[community] Registration for Digging DEEPer webinar on Machine Learning Discrimination

[Gloria Bernal Gomez]

Please accept our apologies for message duplications from cross-posting this announcement.

[Digging DEEPer Webinar. Machine Learning Discrimination: Bias in, bias out. Special guest speaker; Dr. Toon Calders (University of Antwerp). Register for free. Wednesday July 8, 11AM -12PM EDT. wecount.inclusivedesign.ca]

We are excited to announce the start of the Digging DEEPer series, hosted by the Inclusive Design Research Centre and made possible by We Count, a project created with a vision for a fair data ecosystem that serves diversity through opportunities and outcomes.

The We Count – Digging DEEPer series will be a variety of activities and events that will allow us to learn, collaborate, co-design and share with a focus on increasing the participation of the Canadian disability community throughout the data ecosystem. Industry experts and leaders from diverse communities will be joining us to discuss inclusion and accessibility in data science, artificial intelligence and machine learning as well as AI ethics and fairness.

To start off this special series, guest speaker Dr. Toon Calders will be joining us for a webinar on Machine Learning Discrimination: Bias In, Bias Out on Wednesday, July 8, at 11am EDT. This event has limited capacity. To secure your spot, please register through the following link: https://ocadu.zoom.us/webinar/register/WN_VDYRizSrRXOP5SS8ckCUsQ.


Webinar Description: Artificial intelligence is increasingly 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 can 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?


Toon Calders is a professor in the computer science department of the University of Antwerp, Belgium. He is an active researcher in the area of data mining and machine learning. Dr. Calders was one of the first researchers to study how to measure and avoid algorithmic bias in machine learning and is one of the editors of the book Discrimination and Privacy in the Information Society: Data Mining and Profiling in Large Databases (Springer, 2013).

We look forward to you joining us!

Sincerely,

The We Count Team

[We Count Logo]<https://wecount.inclusivedesign.ca/>[Inclusive Design Research Centre]<https://idrc.ocadu.ca/>[DEEP 2020 Designign Enabling Economies and Policies]<https://deep.idrc.ocadu.ca/>

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