IT Security, Data Privacy, and Systems Specialist

About 80,000 Hours

80,000 Hours’ goal is to get talented people working on the world’s most pressing problems. After more than 10 years of research into dozens of problem areas, we’re putting most of our focus on helping people work on positively shaping the trajectory of AI, because we think it presents the most serious and urgent challenge that the world is facing right now.

We’ve had over 10 million readers on our website, have \~600,000 subscribers to our newsletter, and have given one-on-one advice to over 6,000 people. We’ve also been one of the largest drivers of growth in the effective altruism community.

The operations team oversees 80,000 Hours’ HR, recruiting, finances, governance operations, org-wide metrics, and office management, as well as much of our fundraising, tech systems, and team coordination.

Currently, the operations team has ten full-time staff and some part-time staff. We’re planning to significantly grow the size of our operations team this year to stay on track with our ambitious goals and support a growing team.

The role

As our IT Security, Data Privacy, and Systems Lead, you would:

Evaluate and implement security controls

  • Research and make recommendations on security tools (endpoint protection, email security, etc.)
  • Lead the rollout of chosen solutions across our distributed team
  • Balance security needs with operational efficiency
  • Initially, you’ll make recommendations to leadership, but as you grow in the role,

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Executive Assistant to the CEO

About 80,000 Hours

80,000 Hours’ goal is to get talented people working on the world’s most pressing problems. After more than 10 years of research into dozens of problem areas, we’re putting most of our focus on helping people work on positively shaping the trajectory of AI, because we think it presents the most serious and urgent challenge that the world is facing right now.

We’ve had over 10 million readers on our website, have ~600,000 subscribers to our newsletter, and have given one-on-one advice to over 6,000 people. We’ve also been one of the largest drivers of growth in the effective altruism community.

The role

This role joins Niel and Jess in the Office of the CEO, working closely with them to keep 80,000 Hours running smoothly and focusing on its highest priorities.

Your responsibilities will likely include:

  • Managing Niel’s calendar, inbox, and daily planning
  • Supporting with meeting preparation and follow-up
  • Taking on a variety of ad hoc tasks for Niel. Some recent examples include:
    • Researching metrics for a speech
    • Recommending how to integrate Claude and Asana
    • Booking a restaurant for a meeting
    • Creating a record of Niel’s hiring decisions
  • Owning the logistics for recurring projects that the Office of the CEO is responsible for, such as:
    • Quarterly planning periods
    • The annual review
  • Providing flexible help with priority projects,

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Video Operations Associate/Specialist

About 80,000 Hours

80,000 Hours’ goal is to get talented people working on the world’s most pressing problems. After more than 10 years of research into dozens of problem areas, we’re putting most of our focus on helping people work on positively shaping the trajectory of AI, because we think it presents the most serious and urgent challenge that the world is facing right now.

We’ve had over 10 million readers on our website, have ~600,000 subscribers to our newsletter and have given one-on-one advice to over 6,000 people. We’ve also been one of the largest drivers of growth in the effective altruism community.

The role

This role would be great for building career capital in operations, especially if you could one day see yourself in a more senior operations role (e.g. specialising in a particular area, taking on management, or eventually being a Head of Operations or COO).

We plan to hire people at both the associate and specialist levels during this round. The associate role is a more junior position, and we expect to match candidates to the appropriate level as part of the application process so you don’t need to decide which one to apply for. To give an idea of how the roles might differ:

  • Associates are more likely to focus on owning and implementing our processes, identifying improvements and optimisations, and will take on more complex projects over time.

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Recruiting Associate/Specialist

About 80,000 Hours

80,000 Hours’ goal is to get talented people working on the world’s most pressing problems. After more than 10 years of research into dozens of problem areas, we’re putting most of our focus on helping people work on positively shaping the trajectory of AI, because we think it presents the most serious and urgent challenge that the world is facing right now.

