Welcome to the resources for my talk on Ethics in AI for the Paul English Applied Artificial Intelligence Institute. The talk took place on September 20, 2024 at 11:30am. The recording of the talk is available here; use passcode H%Z=e4.w

Click here for the Ethical Ad Libs exercise.

Click here for the 9.3.1 Methodology explanation and example. Junkyard (Mac); another option is mind mapping software from Google, also free and not system-specific.

Click here to access my copy of IDEO’s Ethics Cards for AI designers, or sign up to get your own.

Click here to access the IBM IBM Fairness 360 tool,  and here for the Google WhatIf Tool (less technical knowledge required).

Use the Zoom chat, Teams channel, or email (potasznik@cs.umb.edu) to network and find a team to participate in the AI contest, Hackathon, and/or Symposium!

Honorable mentions for further reading (more on the tech side):

SHAP (SHapley Additive exPlanations) is a game theoretic approach to explain the output of any machine learning model.

Local Interpretable Model-Agnostic Explanations (LIME) is a technique that approximates any black box machine learning model with a local, interpretable model to explain each individual prediction.

Alibi is an open source Python library aimed at machine learning model inspection and interpretation. The initial focus on the library is on black-box, instance based model explanations.

I hope you can also join a talk with a panel of Oracle employees about Ethical AI at that company: Monday, September 23 at 12:00pm. All are welcome! See Teams channel for invite link.