Thanks for visiting!

This project aims to improve our understanding of the likely impacts of human-level artificial intelligence.

The intended audience includes researchers doing work related to artificial intelligence, philanthropists involved in funding research related to artificial intelligence, and policy-makers whose decisions may be influenced by their expectations about artificial intelligence.

The focus is particularly on the long-term impacts of sophisticated artificial intelligence. Although human-level AI may be far in the future, there are a number of important questions which we can try to address today and may have implications for contemporary decisions. For example:

  • What should we believe about timelines for AI development?
  • How rapid is the development of AI likely to be near human-level? How much advance notice should we expect to have of disruptive change?
  • What are the likely economic impacts of human-level AI?
  • Which paths to AI should be considered plausible or likely?
  • Will human-level AI tend to pursue particular goals, and if so what kinds of goals?
  • Can we say anything meaningful about the impact of contemporary choices on long-term outcomes?

Today, public discussion on these issues appears to be highly fragmented and of limited credibility. More credible and clearly communicated views on these issues might help improve estimates of the social returns to AI investment, identify neglected research areas, improve policy, or productively channel public interest in AI.

The goal of the project is to clearly present and organize the considerations which inform contemporary views on these and related issues, to identify and explore disagreements, and to assemble whatever empirical evidence is relevant.

The project is provisionally organized as a collection of posts concerning particular issues or bodies of evidence, describing what is known and attempting to synthesize a reasonable view in light of available evidence. These posts are intended to be continuously revised in light of outstanding disagreements and to make explicit reference to those disagreements.

AI Impacts contributors

Katja Grace

Katja runs AI Impacts. She started doing this because she wanted to know what would happen with AI, and thought other people might too. She continues because she thinks it’s one of the most important research projects at the moment. Her background is in philosophy, economics, and human ecology, with particular interests in anthropic reasoning, artificial intelligence risk, and game theory. She blogs at


Michael Wulfsohn

Michael is a Fellow of the Actuaries Institute in Australia (FIAA) and holds a master’s degree in International and Development Economics. Michael has previously worked as an investment analyst for a consulting firm, a researcher for a development policy think-tank, an economist at a developing country central bank, and a consultant to multilateral development banks. Michael’s research interests include regional and global integration, global public goods, and global catastrophes.


Finan Adamson

Finan Adamson helps organize Seattle EA. He studied Evolutionary biology at The Evergreen State College.




Connor Flexman

Connor is a recent graduate in mathematical physics from Brown University and a researcher at the Democracy Defense Fund. He is especially interested in forecasting and the long-term future of technology.




Justis Mills

Justis Mills studied Philosophy at New College of Florida. His main interests are Effective Altruism, Homestuck, Super Smash Bros, and writing fiction. You can find some of the last of these, and other miscellanea, here.




Jimmy Rintjema

Jimmy Rintjema is a freelance contractor who specializes in providing support for startups and small companies. He is especially interested in helping organizations that study Existential Risk and Artificial Intelligence safety. When he is not glued to his computer, Jimmy enjoys playing soccer and car camping. He resides in Ontario, Canada.



Past contributors

Paul Christiano

John Salvatier

Ben Hoffman

Stephanie Zolayvar




This research was supported as part of the Future of Life Institute FLI-RFP-AI1 program, grant # 2015-143901 (5388).