We’ve had over 10 million readers on our website, have ~600,000 subscribers to our newsletter, and have given one-on-one advice to over 6,000 people. We’ve also been one of the largest drivers of growth in the effective altruism community.

The operations team oversees 80,000 Hours’ HR, recruiting, finances, governance operations, org-wide metrics, and office management, as well as much of our fundraising, tech systems, and team coordination.

Currently, the operations team has ten full-time staff and some part-time staff. We’re planning to significantly grow the size of our operations team this year to stay on track with our ambitious goals and support a growing team.

The role

This role would be great for building career capital in operations, especially if you could one day see yourself in a more senior operations role (e.g. specialising in a particular area, taking on management, or eventually being a Head of Operations or COO).

We plan to hire people at both the associate and specialist levels during this round. The associate role is a more junior position,

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Office Associate/Specialist

About 80,000 Hours

80,000 Hours’ goal is to get talented people working on the world’s most pressing problems. After more than 10 years of research into dozens of problem areas, we’re putting most of our focus on helping people work on positively shaping the trajectory of AI, because we think it presents the most serious and urgent challenge that the world is facing right now.

We’ve had over 10 million readers on our website, have ~600,000 subscribers to our newsletter, and have given one-on-one advice to over 6,000 people. We’ve also been one of the largest drivers of growth in the effective altruism community.

The operations team oversees 80,000 Hours’ HR, recruiting, finances, governance operations, org-wide metrics, and office management, as well as much of our fundraising, tech systems, and team coordination.

Currently, the operations team has ten full-time staff and some part-time staff. We’re planning to significantly grow the size of our operations team this year to stay on track with our ambitious goals and support a growing team.

The role

This role would be great for building career capital in operations, especially if you could one day see yourself in a more senior operations role (e.g. specialising in a particular area, taking on management, or eventually being a Head of Operations or COO).

We plan to hire people at both the associate and specialist levels during this round. The associate role is a more junior position,

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People Operations Associate/Specialist

About 80,000 Hours

80,000 Hours’ goal is to get talented people working on the world’s most pressing problems. After more than 10 years of research into dozens of problem areas, we’re putting most of our focus on helping people work on positively shaping the trajectory of AI, because we think it presents the most serious and urgent challenge that the world is facing right now.

We’ve had over 10 million readers on our website, have ~600,000 subscribers to our newsletter, and have given one-on-one advice to over 6,000 people. We’ve also been one of the largest drivers of growth in the effective altruism community.

The operations team oversees 80,000 Hours’ HR, recruiting, finances, governance operations, org-wide metrics, and office management, as well as much of our fundraising, tech systems, and team coordination.

Currently, the operations team has ten full-time staff and some part-time staff. We’re planning to significantly grow the size of our operations team this year to stay on track with our ambitious goals and support a growing team.

The role

This role would be great for building career capital in operations, especially if you could one day see yourself in a more senior operations role (e.g. specialising in a particular area, taking on management, or eventually being a Head of Operations or COO).

We plan to hire people at both the associate and specialist levels during this round. The associate role is a more junior position,

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Events Associate/Specialist

About 80,000 Hours

80,000 Hours’ goal is to get talented people working on the world’s most pressing problems. After more than 10 years of research into dozens of problem areas, we’re putting most of our focus on helping people work on positively shaping the trajectory of AI, because we think it presents the most serious and urgent challenge that the world is facing right now.

We’ve had over 10 million readers on our website, have ~600,000 subscribers to our newsletter, and have given one-on-one advice to over 6,000 people. We’ve also been one of the largest drivers of growth in the effective altruism community.

The operations function oversees 80,000 Hours’ HR, recruiting, finances, governance operations, org-wide metrics, and office management, as well as much of our fundraising, tech systems, and team coordination.

Currently, the operations team has ten full-time staff and some part-time staff. We’re planning to significantly grow the size of our operations team this year to stay on track with our ambitious goals and support a growing team.

