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Conference Date 29-30 Dec. 2018
First Round Submission 20 Oct. 2018
Second Round Submission 20 Nov. 2018
Registration Date 20 Dec. 2018
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Dr. David Ing

Dr. David Ing is a Cofounder and Research Scientist with the Trito Innovation Colab, centered in Toronto, Canada. In recent years, he has been teaching at Tongji University, University of Toronto, OCAD University, and Aalto University. He is an IBM alumnus of 28 years, following assignments in roles including management consulting, industry solutions and market development. He is a past-president of the International Society for the Systems Sciences. An active blogger, his writing and presentations can be found at

Speech Title: Innovation Learning for Sustainability: What is smarter for urban systems?

Abstract: Sustainability has been generally recognized since the Brundtland Commission in the 1980s.  Circa 2005, the nature of innovation for the 21st century was seen as changing to become "open, collaborative, multidisciplinary and global".  Smarter cities respond to the previously unobservable becoming observable, with the world becoming "instrumented, interconnected and intelligent".
For urban systems, sustainability can be portrayed as an "innovation".  In which ways should Innovation Learning be approached as a normative challenge in smart cities?  In unobservable, unconnected and dumb (unresponsive) cities, the infrastructure is static and fixed, so that the onus is all on people to adjust their behaviours.  In a paradigm of co-responsive movement, a smart city would not only adapt to people, but would also learn for future concordances.
Innovation learning is proposed with three theories:  (i) enskilling attentionality (rather than deskilling through automation); (ii) weaving flows and transforming materials in form-giving; and (iii) agencing strands as (life)lines alongside each other.
These theories are proposed as useful in situations or circumstances under which understanding and prediction is difficult, e.g. the rise of Internet-of-Things devices in urban systems, or the embedding of artificial intelligence software in augmenting and/or automating human capabilities.  The theories were developed in a 2018 book, "Open Innovation Learning: Theory building on open sourcing while private sourcing".

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