Wrap Up & Looking Forward

Suggested time: 5 min

Just like with fraud detection in Module 2, the key to how the algorithm performs is the data it is given and how it is taught to learn. The algorithm doesn’t know what “successful” is; it can only follow what it is given (or not given) to learn a pattern. The algorithm isn’t aware of the flaws in a limited view of “success” nor does it understand the problematic culture/context that created the data.

To avoid these kinds of problems, we need to ask these questions about data and machine learning moving forward:

  • Who collected the data?
  • How did they collect it?
  • For what purpose?
  • How is it used? By whom?
  • What are its impacts? On whom?
  • What are the known limitations?


Closing Reflection

Hearing a reflection from everyone in a meeting is a great way to round out your understanding of the learning materials and identify ways to improve future meetings. Take a few minutes to write out 1–2 sentence responses to the following questions or take turns answering them out loud:

What is one thing you…

  1. Learned in today’s meeting?
  2. Liked about today’s meeting?
  3. Wish you could have changed about today’s meeting?
  4. Are confused about or want to learn about AI in a future meeting?

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