HAI affiliate faculty member Chelsea Finn discusses the valid uses for tools like ChatGPT, the concerns when they’re used for nefarious purposes, and the ways to spot AI text.

The hype around generative AI prompts discussion on risks, such as bad actors propagating disinformation, says HAI Co-Director Fei-Fei Li.

A new study with HAI Associate Director Daniel E. Ho documents systemic discrimination in how the IRS selects taxpayers to be audited, with implications for a debate on the agency’s funding.

While OpenAI has captured the public’s imagination with ChatGPT, ultimately the technology may not change the balance of power among the tech giants. Center for Research on Foundation Models Director Percy Liang calls for more transparency.

CRFM’s Percy Liang explains foundation models, key findings of benchmarking project HELM, and gaps between public and private models on this episode of the podcast The Data Exchange.

Erik Brynjolfsson, Stanford Digital Economy Lab faculty director, says ChatGPT “will get rid of a lot of routine, rote type of work and at the same time people using it may be able to do more creative work.”

Jennifer King, privacy and data policy fellow at Stanford HAI, talks risk of the chat tool and anticipates its proliferation despite those risks.

Expect a rush of new AI tools in 2023, but likely ones that will hit the market without much thought to the business models or societal impact, says HAI Associate Director Russ Altman.

In this article, Axios reports on an HAI event for journalists which focused in part on the critical role humans play in the development and deployment of AI.

AI’s automatic writing tools are making it easier for students to cheat. Associate Director Rob Reich says tech companies and AI developers must agree to self-regulate.

HAI’s Center for Research on Foundation Models launches Holistic Evaluation of Language Models (HELM), the first benchmarking project aimed at improving the transparency of language models and the broader category of foundation models. 

The HAI fall conference challenged attendees to think about what it means to put humans at the center of AI, rather than just “in the loop.”

Artificial intelligence has the potential to transform corporate decision making but getting workers to actually use the technologies is just as important as making sure the systems work in the first place. HAI Faculty Affiliate Melissa Valentine offers five lessons for success.

HAI Policy Director Russell Wald calls for executive action and more congressional hearings and legislation to address the rapidly escalating challenges of AI as identified in the AI Bill of Rights.

Stanford Digital Economy Lab Director Erik Brynjolfsson explains that the goal of AI that mimics human abilities has led to direct economic competition between people and machines—what he calls The Turing Trap. HAI Co-Director Fei-Fei Li weighs in.

HAI Associate Director Curt Langlotz says “will A.I. replace radiologists?” is “the wrong question.” Instead, he says, “The right answer is: Radiologists who use A.I. will replace radiologists who don’t.”

HAI Policy Director Russell Wald says the new Blueprint for an AI Bill of Rights issued by the White House lacks details or mechanisms for enforcement. 

Foundation models present new opportunities for a wide range of professional applications including law and government. JD/PhD Candidate Peter Henderson explains the “Pile of Law” model and data set he and others at RegLab developed for such uses.