice for several days in a row.

How to enter the field

Employers in the resources industry selectively hire graduates who have undertaken some kind of vacation work or internship in the resources or a related industry. This is highly recommended and it is never too early in your degree to start applying for vacation work, which almost always pays well. Going to conferences, joining professional bodies (both cheap or free for students) and being a member of geoscience/engineering clubs are also highly recommended. Apply for as many scholarships as you can, as these are viewed favourably and are surprisingly easy to get as many people simply don’t apply.

Outline of a potential career path

People in the industry tend to take one of two progression paths. They either focus on technical skills and end up being a senior technical staff or the leader of a technical team, or they develop commercial, project management and other skills. From here they might move into a finance role, or potentially move up the corporate ladder towards CEO. One might expect to make Senior Geophysicist after 10-15 years in the industry, or even as little as 5 years if they are particularly dedicated and talented, and will make an average salary of $147,000 AUD according to Payscale. A typical team leader salary is between $150,000 and $180,000. Again, if you’re particularly good, you might make team leader within 5 years. Managers make from $250,000 to $300,000, General Managers make between $300,000 and $550,000.

The income of a CEO, Vice Presidents and other executive officers is highly dependent on the size of the company, the company performance and how the industry is doing in general. A CEO at a large resources company might make over $4,000,000 p.a., but necessarily very few people reach this point. The resources industry fluctuates greatly, meaning that company performance and therefore job prospects vary greatly. Job security ranges from very high to very low, depending on the resources boom/bust cycle. CEOs of major resources companies are generally at least 45 years old, and it is unlikely you will be one before then even if you are highly talented and experienced, as there is a bias towards older leaders.

What have you considered switching to?

As I’ve said earlier, I’m doing a PhD in asteroid geophysics. I am particularly interested in [asteroid mining], and have considered working for an asteroid mining company or starting my own. I am also interested in asteroid impact mitigation, which I believe is a relatively neglected field despite the potential dramatic consequences, and I have the freedom to focus on this in my research. Another field I’ve considered switching to is economics, likely due to my exposure to petroleum economics. If I were to turn back the clock, I would likely do a double degree with science and computer science, as coding is highly relevant to geophysical work, especially cutting edge research, and good programmers appear to be in very high demand in general.

A lot of people in the industry switch to a more commercial role, and some end up being geophysical software developers who produce and sell software to resources companies. Some people I know who have done this have ended up making tens of millions of dollars, and some have done significantly less well. It’s hard to say what the success rate is.

Michael’s verdict

Overall, I would recommend that people pursue a career in the resources industry only if they are certain they are well suited to field work, can operate in a culture that is potentially challenging to someone focused on social impact, have reason to believe that they would be good at the work and have the chance at being influential in the industry, either through existing networks and contacts or expected future ones. The average salary is high, but employment prospects are potentially volatile, and I suspect that, globally speaking, the expected earnings would be higher for someone equally talented in a field such as computer science, so I wouldn’t work in resources just to earn to give.

After answering these questions, I realised how unsatisfied I am with the culture in my industry. However, my main arguments for remaining in the industry at this time are expected future impacts through my contacts, a high salary to earn to give, and gaining relevant expertise to another, similar line of work through space science research. My current plan is to continue working, finish my PhD and build my coding skills on the side to leave open the possibility of moving into computer science.

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