Timnit Gebru

7 Posts

Abeba Birhane
Timnit Gebru

Abeba Birhane: Clean up web datasets

From language to vision models, deep neural networks are marked by improved performance, higher efficiency, and better generalizations. Yet, these systems are also marked by perpetuation of bias and injustice.
Timnit Gebru and the Distributed Artificial Intelligence Research Institute logo
Timnit Gebru

Corporate Ethics Counterbalance: Timnit Gebru launches institute for AI fairness.

One year after her acrimonious exit from Google, ethics researcher Timnit Gebru launched an independent institute to study neglected issues in AI.
Illustration of Thumbzilla destroying a city and shooting lightning from its mouth (T-Rex with Facebook thumbs up)
Timnit Gebru

Don’t Be Evil?!: AI Could Tempt Corporations to Ignore Social Responsibility

Tech companies generally try to be (or to appear to be) socially responsible. Would some rather let AI’s negative impacts slide?
Walking through a narrow hallway in a library
Timnit Gebru

Bias By the Book: Researchers find bias in influential NLP dataset BookCorpus.

Researchers found serious flaws in an influential language dataset, highlighting the need for better documentation of data used in machine learning.
Margaret Mitchell, Marian Croak and Timnit Gebru pictured
Timnit Gebru

Google Overhauls Ethical AI Team: What Google is doing after Timnit Gebru's departure.

Having dismissed two key researchers, Google restructured its efforts in AI ethics. Marian Croak, an accomplished software engineer and vice president of engineering at Google, will lead a new center of expertise in responsible AI, the company announced.
Tree farm dataset
Timnit Gebru

Representing the Underrepresented: Many important AI datasets contain bias.

Some of deep learning’s bedrock datasets came under scrutiny as researchers combed them for built-in biases. Researchers found that popular datasets impart biases against socially marginalized groups to trained models due to the ways the datasets were compiled, labeled, and used.
Examples of high-resolution versions of low-resolution images.
Timnit Gebru

Image Resolution in Black and White: Behind the Pulse controversy about bias in machine learning

A new model designed to sharpen images tends to turn some dark faces white, igniting fresh furor over bias in machine learning. Photo Upsampling via Latent Space Exploration (Pulse) generates high-resolution versions of low-resolution images.

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