#AIChat recap (January 2021)


#AIChat is a 10-15 minute monthly Twitter chat. Where my guest(s) or the topics/live-streaming that helps you figure out how artificial intelligence (AI) will impact your life.

Don’t forget to join me for #AIChat on Thursday, February 25th at 2pm ET. My guest? @BlackWomenInAI The topic? What can we do to close the AI skills gap?

This is a bonus issue for those who have subscribed to my “The Three. Le Trois. El Tres” email newsletter (I need to give you something to read during the Super Bowl weekend because we know that Tom Brady and the Bucs are going to win it 🙂

The topic in January was:

There were was no replies but I will give you both sides of the issue (3 points per side). To help you decide whether or not AI is biased. With lots of reference links that gives you a start to help you to do your own research.


  1. It’s us humans who are feeding the AI software that makes it biased
  2. The software is neutral and
  3. There’s not enough data (or the data is faulty) that makes the AI software biased.


  1. All AI software is racist because it’s an experiment in data bias
  2. Algorithms are lazy and look for the easiest way to predict something and ignores the outliers (example: women and people of color) and
  3. Algorithms are developing their unwanted biases by mistake.


  1. —-, “Bias in AI: What it is, Types & Examples, How & Tools to fix it
  2. Cogburn, Ron: “Is AI just as Biased as the Humans Creating It?
  3. Feathers, Todd: “Fake Data Could Help Solve Machine Learning’s Bias Problem—if We Let It
  4. Greene, Tristin: “Stop calling it bias. AI is racist
  5. Hudson, Matthew: “It’s Too Easy to Hide Bias in Deep-Learning Systems
  6. Khalili, Joel: “Artificial intelligence is hopelessly biased – and that’s how it will stay
  7. Nichols, Greg: “Artificial Intelligence in healthcare is racist
  8. Saifee, Moiz: “Can AI Algorithms be Biased?
  9. Socher, Richard: “AI isn’t dangerous, but human bias is.”
  10. Turbot: “AI isn’t biased. We are!

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