The Cooperative AI Foundation (CAIF) is hiring a Chief Operating Officer, a role that will be critical for the scaling and smooth running of the foundation, both now and in the years to come. We believe this marks an exciting opportunity to have a particularly large impact on the growth of this nascent field and organisation, and thus on the benefits to humanity that it prioritises. Applications will close at 23:59 UTC on 10 July 2022.
Learn moreCall for Proposals
CAIF is seeking proposals for work to improve our ability to evaluate cooperation-relevant features of AI systems. Examples of such work include theoretical contributions on how to define and measure key Cooperative AI concepts, and practical contributions such as benchmark environments and datasets. Anyone is eligible to apply, and we welcome applications from disciplines outside of computer science.
Learn moreCall for Proposals
CAIF is hosting a fortnightly seminar series on New Directions in Cooperative AI, in which we invite leading thinkers to offer their vision for research on cooperative AI. Unlike typical academic talks, these seminars are explicitly agenda-setting, describing a line of work that many researchers could pursue and that CAIF could support. We are currently accepting proposals for new talks.
Learn moreGrant
CAIF is pleased to announce that its first major grant, of $500,000, will be to support the Foundations of Cooperative AI Lab (FOCAL) at Carnegie Mellon University (CMU), led by Prof. Vincent Conitzer. Another $3 million will be provided by the Center on Emerging Risk Research. FOCAL’s goal is to create foundations of game theory appropriate for advanced, autonomous AI agents – with a focus on achieving cooperation. Prospective PhD students interested in working at the lab are encouraged to apply for a PhD program at CMU's Computer Science Department.
Learn moreGrant
CAIF will also be granting £200,000 in order to support the work of Dr. Christian Schroeder de Witt, who will join Associate Prof. Jakob Foerster’s new lab on multi-agent learning at the University of Oxford. Schroeder de Witt’s work focuses mainly on deep multi-agent reinforcement learning and human-AI interaction, though he is also spearheading interdisciplinary research on the intersection of agent-based modeling, probabilistic inference, and climate policy. Prospective PhD students interested in working at the lab are encouraged to apply to both the Engineering Department and the AIMS CDT at Oxford.
Learn moreDate
Seminar Title
Speakers
15:00-16:30 UTC 19 May 2022
Wolfram Barfuss (University of Tübingen, Princeton University)
Collective Cooperative Intelligence
16:00-17:30 UTC 6 May 2022
Gillian Hadfield (Schwartz Reisman Institute for Technology and Society, University of Toronto)
The Foundations of Cooperative Intelligence
16:00-17:30 UTC 28 April 2022
Dorsa Sadigh (Stanford University)
What Makes Human Data Special? How to Learn from Humans, Teach Them, and Help Them Better Teach Us
15:00-16:30 UTC 22 April 2022
Edward Hughes (DeepMind)
Cultural Evolution as a Cooperative AI Generating Algorithm
13:00-14:00 UTC 10 March 2022
Jesse Clifton (Center on Long-Term Risk, CAIF, NCSU)
Sammy Martin (KCL, Center on Long-Term Risk)
Differential Progress in Cooperative AI: Motivation and Measurement
15:00-16:00 UTC 17 February 2022
Joel Leibo (DeepMind)
How to Measure and Train the Social-Cognitive Capacities, Representations, and Motivations Underlying Cooperation
15:00-16:00 UTC 20 January 2022
Vincent Conitzer (Duke University, University of Oxford)
AI Agents May Cooperate Better if They Don’t Resemble Us
Sign up to our mailing list to stay informed about upcoming events