Workshop on "Machine learning, human development, and the future of Futures Literacy"

In the midst of a global shift towards AI of most scientific fields including Social and Human Sciences, UNESCO invites thinkers and curious minds to think of deep learning AI systems' limitations when it comes to anticipation.

Futures Literacy, a capability which consists in better using the future to understand the present by revealing our anticipatory assumptions, remains key to addressing and contextualizing the Future of AI.

UNESCO as a pioneering force in the development of Futures Literacy worldwide since 2012 will organise this masterclass at UNESCO Headquarters (Room VIIIbis) on 7 March 2019.

This seminar series is anchored in the dynamics resulting from UNESCO-Routledge joint publication "Transforming the Future: Anticipation in the 21st Century" (2018).

All human action is based on anticipation. How we anticipate the world makes a difference. Dr Ilkka Tuomi's presentation will discuss three qualitatively different ways of anticipating the future, and put these in the context of learning theories, human agency, artificial intelligence research, and Futures Literacy.

Artificial intelligence aims at creating systems that anticipate their environment and act accordingly. Anticipatory systems theory shows that current “deep learning” AI systems—sometimes called “perfect prediction machines”—rely on a very specific form of anticipation. Data-driven machine learning systems can make perfect predictions as long as history repeats itself; creativity, innovation and development, however, require different kinds of anticipation. In the midst of the current AI avalanche, it becomes important to ask how AI contributes to and constrains human agency and development. Dr Tuomi shows that the answer is intimately connected with the types of anticipation that are possible with AI systems, that these connections can be made clear using anticipatory systems theory, and that current developments in machine learning make a “constructivist” approach increasingly important in strategy and policy development. Futures Literacy is needed both for better policy making and for well-informed discussion about the future of artificial intelligence.

Dr. Tuomi is the Founder and Chief Scientist at Meaning Processing, an independent public research organization located in Helsinki, Finland. He is an internationally known expert in organizational learning, organizational cognition, technology-enabled learning, innovation research, and anticipatory systems theory. He has written five books, chapters in 25 books, over 60 scientific articles, and numerous scientific reports.

His recent work has focused on the intersection of new models for foresight, innovation theory, the mathematics of anticipatory systems and cognition, and the social, economic, and cultural impact of artificial intelligence. His recent publications include Vygotsky meets backpropagation: Artificial neural models and the development of higher forms of thought (AIED 2018); The Impact of Artificial Intelligence on Learning, Teaching and Education: Policies for the Future (European Commission, 2018); Chronotopes of foresight: Models of time-space in probabilistic, possibilistic, and constructivist futures (Futures and Foresight Science, 2019); and Ethics and Choice in Anticipatory Systems (Anticipation 2019, with A.H. Louie).