FLI Artificial Superintelligence Project

by | 1 July 2015

I am writing to announce that GCRI has received a grant from the Future of Life Institute, with funding provided by Elon Musk and the Open Philanthropy Project. The official announcement is here and the full list of awardees is here.

GCRI’s project team includes Tony Barrett, Roman Yampolskiy, and myself. Here is the project title and summary:

Evaluation of Safe Development Pathways for Artificial Superintelligence

Some experts believe that computers could eventually become a lot smarter than humans are. They call it artificial superintelligence, or ASI. If people build ASI, it could be either very good or very bad for humanity. However, ASI is not well understood, which makes it difficult for people to act to enable good ASI and avoid bad ASI. Our project studies the ways that people could build ASI in order to help people act in better ways. We will model the different steps that need to occur for people to build ASI. We will estimate how likely it is that these steps will occur, and when they might occur. We will also model the actions people can take, and we will calculate how much the actions will help. For example, governments may be able to require that ASI researchers build in safety measures. Our models will include both the government action and the ASI safety measures, to learn about how well it all works. This project is an important step towards making sure that humanity avoids bad ASI and, if it wishes, creates good ASI.

Author

Recent Publications

Climate Change, Uncertainty, and Global Catastrophic Risk

Climate Change, Uncertainty, and Global Catastrophic Risk

Is climate change a global catastrophic risk? This paper, published in the journal Futures, addresses the question by examining the definition of global catastrophic risk and by comparing climate change to another severe global risk, nuclear winter. The paper concludes that yes, climate change is a global catastrophic risk, and potentially a significant one.

Assessing the Risk of Takeover Catastrophe from Large Language Models

Assessing the Risk of Takeover Catastrophe from Large Language Models

For over 50 years, experts have worried about the risk of AI taking over the world and killing everyone. The concern had always been about hypothetical future AI systems—until recent LLMs emerged. This paper, published in the journal Risk Analysis, assesses how close LLMs are to having the capabilities needed to cause takeover catastrophe.

On the Intrinsic Value of Diversity

On the Intrinsic Value of Diversity

Diversity is a major ethics concept, but it is remarkably understudied. This paper, published in the journal Inquiry, presents a foundational study of the ethics of diversity. It adapts ideas about biodiversity and sociodiversity to the overall category of diversity. It also presents three new thought experiments, with implications for AI ethics.

Climate Change, Uncertainty, and Global Catastrophic Risk

Climate Change, Uncertainty, and Global Catastrophic Risk

Is climate change a global catastrophic risk? This paper, published in the journal Futures, addresses the question by examining the definition of global catastrophic risk and by comparing climate change to another severe global risk, nuclear winter. The paper concludes that yes, climate change is a global catastrophic risk, and potentially a significant one.

Assessing the Risk of Takeover Catastrophe from Large Language Models

Assessing the Risk of Takeover Catastrophe from Large Language Models

For over 50 years, experts have worried about the risk of AI taking over the world and killing everyone. The concern had always been about hypothetical future AI systems—until recent LLMs emerged. This paper, published in the journal Risk Analysis, assesses how close LLMs are to having the capabilities needed to cause takeover catastrophe.

On the Intrinsic Value of Diversity

On the Intrinsic Value of Diversity

Diversity is a major ethics concept, but it is remarkably understudied. This paper, published in the journal Inquiry, presents a foundational study of the ethics of diversity. It adapts ideas about biodiversity and sociodiversity to the overall category of diversity. It also presents three new thought experiments, with implications for AI ethics.