Oct. 11-12, 2017.
OCAD University, 100 McCaul St., Toronto, Ontario, CANADA
This year at DEEP 2017:
Learning to Support and Understand Diversity & Complexity
“Let’s not teach our machines our stereotypes & presumptions.”
More and more decisions are being delegated to machines, whether to authorize access, recognize illnesses, predict risks, determine loan and credit worthiness, academic potential, future employment performance or a multitude of other functions. This trend has the potential to amplify existing inequities.
Whether we welcome or fear machine intelligence, it is important that we attend to what we teach machines. Do our machines understand and serve individuals that are different or fail to recognize and ignore anyone that does not conform to the model of an average human?
In understanding how bias against outliers is detrimental to machine-learning we gain insights into how our human stereotypes are embedded in our traditional research and public policies, and damage our society.
Topics at DEEP 2017
Discussions will centre around four areas:
- Government Accessible ICT Procurement Policies—recommendations for federal accessible procurement policies will be shared and discussed. Participants will be able to provide input and respond to the final recommendations.
- Cognitive Access & Learning Differences – an area that is not well developed in accessibility legislation and services is the area of cognitive access, yet it is the most prevalent experience of disability. There is a call for Canada to take bold steps in this issue. Participants will help to establish a bold plan.
- Machine Learning—participants will delve into the challenge of teaching machines and automated systems to recognize and adapt to diversity rather than rely on flawed models of “average humans” that perpetuate social, political, and economic biases.
- Co-operative Platforms—participants will step through development of a cooperative platform and consider social implications, privacy implications, inclusion aspects and potential barriers.
Each group will be working toward concrete policies, inclusion models or recommendations for inclusion that will be published and shared openly under Creative Commons licensing.
In the tradition begun in 2012, this event to plan meaningful change will bring together a diversity of fresh perspectives, new ideas, together with seasoned experience, and insight gained from failures and successes. DEEP participants know that digital inclusion is necessary and urgent. We don’t need to persuade each other of the “why”. This allows us to focus our time together during the think tank on the “how”? We will spend our collective time and talents to design strategies, plans, collaborative projects, cross-sector initiatives and new disruptive ways to foster more inclusive prosperity, privacy, and life-long learning.
Events at DEEP 2017
In cooperation with BIG IDeA
“Start Your Machine Learning Engines and Race to the Edge”
Machine learning leaders (including IBM, Microsoft, Google, Amazon and QNX) will be challenged to address scenarios and problems that are not typical or average. Students at more than 8 universities and colleges will create test scenarios and success criteria.
Which AI system can effectively understand and serve: someone who needs to navigate with unique a mobility device, someone who has unusual assets, an applicant with a non-typical employment history, someone seeking a highly specialized product, or other minority needs.
Like all inclusive design, designing for the edge benefits everyone. An AI system that understands and is trained to serve diversity will be better at adapting, predicting and staying relevant. More importantly it will not amplify inequities.