You might have heard that '95% of corporate AI pilots' are failing. It was one of the most widely cited AI statistics of 2025, parroted by media outlets everywhere. It helped trigger a Nasdaq selloff and became a pillar of the case that 'AI is overhyped'. The problem: it's 100% wrong. And not by accident either.

If you carefully read the underlying report, ostensibly from MIT, you find the data point in the opposite direction.

But that was all buried, with the authors instead torturing the results to tell a very different narrative. Why?

Well, the research likely came with a hidden commercial agenda from the start.

Learn more, video, and full transcript: https://80k.info/mit-ai-study

Today Rob Wiblin breaks down how an opaque, conflicted, barely-scrutinised report managed to attract the MIT label, move markets and have a vast impact on global opinion about AI.

This episode was recorded on February 13, 2026.

Chapters:

• The myth (00:00)

• The math was totally wrong (00:52)

• The absurd bar for success (01:46)

• The study ignores its own findings (03:29)

• The sample was tiny (04:50)

• The report wasn’t even available to check (05:55)

• The hidden motives that likely drove this 'research' (06:58)

• The real lesson (09:28)

Video and audio editing: Dominic Armstrong, Milo McGuire, Luke Monsour, and Simon Monsour

Camera operator: Dominic Armstrong

Production: Nick Stockton, Elizabeth Cox, and Katy Moore

Hundreds of millions already turn to AI on the most personal of topics — therapy, political opinions, and how to treat others. And as AI takes over more of the economy, the character of these systems will shape culture on an even grander scale, ultimately becoming “the personality of most of the world’s workforce.”

So… should they be designed to push us towards the better angels of our nature? Or simply do as we ask? Will MacAskill, philosopher and senior research fellow at Forethought, has been thinking through that and the other thorniest issues that come up in designing an AI personality.

He’s also been exploring how we might coexist peacefully with the ‘superintelligent AI’ companies are racing to build. He concludes that we should train such systems to be very risk averse, pay them for their work, and build institutions that enable humans to make credible contracts with AIs themselves.

Will and host Rob Wiblin also discuss what a good world after superintelligence would actually look like — a subject that has received surprisingly little attention from the people working to make it. Will argues that we shouldn’t aim for a specific utopian vision: we don’t know enough about what the best possible future actually is to aim directly for it, and trying to lock in today’s best guesses forever risks baking in errors we can’t yet see.

Will and Rob explore what we can do to steer towards a good future instead, along with why a coalition of democracies building superintelligence together is safer than any single actor, how absurdly useful ChatGPT is for analytic philosophy, and more.

Learn more, video, and full transcript: https://80k.info/wm26

This episode was recorded on February 6, 2026.

Chapters:

• Cold open (00:00:00)
• Will MacAskill is back — for a 6th time! (00:00:29)
• AIs’ “character” could be vital to securing a good future (00:00:59)
• The panic over sychophancy is justified (00:07:54)
• How opinionated should AI be about ethics? (00:12:59)
• Commercial pressures won’t fully determine AI character (00:29:38)
• Risk-averse AI would rather strike a deal than attempt a coup (00:36:46)
• A coalition of democracies building superintelligence is safer than one doing it alone (01:06:40)
• How selfish agents could fund the common good (01:19:13)
• Why not push for pausing AI development? (01:38:39)
• Effective altruism is making a comeback post-SBF (01:48:18)
• EA in the age of AGI (01:56:15)
• Viatopia: an alternative to utopia (02:05:08)
• The least bad alternative to total utilitarianism? (02:34:42)
• How AI could kickstart a golden age of philosophy (02:58:03)

Video and audio editing: Dominic Armstrong, Milo McGuire, Luke Monsour, and Simon Monsour
Music: CORBIT
Camera operator: Alex Miles
Production: Elizabeth Cox, Nick Stockton, and Katy Moore

Hundreds of prominent AI scientists and other notable figures signed a statement in 2023 saying that mitigating the risk of extinction from AI should be a global priority. At 80,000 Hours, we’ve considered risks from AI to be the world’s most pressing problem since 2016.

But what led us to this conclusion? Could AI really cause human extinction? We’re not certain, but we think the risk is worth taking very seriously.

In particular, as companies create increasingly powerful AI systems, there’s a concerning chance that:

• These AI systems may develop dangerous long-term goals we don’t want.
• To pursue these goals, they may seek power and undermine the safeguards meant to contain them.
• They may even aim to disempower humanity and potentially cause our extinction.

This article is written by Cody Fenwick and Zershaaneh Qureshi, and narrated by Zershaaneh Qureshi. It discusses why future AI systems could disempower humanity, what current AI research reveals about behaviours like power-seeking and deception, and how you can help mitigate the dangers.

You can see the original article — packed with graphs, images, footnotes, and further resources — on the 80,000 Hours website:

https://80000hours.org/problem-profiles/risks-from-power-seeking-ai/

Chapters:

• Risks from power-seeking AI systems (00:01:00)
• Introduction (00:01:17)
• Summary (00:03:09)
• Why are the risks from power-seeking AI a pressing world problem? (00:04:04)
• Section 1: Humans will likely build advanced AI systems with long-term goals (00:05:43)
• Section 2: AIs with long-term goals may be inclined to seek power (00:11:32)
• Section 3: These power-seeking AI systems could successfully disempower humanity (00:26:26)
• Section 4. People might create power-seeking AI systems without enough safeguards, despite the risks (00:38:34)
• Section 5: Work on this problem is neglected and tractable (00:47:37)
• Section 6: What are the arguments against working on this problem? (00:59:20)
• Section 7: How you can help (01:25:07)
• Thank you for listening (01:28:56)

Audio editing: Dominic Armstrong
Production: Zershaaneh Qureshi, Elizabeth Cox, and Katy Moore