Algorithms in the Real World

Overview

In this module, students explore barriers to applying comparison-based algorithms in the real world: incommensurable values, imperfect proxy measures, and problems with idealization and abstraction. Students also consider threats faced by people whose personal information might be included in or excluded from the data their algorithms operate on. One version of the lecture uses shortest path algorithms as a running example; an alternative version uses sorting as the example. The associated homework problems are compiled from several different problem sets across multiple versions of the course. Each of these problems includes at least a subpart that asks students to consider what other values might be at stake in the problem, how these values should be measured or approximated, how the collection of the relevant data might impact the people involved, or how idealization and abstraction in problem formulation might lead to real-world harms.

Contributors

  • Ethics materials by Kathleen Creel, Benjamin Xie, Daniel Webber, Makenzy Caldwell, Ricky Parada, and Nicole Lee.

Ethics goals

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