Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Modelling Transformative AI Risks (MTAIR) Project: Introduction, published by David Manheim, Aryeh Englander on the AI Alignment Forum. 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 this model. We are primarily interested in feedback on the portions of the model that we are presenting in detail. In the final posts of this sequence we will describe some of our plans going forward. Conceptual Approach There are two primary parts to the MTAIR project. The first part, which is still ongoing, involves creating a qualitative map (“model”) of key hypotheses, cruxes, and relationships, as described earlier. The second part, which is still largely in the planning phase, is to convert our qualitative map into a quantitative model with elicited values from experts, in a way that can be useful for decision-making purposes. Mapping key hypotheses: As mentioned above, this part of the project involves an ongoing effort to map out the key hypotheses and debate cruxes relevant to risks from Transformative AI, in a manner comparable to and building upon the earlier diagram by Ben Cottier and Rohin Shah. As shown in the conceptual diagram below, the idea is to create a qualitative map showing how the various disagreements and hypotheses (blue nodes) are related to each other, how different proposed technical or governance agendas (green nodes) relate to different disagreements and hypotheses, and how all of those factors feed into the likelihood that different catastrophe scenarios (red nodes) might materialize. Qualitative map illustrating relationships between hypotheses, propositions, safety agendas, and outcomes Quantification and decision analysis: Our longer-term plan is to convert our hypothesis map into a quantitative model that can be used to calculate decision-relevant probability estimates. For example, a completed model could output a roughly estimated probabili...