Keynote Abstract: Ever since Gartner’s identified gamification as an emergent technology in its Hype Cycle report in 2011, many bold predictions about this technology were made. Gamification took the industries by a whirlwind. Venture capitalists, startups, and large enterprises are all jumping on this simple elegant framework that can drive individual behavior changes at a scale and speed that could change the world.

Today, more than 10 years later, none of the predictions were realized. Gamification is no longer on the Hype Cycle, and it’s subsumed into other disciplines, such as user experience, product design, and software development. Join me to explore what’s the missing key and how you can make a difference and fulfill the promise and potential of gamification.

Dr. Michael Wu is one of the world’s premier authorities on artificial intelligence (AI), machine learning (ML), data science, and behavioral economics. He’s currently the Chief AI Strategist at PROS (NYSE: PRO), an AI-powered SaaS provider that helps companies monetize more efficiently in the digital economy. He’s been appointed as a Senior Research Fellow at the Ecole des Ponts Business School for his work in Data Science, and he serves as an advisor and a lecturer for UC Berkeley Extension’s AI programs.

Prior to PROS, Michael was the Chief Scientist at Lithium for a decade, where he focuses on developing predictive and prescriptive algorithms to extract insights from social media big data. His research spans many areas, including customer experience, CRM, online influence, gamification, digital transformation, AI, etc. His R&D won him the recognition as an Influential Leader by CRM Magazine along with Mark Zuckerberg, Marc Benioff and other industry giants.

Michael has served as a DOE fellow at the Los Alamos National Lab conducting research in face recognition and was awarded 4 years of full fellowship under the Computational Science Graduate Fellowship. Prior to industry, Michael received his triple major undergraduate degree in Applied Math, Physics, and Molecular & Cell Biology; and his Ph.D. from UC Berkeley’s Biophysics program, where he uses machine learning to model visual processing within the human brain. Michael believes in knowledge dissemination, and speaks internationally at universities, conferences, and enterprises. His insights have inspired many global enterprises and are made accessible through “The Science of Social,” and “The Science of Social 2”—two easy-reading e-books.