Abstract: This talk will sketch an alternate paradigm to mainstream AI practice, one that broadens the focus beyond optimizing algorithms considered in isolation to designing processes of human-algorithm collaboration. The envisioned practice would harness human and machine complementarities to develop systems of human-machine collective intelligence. Such systems integrate the best capabilities of both machine intelligence and human users while mitigating the deficits of each. Such a practical field requires a conceptual foundation that integrates concepts and methods from the humanities and social sciences with those of the statistical and computational sciences. The proposed approach differs from, but complements, recent calls to foster responsible computing research and “operationalize ethics” in industry.