This is the repo that will host all the materials used for my Stanford HAI talk on April 17, 2020 - 11:00 AM titled:
On the four horsemen of ethical malice in peer reviewed machine learning literature
_The thawing of the AI winter and the subsequent deep learning revolution has been marked by large scale open-source-driven democratization efforts and a paper publishing frenzy. As we navigate through this massive corpus of technical literature, four categories of ethical transgressions come to fore:
- Dataset curation
- Modeling
- Problem definitions
- Sycophantic tech-journalism.
In this talk, we will explore specific examples in each of these categories with a strong focus on computer vision. The goal of this talk is to not just demonstrate the widespread usage of these datasets and models, but to also elicit a commitment from the attending scholars to either not use these datasets or models, or to insert an ethical caveat in case of unavoidable usage.
