Trump eliminates Biden AI policies

Trump has signed an Executive Order “eliminating harmful Biden Administration AI policies and enhancing America’s global AI dominance.” (Fact Sheet) In a Fact Sheet he calls Biden’s order(s) dangerous and onerous using the usual stifling innovation argument:

The Biden AI Executive Order established unnecessarily burdensome requirements for companies developing and deploying AI that would stifle private sector innovation and threaten American technological leadership.

There are, however, other components to the rhetoric:

  • It “established the commitment … to sustain and enhance America’s dominance to promote human flourishing, economic competitiveness, and national security.” The human flourishing seems to be
  • It directs the creation of an “AI Action Plan” within 180 days to sustain dominance. Nothing is mentioned about flourishing in regards to the plan. Presumably dominance is flourishing. This plan and review of policies will presumably where we will see the details of implementation. It sounds like the Trump administration may keep some of the infrastructure and policies. Will they, for example, keep the AI Safety Institute in NIST?
  • There is an interesting historic section reflecting back to activities of the first Trump administration noting that “President Trump also took executive action in 2020 to establish the first-ever guidance for Federal agency adoption of AI to more effectively deliver services to the American people and foster public trust in this critical technology.” Note the use of the word “trust”. I wonder if they will return to trustworthy AI language.
  • There is language about how “development of AI systems must be free from ideological bias or engineered social agendas.” My guess is that the target is AIs that don’t have “woke” guardrails.

It will be interesting to track what parts of the Biden orders are eliminated and what parts are kept.

 

Humanity’s Last Exam

Researchers with the Center for AI Safety and Scale AI are gathering submissions for Humanity’s Last Exam. The submission form is here. The idea is to develop an exam with questions from a breadth of academic specializations that current LLMs can’t answer.

While current LLMs achieve very low accuracy on Humanity’s Last Exam, recent history shows benchmarks are quickly saturated — with models dramatically progressing from near-zero to near-perfect performance in a short timeframe. Given the rapid pace of AI development, it is plausible that models could exceed 50% accuracy on HLE by the end of 2025. High accuracy on HLE would demonstrate expert-level performance on closed-ended, verifiable questions and cutting-edge scientific knowledge, but it would not alone suggest autonomous research capabilities or “artificial general intelligence.” HLE tests structured academic problems rather than open-ended research or creative problem-solving abilities, making it a focused measure of technical knowledge and reasoning. HLE may be the last academic exam we need to give to models, but it is far from the last benchmark for AI.

One wonders if it really will be the last exam. Perhaps we will get more complex exams that test for integrated skills. Andrej Karpathy criticises the exam on X. I agree that what we need are AIs able to do intern-level complex tasks rather than just answering questions.

Do we really know how to build AGI?

Sam Altman in a blog post titled Reflections looks back at what OpenAI has done and then predicts that they know how to build AGI,

We are now confident we know how to build AGI as we have traditionally understood it. We believe that, in 2025, we may see the first AI agents “join the workforce” and materially change the output of companies. We continue to believe that iteratively putting great tools in the hands of people leads to great, broadly-distributed outcomes.

It is worth noting that the definition of AGI (Artificial General Intelligence) is sufficiently vague that meeting this target could become a matter of semantics. None the less, here are some definitions of AGI from OpenAI or others about OpenAI,

  • “OpenAI’s mission is to ensure that artificial general intelligence (AGI)—by which we mean highly autonomous systems that outperform humans at most economically valuable work—benefits all of humanity.” – Note the “economically valuable work”. I wonder if philosophizing or making art is valuable? Is intelligence being limited here to economics?
  • “AI systems that are generally smarter than humans” – This is somewhat circular as brings us back to defining “smartness”, another work for “intelligence”.
  • “any system that can outperform humans at most tasks” – This could be timed to the quote above and the idea of AI agents that can work for companies outperforming humans. It seems to me we are nowhere near this if you include physical tasks.
  • “an AI system that can generate at least $100 billion in profits” – This is the definition used by OpenAI and Microsoft to help identify when OpenAI doesn’t have to share technology with Microsoft any more.

Constellate Sunset

The neat ITHAKA Constellate project is being shut down. It sounds like it was not financially sustainable.

As of November 2024, ITHAKA made the decision to sunset Constellate on July 1, 2025. While we’re proud of the meaningful impact Constellate has had on individuals and institutions, helping advance computational literacy and text analysis skills across academia, we have concluded that continuing to support the platform and classes is not sustainable for ITHAKA in the long term. As a nonprofit organization, we need to focus our resources on initiatives that can achieve broad-scale impact aligned with our mission. Despite Constellate’s success with its participating institutions, we haven’t found a path to achieve this broader impact.

It sounds like this sort of analytical support is best supported in universities by courses, workshops etc. Constellate developed cool notebooks (available in GitHub), courses built on the notebooks, and webinar recordings.

The Gamergate Social Network: Interpreting Transphobia and Alt-Right Hate Online

Catherine Bevan led the writing of a paper that just got published in Digital Studies, The Gamergate Social Network: Interpreting Transphobia and Alt-Right Hate Online. The paper explores transphobia in the gamergate controversy through a social network analysis. Catherine did a lot of work hand tagging events and then visualizing them.

How safe is AI safety?

Today I gave a plenary talk on “How Safe is AI Safety?” to open a Workshop on AI and DH (Part 1) organized by the Centre de recherche interuniversitaire sur les humanités numériques (CRIHN) at the Université de Montréal.

In the paper I looked at how AI safety is being implemented in Canada and what is the scope of the idea. I talked about the shift from Responsible AI to AI Safety in the Canadian government’s rhetoric.

I’m trying to figure out what to call the methodology I have developed for this and other research excursions. It has elements of Foucault’s geneaology of ideas – trying to follow ideas that are obvious through the ways the ideas are structured in institutions. Or, it is an extension of Ian Hacking’s idea of historical ontology where we try to understand ideas about things through their history.

 

Metaculus on AGI Outcomes

Listening to Jacob Steinhardt on The Hinton Lectures™ I learned about Metaculus, which is a forecasting service which is a public benefit company. It has a focus area on AI Progress with lots of AI related forecasts, (which seems to be a huge area of interest.) This service coordinates human forecasts and builds infrastructure to facilitate others in forecasting.

Neat!

Claudette – An Automated Detector of Potentially Unfair Clauses in Online Terms of Service

Randy Goebel gave a great presentation on the use of AI in Judicial Decision Making on Friday to my AI Ethics course. He showed us an example tool called Claudette which can be used to identify potentially unfair clauses in a Terms and Conditions document. You can try it here at the dedicated web site here.

Why is this useful? It provides a form of summary of a document none of us read that could help us catch problematic clauses. It could help us be more careful users of applications.

Can A.I. Be Blamed for a Teen’s Suicide?

The New York Times has a story about youth who committed suicide after extended interactions with a character on Character.ai. The story, Can A.I. Be Blamed for a Teen’s Suicide? describes how Sewell Setzer III has long discussions with a character called Daenerys Targaryen from the Game of Thrones series. He became isolated and got attached to Daenerys. He eventually shot himself and now his mother is suing Character.ai.

Here is an example of what he wrote in his journal,

I like staying in my room so much because I start to detach from this ‘reality,’ and I also feel more at peace, more connected with Dany and much more in love with her, and just happier.

The suit claims that Character.ai’s product was untested, dangerous and defective. It remains to be seen if these types of suits will succeed. In the meantime we need to be careful with these social AIs.