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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. is currently largely written and maintained by Katja Grace and John Salvatier, with the help of many others.

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