The role

This role would be great for building career capital in operations, by helping us design and run high-quality events that strengthen our team, culture, and connections in the AI safety space. We’re looking for an Events Associate/Specialist who can take ownership of the day-to-day logistics and execution of our events.

We plan to hire people at both the associate and specialist levels during this round.

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Operations generalists

About 80,000 Hours

80,000 Hours’ goal is to get talented people working on the world’s most pressing problems. After more than 10 years of research into dozens of problem areas, we’re putting most of our focus on helping people work on positively shaping the trajectory of AI, because we think it presents the most serious and urgent challenge that the world is facing right now.

We’ve had over 10 million readers on our website, have ~600,000 subscribers to our newsletter, and have given one-on-one advice to over 6,000 people. We’ve also been one of the largest drivers of growth in the effective altruism community.

The operations team oversees 80,000 Hours’ HR, recruiting, finances, governance operations, org-wide metrics, and office management, as well as much of our fundraising, tech systems, and team coordination.

Currently, the operations team has ten full-time staff and some part-time staff. We’re planning to significantly grow the size of our operations team this year to stay on track with our ambitious goals and support a growing team.

To learn more about the other teams hiring during this round (video team, office of the CEO), see the individual job descriptions.

The role

This role would be great for building career capital in operations, especially if you could one day see yourself in a more senior operations role (e.g. specialising in a particular area, taking on management, or eventually being a Head of Operations or COO).

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Rebuilding after apocalypse: What 13 experts say about bouncing back

What happens when civilisation faces its greatest tests?

This compilation brings together insights from researchers, defence experts, philosophers, and policymakers on humanity’s ability to survive and recover from catastrophic events. From nuclear winter and electromagnetic pulses to pandemics and climate disasters, we explore both the threats that could bring down modern civilisation and the practical solutions that could help us bounce back.

You’ll hear from:

  • Zach Weinersmith on how settling space won’t help with threats to civilisation anytime soon (unless AI gets crazy good) (from episode #187)
  • Luisa Rodriguez on what the world might look like after a global catastrophe, how we might lose critical knowledge, and how fast populations might rebound (#116)
  • David Denkenberger on disruptions to electricity and communications we should expect in a catastrophe, and his work researching low-cost, low-tech solutions to make sure everyone is fed no matter what (#50 and #117)
  • Lewis Dartnell on how we could recover without much coal or oil, and changes we could make today to make us more resilient to potential catastrophes (#131)
  • Andy Weber on how people in US defence circles think about nuclear winter, and the tech that could prevent catastrophic pandemics (#93)
  • Toby Ord on the many risks to our atmosphere, whether climate change and rogue AI could really threaten civilisation, and whether we could rebuild from a small surviving population (#72 and #219)
  • Mark Lynas on how likely it is that widespread famine from climate change leads to civilisational collapse (#85)
  • Kevin Esvelt on the human-caused pandemic scenarios that could bring down civilisation — and how AI could help bad actors succeed (#164)
  • Joan Rohlfing on why we need to worry about more than just nuclear winter (#125)
  • Annie Jacobsen on the rings of annihilation and electromagnetic pulses from nuclear blasts (#192)
  • Christian Ruhl on thoughtful philanthropy that funds “right of boom” interventions to prevent nuclear war from threatening civilisation (80k After Hours)
  • Athena Aktipis on whether society would go all Mad Max in the apocalypse, and the best ways to prepare for a catastrophe (#144)
  • Will MacAskill on why potatoes are so cool (#130 and #136)

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The AI 2027 scenario and what it means: a video tour

AI 2027, a research-based scenario and report from the AI Futures Project, combines forecasting and storytelling to explore a possible future where AI radically transforms the world by 2027.

Some of you will have read this report, or come across it. Lead author, Daniel Kokotajlo, was interviewed by New York Times columnist Ross Douthat and US Vice President JD Vance claims to have read the report. Some of you might not have heard of it yet, or haven’t had the time to dig in…

So we made a video diving into it.

