Fairness in AI

Main challenges and how to tackle them

In partnership with Data Science for Social Good Portugal, we are launching a series of webinars in AI topics related to social good. The second talk was by Francisca Morgado, on the 29th of July, with the topic “Fairness in AI”. In case you weren’t able to register in time or attend the talk, it is available on the link below. Check our previous talk on Geospatial Machine Learning if you missed it.

Talk abstract:

Fairness is an abstract concept that has been changing throughout the ages. Our history shows us countless unfair events that have influenced human behavior and cultures but did we transmit these behaviors to technology?
In this Talk we will discuss the concept of Fairness in AI systems. “What is Fairness and how can it be measured?”, “How can algorithms be unfair?”, “What kind of bias may be present in the datasets?”, and “How to avoid unfair decisions?” are some of the questions that will be answered in this session, along with some practical examples.

Course, Templates

Data Ignite

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Slides are available here.

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