Webinar details:

Tuesday, November 30, 2021
4:00 PM – 5:00 PM

From the description:

While AI has had tremendous impacts in many ways, it has also had unintended consequences that have disproportionately impacted marginalized populations, including students of color, those living in poverty, and those with learning disabilities. What do educators need to know about AI to leverage its potential and make sure it works effectively and without bias for unserved, underrepresented students?


In this edWebinar, we will:

  • Define AI, so we are all speaking the same language
  • Learn to identify the ways in which existing equity issues in education can be amplified by the EdTech products we use
  • Dive into best practices for mitigating AI bias by focusing on case studies
  • Unveil new Digital Promise product certification for prioritizing racial equity in AI
  • Discuss how we might identify new opportunities in AI that champion the needs of our most marginalized learners
  • This edWebinar will be of interest to teachers, librarians, school and district leaders, and educational technology leaders of all grade levels.
  • There will be time for questions at the end of the presentation.

Why attend?

Educational technology products that use AI and machine learning can compound existing biases and introduce new ones through assumptions baked into algorithms. Did you notice this during the pandemic? I did. I was trying to help a staff member with using virtual backgrounds in Webex Meetings. When I Google-searched for troubleshooting methods, I found this now-famous Twitter thread that paralleled the problem we were facing (click through and click on the images to see what is happening and how Twitter’s own image display algorithm replicates and compounds the problem from Zoom).

Similarly, remote proctoring technologies have potential baked-in algorithmic bias that has disproportionate impact on students of color, those living in poverty, and those with learning disabilities.

Are the technologies we choose to use for teaching and learning free from similar baked-in biases? I’ll be attending this webinar to learn more. If you’d like to attend as well, I invite you to let me know. Perhaps we can compare notes or even share a Google Doc and take notes together!

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