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AI & Society

Workshop: Prototyping Models

Background

The evaluation of performance of machine learning models has historically been done on the basis of rather narrow technical criteria. Arguments have been made to expand the scope of such evaluations to include a wider range of metrics, including ethical ones (e.g. Mitchell et al., 2019). 

Learning Objectives

By completing this activity you will have learned how to analyse the risks related to a hypothetical machine learning model for an envisioned public AI system. 

Instructions

  1. Use the model that you imagine would be at the core of your envisioned design
  2. Take the attached canvas and put it on your Miro board
  3. Go over the various sections and discuss potential answers to the questions
  4. For each answer, add at least 1 post-it note
  5. If you can’t answer the question right now, answer it as a hypothesis instead, and make a note of what you need to do to get the answer you need

Product

The end-result of this activity is a filled-out canvas on your miro board. 

Follow-up

We will use the questions and issues you have identified by doing this exercise as the starting point for the plenary discussion later in the day.

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