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FAQs

Isn’t AI overhyped?

There is a lot of exaggerated hype about AI out there, and it’s good to be skeptical of people making extreme claims about a new technology — they often turn out to be misleading or even scams.

But the progress we’ve seen in AI over the last few years is undoubtedly real, even if some people claim AI can do things it can’t yet. The technology is moving fast, and the AI capabilities now on display every day would astound people working in the field five years ago. We’ve documented some of the impressive progress here and here, and explored whether it might continue here.

It’s important to keep in mind at least three key points about AI progress:

1. AI has made incredible progress.
2. Current AI systems still have many flaws and limitations.
3. Future AI systems will likely be much, much better.

We think sometimes people focus too much on either (1) or (2) without acknowledging the other. And not nearly enough people are focused on (3) — and what it might mean for civilisation.

Could the risks truly be existential?

Unfortunately, we think so.

Over the past 10 years we’ve investigated many candidate existential risks — meaning disasters that could result in outcomes as bad as human extinction, or worse — because we think these risks are worth prioritising. Most candidate existential risks don’t make the cut. But because AI technology could become enormously powerful and agentic, it’s like creating a new, smarter-than-us species and hoping it treats us well forever.

We’re not alone in being concerned. Top scientists, AI business leaders, and politicians have also warned that risks downstream of the creation of powerful AI could be existential. This view is still controversial, though. Some serious people who have examined the question of whether AI poses an existential risk have come away unconvinced. So we’re not completely certain.

But we don’t need certainty to act on existential risks. If there’s a meaningful chance that a technology could pose an existential risk, then it’s worth taking steps to mitigate that. We think in this case, the risks are high enough that they demand much more attention than they have received.

For (much) more on this question, see our article on the risk of an AI-related catastrophe.

What are the best objections to thinking AGI could come soon, or that it poses existential risks?

We think some of the best arguments that AGI won’t come soon are:

1. The path to AGI is not obvious: Today’s AI systems, while impressive, remain narrow specialists rather than general problem-solvers. They excel at specific tasks (chess, image recognition, coding, etc.) but lack the broad adaptability and understanding of a human mind. For example, even advanced language models often stumble on basic common-sense reasoning or logical consistency. Some AI scientists think we’re missing crucial insights and innovations that will be necessary to create truly general and broadly useful intelligent systems.
2. There are many potential bottlenecks on AI development that might choke off progress at a certain point. And it’s possible some will appear on the horizon that we haven’t foreseen.
3. Most of the world does not seem to be acting like we’re about to experience a radically transformative new technology in the coming years. It’s even highly controversial among people working on AI. To think so is going against the grain of the world as a whole, and might be due to placing too much credence in the predictions of a small group of AI experts.

We think the best arguments against the idea that AGI poses a significant existential risk are:

1. We don’t understand the nature of AI goals and motivations. It’s possible that it will be easy to steer by default, and be unlikely to develop powerseeking or dishonest tendencies, which would reduce several of the risks (though not all).
2. If development is slow and gradual, then it is much more likely to be safe. If advances in AI are incremental and closely monitored, safety research may be able to head off any issues.
3. In general, AI systems will be designed by humans, and humans have strong incentives to ensure that AI systems are safe and aligned to human purposes at each step in technological development.
4. Multiple powerful AI systems could be deployed by different actors and act as “checks and balances” on one another, reducing several of the risks we’re most worried about.
5. Many other concerns about new technology and catastrophic risks have been unfounded or exaggerated — or the problems have been solved relatively easily — so we should expect something similar to play out with AI.
6. Existentially risky is an extremely high bar — meaning we should start by assuming that issues created by the development of AGI will be more moderate — and only change our minds based on strong arguments or evidence.

We think there are good responses to each of these points in favour of thinking AGI could come soon and pose existential risks, but it’s not so obvious that reasonable people can’t disagree.

I want to meet other people working on AI risks and learn more about the topic. Where should I start?

Absorbing the information, podcasts, and newsletters on this page is a good place to start. We also have a reading list for other blog posts and research papers we recommend.

Those sources will link to other resources, and we’d encourage you to explore them for as long as they hold your interest.

Attending conferences, such as Effective Altruism Global or NeurIPS, can be a useful way to network with other people in the field. There are also meet-ups, courses, and other events to grow your network and skills.

