Advanced human-AI collaboration

Teaching AI about social intelligence

Current AI is a good tool but a poor teammate because of its lack of human understanding.

That is why the research and development arm of the U.S. Department of Defense, the Defense Advanced Research Projects Agency (DARPA), is exploring new ways to build social skills in AI systems that would allow humans and machines to work effectively together.

Clues on how to create machines with social intelligence have been found in an unexpected place: the popular video game Minecraft.

ASU researchers teamed up with Aptima — a company that develops solutions to optimize and improve human performance in mission-critical, technology-intensive settings — during a four-year program funded by DARPA called Artificial Social Intelligence for Successful Teams, or ASIST. The project aims to improve the social intelligence of artificial intelligence and make it better able to assist teams of humans working in complex environments, including national security missions.

Researchers from GSI’s Center for Human, Artificial Intelligence, and Robot Teaming (CHART)generated data from 1,160 Minecraft games, which represents the largest publicly available human-AI team research dataset in history.

CHART is at the forefront of a new science of human, AI and robot teaming. It synthesizes research across computer science, robotics, law, art and social science to revolutionize how we ensure national security through human-machine teaming.

While team research is statistically underpowered because it is hard to schedule and convene participants at the same time, CHART found innovative ways of recruiting participants by hosting Minecraft competitions and virtual hackathons and giving awards to high performers.

More than 200 participants — including representatives from the Massachusetts Institute of Technology, Cornell, the University of Southern California and Carnegie Mellon University — played a role in the ASIST research. ASIST is one component of a broader DARPA initiative called AI Forward, which is taking a deep look at how to reliably build trustworthy AI systems by examining AI theory, AI engineering and human-AI teaming.