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Explore how licensing frameworks can determine whether artificial intelligence systems create widespread benefit or concentrated harm in this comprehensive seminar. Discover why the contractual layer through which AI enters society represents an overlooked yet essential domain of AI governance that shapes systemic outcomes at scale. Learn how seemingly mundane licensing decisions can determine whether automation gains circulate broadly or concentrate among few, whether personal data receives protection or faces harvesting, and whether scientific knowledge can self-organize or remains locked behind commercial barriers. Examine how complexity research principles apply to socio-economic systems, where interaction rules encoded in contracts shape outcomes more than inherent system qualities. Understand why current licensing templates funnel diverse AI technologies into outdated economic models, often wasting their transformative potential. Investigate how new approaches to license design can steer automation toward inclusion, sustainability, and collective benefit without altering underlying technical capabilities. Analyze real-world scenarios demonstrating how AI systems with identical beneficial capabilities could produce vastly different societal impacts based solely on their licensing terms. Study the AI Commons License Suite as a modular framework for impact-oriented governance that addresses value flows, responsibilities, and power relations. Gain insights from Dr. Em Lenartowicz's research on humanistic management, social ontology, and complexity studies as applied to collective intelligence systems. Consider licensing as a creative design space where long-term societal impacts of artificial intelligence can be intentionally shaped rather than left to chance.