Finally, our 1-1 advisors can introduce you to experts or potential future colleagues based on your specific situation.

I already have specialised skills. Where do I fit in?

If you’ve got specialised skills (or experience), there are many organisations that could be excited to hire you.

In fact, many organisations are bottlenecked on more experienced talent — people who can lead teams or bring years of experience in an area that’s particularly hard for generalists, like scientific disciplines or law.

You can filter our job board for different skills and seniority, as well as for organisations working on AI. The job board allows you to set up alerts for specific filters, so you can get an email if a role matching your needs is posted.

In general, we know employers working on AI risk are interested in people with the following skills:

• Policy and political skills (especially concerning AI but many other areas are relevant, e.g. China-US relations). These skills allow you to work in government, think tanks, or politics.
• ML engineering for technical safety research
• Information and cybersecurity, to safeguard powerful AI technology from cyberthreats and theft
• Organisation building, e.g. to do general ‘getting stuff done’ work
• Communications and community building
• Research in any area that might be relevant, including social sciences, international relations, history, and even philosophy, as well as AI itself
• Forecasting
• AI hardware expertise
• Entrepreneurship

Other skills might also be relevant, even if it’s not obvious at first how or they’re too niche for us to cover here.

Getting to know more people in the field might help you better figure out where you can contribute. So go to conferences, meet-ups, lectures, and other events with people who are also working on AI risks to expand your network.

It’s also possible you’ll need to learn new skills or get new experience. The good news is that you may be able to get up to speed relatively quickly, because AI risk is a young field. For ways to skill up, see our section above.

You can also apply to speak to one of our 1-1 advisors, who can help put you in touch with potential collaborators or employers.

I’m early in my career. How can I help?

If you’re at the start of your career, you might be able to get an entry-level position or fellowship right away. So it’s often worth doing a round of applications immediately, especially if you have technical skills.

You can try the following steps:

1. Spend 20-200 hours reading about AI, speaking to people in the field (and maybe doing short projects).
2. Apply to impactful organisations that might be able to use your help. Check out our job board for some opportunities.
3. Aim for the job with the best combination of (i) strong org mission, (ii) team quality, (iii) centrality to the ecosystem, (iv) influence of the role, and (v) personal fit.

However, in most cases, early career people will need to spend at least 1–3 years gaining relevant skills before they should focus on how to apply them.

The skills listed above seem most helpful for working on this issue. Focus on whichever you expect to most excel at. But if you are right at the start of your career, don’t forget general skills like project management and personal productivity. You might want to check out the chapter of our career guide on how to be successful.

Should I work at a frontier AI company?

If you want to help reduce catastrophic risks from AI, working at a frontier AI company is an important option to consider, but the impact is extremely varied. These roles often come with great potential for career growth, and by placing you right in the center of AI development, some could be (or lead to) highly impactful ways of reducing the chances of an AI-related catastrophe.

However, there’s also a risk of doing a lot of harm, and there are particular roles you should probably avoid.

For more on this question, check out our full article.

I can’t change jobs (or am not ready to yet). What else can I do to help?

If you don’t immediately want to change jobs or aren’t sure what you could do, you could ask people in the field what to do in order to best position yourself for the next 3–12 months, and then do that. Or see our advice for early career people above.

Keep in mind that few people have much expertise in transformative AI right now, so it’s often possible to pull off big career changes pretty fast with a little retraining.

Otherwise, we recommend that you educate yourself more about AI and follow along with ongoing developments. That will help you figure out how to best contribute from your current path, for example, by donating, promoting clear thinking about the issue, mobilising others, or preparing to switch when new opportunities become available (which could very well happen given the pace of change!).

Do you think everyone should drop everything right now to work on making things go well with AI?

No. There are reasons not to work on this issue:

1. You might not have the flexibility to make a large career change right now.
2. There are other important problems, and you might be far better suited for a job focused on another issue.
3. You might be too concerned about the (definitely huge) uncertainties about how best to help or be less convinced by the arguments that it’s pressing.

However, we think most people reading this should seriously consider it. The issue is very neglected, important, and urgent, and many people can contribute. So we think it will be many people’s best option.

More questions? Email us