On Friday, May 22, 2009, Steve Omohundro spoke at the Bay Area Future Salon at SAP in Palo Alto on:
The Science and Technology of Cooperation
Here’s a pdf file of the slides:
A new science of cooperation is arising out of recent research in biology and economics. Biology once focused on competitive concepts like “Survival of the Fittest” and “Selfish Genes”. More recent work has uncovered powerful forces that drive the evolution of increasing levels of cooperation. In the history of life, molecular hypercycles joined into prokaryotic cells which merged into eukaryotic cells which came together into multi-cellular organisms which formed hives, tribes, and countries. Many believe that a kind of “global brain” is currently emerging. Humanity’s success was due to cooperation on an unprecedented scale. And we could eliminate much waste and human suffering by cooperating even more effectively. Economics once focused on concepts like “Competitive Markets” but more recently has begun to study the interaction of cooperation and competition in complex networks of “co-opetition”. Cooperation between two entities can result if there are synergies in their goals, if they can avoid dysergies, or if one or both of them is compassionate toward the other. Each new level of organization creates structures that foster cooperation at lower levels. Human cooperation arises from Haidt’s 5 moral emotions and Kohlberg’s 6 stages of human moral development.
We can use these scientific insights to design new technologies and business structures that promote cooperation. “Cooperation Engineering” may be applied to both systems that mediate human interaction and to autonomous systems. Incentives and protocols can be designed so that it is in each individual’s interest to act cooperatively.Autonomous systems can be designed with cooperative goals and we can design cooperative social contracts for systems which weren’t necessarily built to be cooperative. To be effective, cooperative social contracts need to be self-stabilizing and self-enforcing. We discuss these criteria in several familiar situations. Cooperative incentive design will help ensure that the smart sensor networks, collaborative decision support, and smart service systems of the eco-cities of the future work together for the greater good.We finally consider cooperation betweenvery advanced intelligent systems. We show that an asymmetry from computational complexity theory provides a theoretical basis for constructing stable peaceful societies and ecosystems. We discuss a variety of computational techniques and pathways to that end.
On March 19, 2009, Steve Omohundro gave a talk at City College of San Francisco on “Evolution, Artificial Intelligence, and the Future of Humanity”. Thanks to Mathew Bailey for organizing the event and to the CCSF philosophy club for filming the talk. It’s available on YouTube in 7 parts:
Evolution, Artificial Intelligence, and the Future of Humanity
by Steve Omohundro, Ph.D.
This is a remarkable time in human history! We are simultaneously in the midst of major breakthroughs in biology, neuroscience, artificial intelligence, evolutionary psychology, nanotechnology and fundamental physics. These breakthroughs are dramatically changing our understanding of ourselves and the nature of human society. In this talk we’ll look back at how we got to where we are and forward to where we’re going. Von Neumann’s analysis of rational economic behavior provides the framework for understanding biological evolution, social evolution, and artificial intelligence. Competition forced creatures to become more rational. This guided their allocation of resources, their models of the world, and the way they chose which actions to take. Cooperative interactions gave evolution a direction and caused organelles to join into eukaryotic cells, cells to join into multi-cellular organisms, and organisms to join into hives, tribes, and countries. Each new level of organization required mechanisms that fostered cooperation at lower levels. Human morality and ethics arose from the relation between the individual and the group. The pressures toward rational economic behavior also apply to technological systems. Because artificial intelligences will be able to modify themselves directly, they will self-improve toward rationality much more quickly than biological organisms. We can shape their future behavior by carefully choosing their utility functions. And by carefully designing a new social contract, we can hope to create a future that supports our most precious human values and leads to a more productive and cooperative society.