AI Blindspot Cards View website

Crafted by: Ania Calderon, Dan Taber, Hong Qu, and Jeff Wen · 2019

AI Blindspots are oversights in a team’s workflow that can generate harmful unintended consequences. They can arise from our unconscious biases or structural inequalities embedded in society. Blindspots can occur at any point before, during, or after the development of a model. The consequences of blindspots are challenging to foresee, but they tend to have adverse effects on historically marginalized communities. Like any blindspot, AI blindspots are universal – nobody is immune to them – but harm can be mitigated if we intentionally take action to guard against them.

The AI Blindspot Cards were designed to be used in a 10 step discovery process that helps organizations spot and address unconscious biases and structural inequalities that can lead to unintended consequences when deploying AI systems.