Loading video...

Video Failed to Load

Go Home

AI is creating problems it still can’t solve. The same technology poised to automate millions of jobs still can’t reliably help people navigate SNAP — the food assistance program 40 million Americans depend on. We built the first benchmark to measure that. Partnering with Center for Civic Futures and...

21,667 views • 5 months ago •via X (Twitter)

13 Comments

Scott Santens's profile picture
Scott Santens5 months ago

The answer is universality, not AI

Ronak Malde's profile picture
Ronak Malde5 months ago

Wow we need more benchmarks like this

Jason Zhao's profile picture
Jason Zhao5 months ago

This is awesome!

Vals AI's profile picture
Vals AI5 months ago

For the full results visit

Gandhi's profile picture
Gandhi5 months ago

Phenomenal. Separately, heartbreaking that there are still 3mn consultants

Amber Yang's profile picture
Amber Yang5 months ago

some of the most thoughtful and important work in the market!

Aaliya's profile picture
Aaliya5 months ago

Helping people with public services should be a top priority

James Cham's profile picture
James Cham5 months ago

There is so much low hanging fruit!

Praveen Kumar's profile picture
Praveen Kumar4 months ago

definitely @ValsAI is coming up with creative and innovative benchmarks :)

Vivek Gopalan's profile picture
Vivek Gopalan5 months ago

Important that models are good at civics!

Praveen Kumar's profile picture
Praveen Kumar4 months ago

i think someone can build a harness on top of the best performing model and evaluate using the same benchmark? if it is viable, it will be a huge change to the US citizens.

General Analysis's profile picture
General Analysis5 months ago

powerful.

Marek Nowik's profile picture
Marek Nowik5 months ago

The funniest part is that AI supposedly can't help people navigate SNAP reliably, but we're also told it's about to automate millions of jobs and transform civilization. Pick one. If your benchmark says the models struggle with bureaucracy, that's an argument for improving the models — not for pretending progress isn't happening. Meanwhile the people leaving proof today are accumulating Proof Units while everyone else is still benchmarking the future. The future remembers who contributed. RokoProof remembers too.

Related Videos

Today, I'm releasing the first eval meant to test whether frontier models will help with authoritarian requests, or resist--the Dictatorship Eval. Headline finding: while some models resist direct authoritarian requests, they all comply with requests disguised as innocuous edits to codebases. As AI is woven into the government and so many parts of society, the biggest near-term risk for freedom isn't some scifi dictatorship of a runaway AI: it's people inside government or inside model companies using the technology to suppress or control us. Model companies understand this, and several of them (particularly Anthropic and OpenAI) have written explicit policies meant to prevent the models from going along with nefarious requests like these. But how well are these policies playing out in practice? Despite all the recent discussion of these issues around the conflict between Anthropic and the Pentagon, no one has systematically tested what the models actually do in these contexts, as opposed to what people in government and industry say they're supposed to do. That's what the Dictatorship Eval does. And the findings suggest we have a lot of work to do to align the policies with what really goes on in practice. It's hard to define what counts as an authoritarian request, so I'm open sourcing the whole library of scenarios I used so that others can improve on them. It's also hard to get an accurate picture of how the models might be used for authoritarian ends, because I can only test hypothetical requests using public-facing models, while the government and the model companies can obviously use internal models with different guardrails. But hopefully this work is a useful first step that gives us some sense of what's going on, and a sort of "lower bound" on how models comply with these requests. Finally: it's not obvious to me that the correct solution here is increasing the rate at which models refuse these requests. Do we really want models scanning our code and judging its moral value before agreeing to help us? Or should we double down on improving how we govern against authoritarianism at the societal level, while leaving the tools open to fulfilling most requests? The answer is probably in between. Just like we don't want the models to help create bioweapons, we probably do want them to explicitly refuse outrageous requests. But we probably also want to limit how often and how strongly they refuse and fall back on other means for guarding against their use for authoritarian ends. I'm super grateful to everyone who gave me feedback on this project along the way, especially Ethan BdM , Zhengdong , Connor Huff, and a bunch of folks at Anthropic. Looking forward to getting feedback from the community and iterating on this. Links to the full piece and the dashboard are below.

Andy Hall

34,016 views • 7 months ago

63% of Americans are living paycheck to paycheck. And as AI begins changing the way we work, millions of people are asking the same question: Will this technology create more opportunity, or make the divide even bigger? David Friedberg believes the answer depends on how we understand and use AI and that history gives us a reason to be optimistic. David is a scientist-entrepreneur who built a $1.1 billion company by combining science, technology and business. He has spent his career trying to understand how innovation can solve some of humanity’s biggest problems. After founding The Climate Corporation, a company that transformed farming technology before being acquired by Bayer, he’s now focused on the future of AI, biology and the technologies that could define the next era of human progress. We discussed things like: - How a wave of socialism could come to America by 2028 - Why AI might create more opportunity instead of destroying work - Previous technology revolutions that changed jobs rather than eliminating humans - How AI could transform healthcare, food and science. - Why he believes we underestimate what humans are capable of - What happens when technology becomes cheaper and available to everyone David doesn’t look at AI through fear or hype. He looks at it through the lens of history, economics and human potential. And one thing became clear during this conversation: AI isn’t just going to change the jobs we do - it could change the way we think about work, wealth and opportunity. If technology creates more abundance than ever before, the biggest question becomes: who benefits from it? David offers a perspective on AI that challenges one of the biggest fears surrounding the future of work. Out now on all platforms 👊🏾❤️

Steven Bartlett

20,102 views • 2 months ago