Why take the AI 2027 scenario seriously

The report goes through the creation of AI agents, job loss, the role of AIs improving other AIs (R&D acceleration loops), security crackdowns, misalignment — and then a choice: slow down or race ahead.

Kokotajlo’s predictions from 2021 (pre-ChatGPT) in What 2026 looks like have proved prescient, and co-author Eli Lifland is among the world’s top forecasters. So even if you don’t end up buying all its claims, the report’s grounding in serious forecaster views, research, and dozens of wargames makes it worth taking seriously.

Why watch our AI 2027 video

Containing expert interviews, our analysis, and discussion of what a sane world would be doing, we think the video will be an enjoyable and informative watch whether you’re familiar with the report or not.

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#220 – Ryan Greenblatt on the 4 most likely ways for AI to take over, and the case for and against AGI in under 8 years

Ryan Greenblatt — lead author on the explosive paper “Alignment faking in large language models” and chief scientist at Redwood Research — thinks there’s a 25% chance that within four years, AI will be able to do everything needed to run an AI company, from writing code to designing experiments to making strategic and business decisions.

As Ryan lays out, AI models are “marching through the human regime”: systems that could handle five-minute tasks two years ago now tackle 90-minute projects. Double that a few more times and we may be automating full jobs rather than just parts of them.

Will setting AI to improve itself lead to an explosive positive feedback loop? Maybe, but maybe not.

The explosive scenario: Once you’ve automated your AI company, you could have the equivalent of 20,000 top researchers, each working 50 times faster than humans with total focus. “You have your AIs, they do a bunch of algorithmic research, they train a new AI, that new AI is smarter and better and more efficient… that new AI does even faster algorithmic research.” In this world, we could see years of AI progress compressed into months or even weeks.

With AIs now doing all of the work of programming their successors and blowing past the human level, Ryan thinks it would be fairly straightforward for them to take over and disempower humanity, if they thought doing so would better achieve their goals. In the interview he lays out the four most likely approaches for them to take.

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Early-stage startup employee

Joining a rapidly growing tech startup can be a great option for career capital because you learn how to get stuff done and gain organisation-building skills that are very useful to many social impact projects. If the startup does well, you can also earn a significant amount of money and gain a credential in the tech world. You might also be able to find a startup with a positive direct impact.

If you can work at an AI applications startup (using AI to solve a particular problem rather than working on frontier development), then you also get to learn about how to deploy AI, which seems like one of the most valuable skills (though be cautious about roles that could accelerate AI development).

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#219 – Toby Ord on graphs AI companies would prefer you didn’t (fully) understand

The era of making AI smarter by just making it bigger is ending. But that doesn’t mean progress is slowing down — far from it. AI models continue to get much more powerful, just using very different methods. And those underlying technical changes force a big rethink of what coming years will look like.

Toby Ord — Oxford philosopher and bestselling author of The Precipice — has been tracking these shifts and mapping out the implications both for governments and our lives.

As he explains, until recently anyone can access the best AI in the world “for less than the price of a can of Coke.” But unfortunately, that’s over.

What changed? AI companies first made models smarter by throwing a million times as much computing power at them during training, to make them better at predicting the next word. But with high quality data drying up, that approach petered out in 2024.

So they pivoted to something radically different: instead of training smarter models, they’re giving existing models dramatically more time to think — leading to the rise in “reasoning models” that are at the frontier today.

The results are impressive but this extra computing time comes at a cost: OpenAI’s o3 reasoning model achieved stunning results on a famous AI test by writing an Encyclopedia Britannica‘s worth of reasoning to solve individual problems — at a cost of over $1,000 per question.

This isn’t just technical trivia: if this improvement method sticks, it will change much about how the AI revolution plays out — starting with the fact that we can expect the rich and powerful to get access to the best AI models well before the rest of us.

