Pioneers | OLCreate - The Open University

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# Pioneers

## 2\. Artificial intelligence

### 2.2. Timnit Gebru

![Timnit Gebru. Source: TechCrunch (2021)](https://www.open.edu/openlearncreate/pluginfile.php/860158/mod_label/intro/Timnit_Gebru_crop.jpg)

_Figure 1: Timnit Gebru._

_Source: TechCrunch (2021)_

##### Downloadable teaching resource

[Timnit Gebru (.pptx)](https://www.open.edu/openlearncreate/mod/resource/view.php?id=235930)

##### Overview

Timnit Gebru (ትምኒት ገብሩ) is a leading figure in AI ethics.

##### Background

Timnit Gebru was born in Addis Ababa, Ethiopia in 1983 of Eritrean descent, and went to the US as a political refugee in 1999. She went on to achieve bachelor’s and master’s degrees in electrical engineering at Stanford, and a Ph.D. from the Stanford Artificial Intelligence Laboratory (Dataiku, 2021).

##### Contributions

Gebru initially worked on designing circuits and algorithms, including work on facial recognition software, for Apple as an intern. She went on to a successful career primarily as a researcher in AI, with a focus on AI ethics. Gebru worked at Microsoft Research in the FATE (Fairness Accountability Transparency and Ethics in AI) group, studying algorithmic bias and ethical concerns in data use (Dataiku, 2021).  After noting the lack of black people at the 2016 Neural Information Systems Conference, Gebru was instrumental in launching 'Black in AI' to improve representation in the AI sector (Black in AI, 2024).

While at Microsoft, she co-authored a research paper titled 'Gender Shades', looking at bias in facial recognition software. This was linked to an MIT project promoting intersectional and inclusive product testing in AI (MIT Media Lab, no date). The Gender Shades project revealed differences in error rates, particularly worse for darker females. The project is presented at [gendershades.org](https://gendershades.org/) and the [paper](https://www.media.mit.edu/publications/gender-shades-intersectional-accuracy-disparities-in-commercial-gender-classification/) available via MIT Media Lab (Buolamwini and Gebru 2018; Buolamwini _et al._, 2018).

She joined Google as a research scientist on their ethical AI team, concerned with the implications of AI and technology for "social good" (Dataiku, 2021). In 2020 she worked on a paper covering ethical risks of AI language models with other authors including Google staff. The paper proved controversial, and she was forced out of Google after refusing to withdraw the paper or remove Google employees as authors (Dataiku, 2021). This paper is discussed in the [Feature section](https://www.open.edu/openlearncreate/mod/book/tool/print/index.ph

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