David Manheim

Numerous books, articles, and blog posts have laid out reasons to think that AI might pose catastrophic or existential risks for the future of humanity. However, these reasons often differ from each other both in details and in main conceptual arguments, and other researchers have questioned or disputed many of the key assumptions and arguments. The disputes and associated discussions can often become quite long and complex, and they can involve many different arguments, counter-arguments, sub-arguments, implicit assumptions, and references to other discussions or debated positions. Many of the relevant debates and hypotheses are also subtly related to each other. Two years ago, Ben Cottier and Rohin Shah created a hypothesis map, shown below, which provided a useful starting point for untangling and clarifying some of these interrelated hypotheses and disputes. The MTAIR project is an attempt to build on this earlier work by including additional hypotheses, debates, and uncertainties, and by including more recent research. We are also attempting to convert Cottier and Shah’s informal diagram style into a quantitative model that can incorporate explicit probability estimates, measures of uncertainty, relevant data, and other quantitative factors or analysis, in a way that might be useful for planning or decision-making purposes. Cottier and Shah's 2019 Hypothesis Map for AI Alignment This post is the first in a series which presents our preliminary outputs from this project, along with some of our plans going forward. Although the project is still a work in progress, we believe that we are now at a stage where we can productively engage the community, both to contribute to the relevant discourse and to solicit feedback, critiques, and suggestions. This introductory post gives a brief conceptual overview of our approach and a high-level walkthrough of the hypothesis map that we have developed. Subsequent posts will go into much more detail on different parts of