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[Closed] Expression of interest: Head of Recruiting

We’re looking for someone to build and lead 80,000 Hours’ recruiting function from scratch.

We’d like to make 15–25 strong hires each year through a recruiting team. Currently, we make around 10 hires — each of which represents a very large investment in capacity from team leads — which is a major bottleneck on our growth.

Our ideal candidate can solve the problems, hire the team, and build the systems needed to pull this off. So we expect this to be a challenging role which will require substantial relevant experience.

We’re looking for someone who has experience with:

  • The personnel challenges faced by organisations working in EA or AI — you’ve either worked at an EA organisation, an AI safety organisation, or have otherwise developed a strong understanding of the landscape of hiring challenges these organisations face.
  • Professional recruiting — this could be as an internally-facing recruiter or as a headhunter. Recruiting for your own team could be enough, especially if you’ve been especially interested in recruitment along the way.
  • Leading a team — you’ve managed people before and understand what it takes to build and lead a function.

We expect that you’ll initially report to Brenton Mayer (COO) and then transition to reporting to Sashika Coxhead (Head of People Operations) when she returns from maternity leave.

If you meet all three of the criteria mentioned above,

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Updates to our list of the world’s most pressing problems

80,000 Hours’ aim is to help people find careers that tackle the world’s most pressing problems. To do this, one thing we do is maintain a public list of what we see as the issues where additional people can have the greatest positive impact.

We’ve just made significant updates to our list. Here are the biggest changes:

  • We’ve broadened our coverage of particularly pressing issues downstream of the possibility that artificial general intelligence (AGI) might be here soon. In particular, we added a profile on AI-enabled power grabs near the top of our list and are adding several writeups of new emerging challenges that advanced AI could create or worsen.
  • We’ve removed ‘meta’ problems for simplicity and clarity. Our problem profiles list used to feature articles on building effective altruism, broadly improving institutional decision making, and global priorities research — which are all approaches to improving our ability to solve the world’s most pressing problems. Grouping these ‘meta problems’ with object-level problems sometimes causes confusion and makes it hard to compare across cause areas, so we’ve now taken them off the list. But we still think these topics are very important, so the articles are still live on our site, and related articles appear on our list of impactful career paths.
  • We’ve streamlined the presentation by consolidating related issues and restructuring the page as a more unified ranking rather than separate categories.

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How not to lose your job to AI

About half of people are worried they’ll lose their job to AI. And they’re right to be concerned: AI can now complete real-world coding tasks on GitHub, generate photorealistic video, drive a taxi more safely than humans, and do accurate medical diagnosis. And over the next five years, it’s set to continue to improve rapidly. Eventually, mass automation and falling wages are a real possibility.

But what’s less appreciated is that while AI drives down the value of skills it can do, it drives up the value of skills it can’t. Wages (on average) will increase before they fall, as automation generates a huge amount of wealth, and the remaining tasks become the bottlenecks to further growth. As I’ll explain, ATMs actually increased employment of bank clerks — until online banking automated the job much more.

Your best strategy is to learn the skills that AI will make more valuable, trying to ride the wave of automation. So what are those skills? Here’s a preview:

Skills most likely to increase in value as AI progresses

These will be especially valuable when combined with knowledge of fields needed for AI including machine learning, cyber & information security, data centre & power plant construction, robotics development and maintenance, and (lesso) fields that could expand a lot given economic growth.

In contrast, the future for these skills seems a lot more uncertain:

  • Coding,

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#218 – Hugh White on why Trump is abandoning US hegemony – and that’s probably good

For decades, US allies have slept soundly under the protection of America’s overwhelming military might. Donald Trump — with his threats to ditch NATO, seize Greenland, and abandon Taiwan — seems hell-bent on shattering that comfort.

