I asked GPT v4 your question:

> What has Eliezer Yudkowsky produced, in terms of scientific output? I've read plenty of his lesswrong's writing on the idea of rationalist, as well as plenty more on the AI alignment side (obviously including the famous basilisk). Can you point me to some results from the last 2 decades of his works? Either from him or his institute. That helps to calibrate what his expectation for the AI safety field.

And this was the answer it wrote - I've prefaced each paragraph with "GPT-4>" to indicate the source. It is not fact-checked, and indeed, it has at least one error: The paper GPT-4 claimed to introduce "the concept of Logical Induction" actually introduces "logical induction criterion" and speaks about evaluating algorithms for Logical Induction. Close, but wrong. But overall it is an interesting response - just not a carefully considered one by how we currently would describe logical reasoning, etc.

GPT-4> Eliezer Yudkowsky is a well-known researcher, writer, and advocate for AI safety and rationality. He has contributed significantly to the fields of AI alignment and rational thinking through his work at the Machine Intelligence Research Institute (MIRI), formerly known as the Singularity Institute for Artificial Intelligence (SIAI), and through his writings on LessWrong. Here are some notable outputs from Yudkowsky and MIRI:

GPT-4> 1. Coherent Extrapolated Volition (CEV): Yudkowsky introduced the concept of CEV as a way to describe the ideal values and preferences of humanity that an AI should pursue. The CEV aims to find the values that would emerge if humans had the opportunity to reflect on their goals and beliefs more thoroughly and coherently.

GPT-4> 2. Timeless Decision Theory (TDT): Yudkowsky developed TDT as an alternative to standard decision theories such as Causal Decision Theory (CDT) and Evidential Decision Theory (EDT). TDT aims to better address problems like Newcomb's Problem and counterfactual mugging by considering the logical implications of an agent's decision, rather than just the causal consequences.

GPT-4> 3. Research on Logical Induction: MIRI researchers, including Scott Garrabrant and others, published a paper in 2016 that introduced the concept of logical induction. This work is an attempt to formalize the process of reasoning under logical uncertainty and updating beliefs about mathematical statements.

GPT-4> 4. Yudkowsky's sequence of essays on rationality: Yudkowsky has written extensively on various topics related to rationality, including epistemic rationality, instrumental rationality, and biases. These writings are accessible on LessWrong and have been compiled into the book "Rationality: From AI to Zombies."

GPT-4> 5. AI safety research: MIRI has produced a range of research on AI safety topics, including value alignment, decision theory, and robustness. Much of this work has been foundational in shaping the AI alignment research landscape.

GPT-4> While Yudkowsky's work might not have the same breadth of peer-reviewed publications as some other AI researchers, his contributions have been influential in the AI alignment and rationality communities. His ideas have helped shape the ongoing discussion about AI safety and the development of effective strategies for managing advanced AI systems.