Learning from biological and social systems for designing beneficial AI

Principles of Intelligent Behavior in Biological and Social Systems (PIBBSS) aims to facilitate research studying parallels between intelligent behavior in natural and artificial systems, and to leverage these insights towards the goal of building safe and aligned AI.

We are happy to announce that we are running the 2nd iteration of the PIBBSS Summer Research Fellowship for Summer 2023. Learn more here!

We also run a speaker series and thematic research workshops, publish our research, and always look for other ways to support research and training in this space. If you're excited about our mission and want to get involved (in whatever capacity), fill in this ‘expression of interest’ form.

PIBBSS Summer Research Fellowship 2023 brings together researchers studying complex and intelligent behavior in natural and social systems.


Future of Artificial Intelligence

We are dedicated to prioritizing and fostering careful, value-sensitive, and epistemically diverse approaches toward the design and implementation of artificial intelligent systems.

Humanity is making fast progress in its ability to engineer sophisticated forms of complex and intelligent behaviors in artificial systems. Such systems will have an increasingly dominating effect over the future course of our civilization.

This progress could unlock immense positive potential, but it could also lead to irreversible, harmful effects. Thus, research in AI alignment aspires to contribute to preserving and fostering human potential. You can learn more about AI alignment by consulting the resources outlined here.

 

Intelligence in Biological and Social Systems

Insofar as AI research is interested in mechanisms that can search and instantiate complex behaviors, the study of complex natural and social systems can inform the design of artificial behaviors.

Throughout the history of science, we observed that a wide variety of complex and intelligent systems exhibit similar properties. Such cross-system phenomena include adaptation, robustness, goal-directed behavior, learning, embeddedness, modularity, phase transitions, and more.

In understanding the mechanisms that give rise to these phenomena and the role they play in defining the functionality of such systems, we seek to improve our ability to develop artificial systems that reliably depict desired properties.

PIBBSS targets a diverse selection of domains that have the potential to help advance key bottlenecks in designing safe and aligned artificial intelligent systems.

The fellowship is focused on domains with a rich repertoire of tools and insights about complex behavior found in natural and social systems.

These are fields such as ecology, evolutionary biology, cognitive science, neuroscience, sociology, legal theory, political economy, statistical mechanics, linguistics, media studies, and more.

 We are proud to partner with the Center for Theoretical Study, and the Stanford Existential Risks Initiative to make this fellowship possible.