But according to Hugh White — one of the world’s leading strategic thinkers, emeritus professor at the Australian National University, and author of Hard New World: Our Post American Future — Trump isn’t destroying American hegemony. He’s simply revealing that it’s already gone.

“Trump has very little trouble accepting other great powers as co-equals,” Hugh explains. And that happens to align perfectly with a strategic reality the foreign policy establishment desperately wants to ignore: fundamental shifts in global power have made the costs of maintaining a US-led hegemony prohibitively high.

Even under Biden, when Russia invaded Ukraine, the US sent weapons but explicitly ruled out direct involvement. Ukraine matters far more to Russia than America, and this “asymmetry of resolve” makes Putin’s nuclear threats credible where America’s counterthreats simply aren’t.

Hugh’s gloomy prediction: “Europeans will end up conceding to Russia whatever they can’t convince the Russians they’re willing to fight a nuclear war to deny them.”

The Pacific tells the same story. Despite Obama’s “pivot to Asia” and Biden’s tough talk about “winning the competition for the 21st century,” actual US military capabilities there have barely budged while China’s have soared, along with its economy — which is now bigger than the US’s, as measured in purchasing power. Containing China and defending Taiwan would require America to spend 8% of GDP on defence (versus 3.5% today) — and convince Beijing it’s willing to accept Los Angeles being vaporised. Unlike during the Cold War, no president — Trump or otherwise — can make that case to voters.

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3 reasons AGI might still be decades away

We recently argued that AGI could be here by 2030.

And we’re not the only ones — CEOs of leading AI labs and many AI researchers are saying similar things.

But many people disagree, and there’s a good chance that AGI won’t be here by 2030. Some think it could still be decades away.

So what are the reasons to expect a longer path to AGI?

Reason 1: The path to AGI isn’t obvious

Today’s AI systems can write excellent code, produce research reports, and do Nobel Prize-worthy work in protein folding.

But frontier systems still can’t:

  • Independently carry out complicated tasks for hours, days, or weeks
  • Interact with the physical world in complex and adaptive ways
  • Consistently learn from past interactions to improve performance over time

In other words, we don’t yet have AGI — AI systems with general intelligence that can reliably replace humans on a wide range of tasks.

In 2024, OpenAI’s Sam Altman declared, “we are now confident we know how to build AGI.” But how will we get there?

Some people think that we can build AGI by scaling up existing models. But others argue that scaling has only seriously improved AI performance in areas like software engineering, where the tasks are clearly defined and often quickly verifiable.

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#217 – Beth Barnes on the most important graph in AI right now — and the 7-month rule that governs its progress

Beth Barnes on the most important graph in AI right now — and the 7-month rule that governs its progress

AI models today have a 50% chance of successfully completing a task that would take an expert human one hour. Seven months ago, that number was roughly 30 minutes — and seven months before that, 15 minutes.

These are substantial, multi-step tasks requiring sustained focus: building web applications, conducting machine learning research, or solving complex programming challenges.

Today’s guest, Beth Barnes, is CEO of METR (Model Evaluation & Threat Research) — the leading organisation measuring these capabilities.

Beth’s team has been timing how long it takes skilled humans to complete projects of varying length, then seeing how AI models perform on the same work.

The resulting paper from METR, “Measuring AI ability to complete long tasks,” made waves by revealing that the planning horizon of AI models was doubling roughly every seven months. It’s regarded by many as the most useful AI forecasting work in years.

The companies building these systems aren’t just aware of this trend — they want to harness it as much as possible, and are aggressively pursuing automation of their own research.

That’s both an exciting and troubling development, because it could radically speed up advances in AI capabilities, accomplishing what would have taken years or decades in just months. That itself could be highly destabilising, as we explored in a previous episode: Will MacAskill on AI causing a “century in a decade” — and how we’re completely unprepared.

And having AI models rapidly build their successors with limited human oversight naturally raises the risk that things will go off the rails if the models at the end of the process lack the goals and constraints we hoped for.

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