We Count has a lot of things on the go. You can learn and co-create with us and earn micro-badges to show your effort. Here are some of our upcoming and ongoing learning activities.
All We Count/Digging DEEPer workshops and webinars are accessible, free and open to the public. We welcome people from all backgrounds and experience levels.
Don’t miss out on We Count events, sign up to the mailing list.
2020 We Count, Future of Work & Digging DEEPer Events
AI-Powered Mobile Assistive Technology Apps Risks and Benefits
Work Groups from the AI-Powered Mobile Assistive Technology Apps: Risks and Benefits workshop will discuss their findings with guest speaker Dr. Roger Melko as a further exploration of assistive technologies and artificial intelligence.
October 21, 2020, 10:30 AM – 12 PM Register for Free
Documentary Screening: Coded Bias (To be confirmed)
CODED BIAS explores the fallout of MIT media lab researcher Joy Buolamwini’s startling discovery that facial recognition does not see dark-skinned faces accurately, and her journey to push for the first-ever legislation in the U.S. to govern against bias in the algorithms that impact us all. https://www.codedbias.com/about
October 29, 2020, 6:30 PM – 8:30 PM
Risks and Opportunities of AI, Smart Systems and Automation for Employment of Persons with Disabilities
Panelist will give an introduction to AI and Machine Learning with a focus on concerns for persons with disabilities and employment.
November 3, 2020, 1:30 PM – 3 PM
Introduction to Coding to Learn and Create Project
Learn how Coding to Learn and Create is working to empower all learners to be creators of their digital worlds, to express themselves using code and art, and to apply these skills to other areas of learning and daily life. Not just learning to code, but coding to learn and create. https://www.codelearncreate.org/
November 10, 2020, 2 PM – 3 PM
Identifying and Addressing Bias in Machine Learning Models on Selection of Candidates from a Policy Perspective
The panelists will discuss how machine learning models can carry bias on selecting candidates, affecting persons with disabilities and other individual differences.
November 17, 2020, 1:30 PM – 3 PM
Coding to Learn and Create Workshop
Join us for a co-design activity that focuses on coding education approaches.
November 24, 2020, 2 PM – 3 PM
How to Make Artificial Intelligence Inclusive for Hiring and HR
Panelists will highlight some of the potential problems that arise from AI in the hiring process and brainstorm ideas to make this process more inclusive for persons with disabilities.
December 1, 2020, 1:30 PM – 3 PM
The Future Imaginary: Strategies for Building Indigenous Possibilities
Join us for a presentation from Jason Lewis
December 9, 2020, 10:30 AM – 12:00 PM
Discussion: The Metric Society and Surveillance
Join us for a discussion with author, Steffan Mau and other panelists.
AI-Powered Mobile Assistive Technology Apps
Artificial intelligence is rapidly advancing to think like us and to deep dream through machine learning. How can we leverage this technology to improve accessibility, and at the same time, keep up with the ramifications? Inspired by Dr. Roger Melko’s CBC podcast, this three-part workshop will explore and dig deeper into the possibilities of AI-powered assistive technology mobile apps.
Webinar - Conversation with Dr. Roger Melko. We Count Learners will discuss their findings with guest speaker Dr. Roger Melko and others as a further exploration of the topic.
Wednesday, October 21 at 10:30 AM – 12:00 PM (EDT)
Accessible Survey Platforms
A Conversation on Accessible Survey Platforms, hosted by the Inclusive Design Research Centre.
The recording of the webinar will be available soon.
Machine Learning: Bias In, Bias Out
Featuring: Dr. Toon Calders
(University of Antwerp)
Artificial intelligence is more and more responsible for decisions that have a huge impact on our lives. But predictions made using data mining and algorithms can affect population subgroups differently. Academic researchers and journalists have shown that decisions taken by predictive algorithms sometimes lead to biased outcomes, reproducing inequalities already present in society. Is it possible to make a fairness-aware data mining process? Are algorithms biased because people are too? Or is it how machine learning works at the most fundamental level?
Dr. Toon Calders, specialist in Machine Learning from the Department of Computer Science, in the Faculty of Science at the University of Antwerp, Belgium, provides an introduction to machine learning bias through his Digging DEEPer webinar.
Earn Badges from this webinar