eventSeminar
Khaoula Chehbouni | Best Practices for the Use of LLMs as Judges
SeminarNov 13, 20261:00 PM - 2:15 PM
November
13
2026
An AI Measurement Science (AIMS) Seminar Series
Event
An AI Measurement Science (AIMS) Seminar Series
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An AI Measurement Science (AIMS) Seminar Series
An AI Measurement Science (AIMS) Seminar Series
Phil Lewis from the National Center for O*NET Development will talk about data infrastructure the US Department of Labor provides, and how AI is used to update it. A panel with Diyi Yang from the Stanford Computer Science Department and DEL’s Erik Brynjolfsson will discuss the opportunities of a new partnership between Stanford and the National Center for O*NET Development.
Phil Lewis from the National Center for O*NET Development will talk about data infrastructure the US Department of Labor provides, and how AI is used to update it. A panel with Diyi Yang from the Stanford Computer Science Department and DEL’s Erik Brynjolfsson will discuss the opportunities of a new partnership between Stanford and the National Center for O*NET Development.
In the last year, AI models have rapidly improved on public benchmarks measuring their ability to carry out research tasks autonomously. Such performance suggests that models may be capable of automating parts of the AI R&D process itself, thereby accelerating the pace of AI progress.
In the last year, AI models have rapidly improved on public benchmarks measuring their ability to carry out research tasks autonomously. Such performance suggests that models may be capable of automating parts of the AI R&D process itself, thereby accelerating the pace of AI progress.
"In this talk I hope to illustrate how AI ethics can avoid the undesirable extremes of two dimensions:
First dimension: Complacency vs Inflation
On the one hand, I will argue that we should eschew the complacent view that AI presents no novel challenges for ethics, the view that AI is just a technology like any other, so extant ethical principles for non-AI technologies are all we need. On the other hand, I will also argue that we should also avoid the inflationary view that the need for new ethical principles for AI derives from the fact that AI systems are themselves moral agents and/or patients.
Second dimension: Reactive systems vs Robots with Obligations
On the one hand, I will argue that the ethical construction of autonomous AI systems (including, but not limited to, autonomous robots such as driverless cars) will require that such systems do more than merely transform an input signal to an output signal (as is prevalent in much machine learning technology); at least part of that transformation, to have the right counterfactual richness that ethics requires, will have to have deliberative structure. On the other hand, AI systems that reason about their ethical obligations and what is morally permissible for them are not a solution since AI systems will not, for the foreseeable future, be the kinds of things that could have ethical obligations or moral permissions.
For each of these dimensions, I give a specific example (a policy, and a design, respectively) that avoids the horns of the dilemma, and the moral hazards they entail." - Ron Chrisley
