I’m embarrassed to admit that up until a few days ago, I was completely unaware that Angela Davis is a lesbian. It made

Along the way, Deborah (who I call Agent Deb) reached out to me on Facebook after seeing my TED Talk. She shared her emerging interest in issues of bias and representation in computer vision especially as she dove into datasets and saw what I was seeing: pale male data being used to represent all of society. Having just experienced Timnit’s generosity in working with me as a master’s student at the time, it was easy to pay it forward and mentor Deb who was an undergraduate at the time. Agent Deb and Timnit were invaluable supporters as I brought my MIT master’s thesis to completion in the Fall of 2017. It was a joy to co-author Gender Shades and then Actionable Auditing together with these Face Queens, building upon my thesis concepts, methodology, dataset, and analysis. Beyond talking about algorithmic bias and gawking at datasets, we also showed up to talk each other off the ledge.

I repeatedly heard, “Why are you focusing on dark-skinned faces?” “Why Black women?” These statements revealed how unusual it was to some of my colleagues to center people of color and Black women in particular in A.I. research. Why not center people like me, people like Timnit, people like Deborah?

The spotlight both shines and burns, and it is imperative that we rally behind one another at all stages of our careers. I am forever indebted to Timnit, who showed up for me long before others understood the value of my work. As I wrote on Twitter, she has always had my back.

If you want to get more things done, do your best work every day and crush your work and life goals, you have to make time for habits that may seem like lazy but actually help you get more work done.

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unt of time at my job working on serverless and those questions were easier on the exam. The CSAA exam does a great job of having questions based on real-world scenarios and the best way to prep for that is to have faced similar scenarios to those. If you have a chance to use AWS at work I encourage doing so. Using AWS at work will save you some time that you would otherwise have to spend studying after work.

At 24, Agent Deb has co-authored some of the most visible and impactful papers on algorithmic auditing. Before finishing her undergraduate degree, she was the lead author of the Actionable Auditing paper that put Amazon on its toes. We had so much fun together working on the Black Panther Scorecard and continue to collaborate as she leads algorithmic harms research for AJL’s CRASH project.

Super productive people want to get the results or outcome they want with less time and effort. They want to be able to achieve their goals and still have time to spend on other things that matter to them.

This week Timnit was ousted from Google for demanding research integrity and Deborah was featured in the 2021 Forbes 30 under 30. These cases are examples of how as highly visible and accomplished Black women we live at the intersections of privilege and oppression, praise and evisceration. The contrast of the Forbes recognition and Google’s Gebrugate reminded me of how we were attacked by Amazon for showing that they, like their peers, sold biased A.I. products despite the impact and recognition of our prior research.

You get better data. The more you simply ask people how they feel or what they think in a given situation, the better your model for them becomes. And that in turn means your guesses at how they’re thinking and feeling will be more accurate. So we have a bit of a paradox: If you want to be able to read people’s minds more effectively, you need to stop trying to read their minds and just ask instead.

They were right, and I went on to produce works like “AI, Ain’t I A Woman?”, featured in art exhibitions around the world, sign a book deal with Penguin Random House, combat symbolic annihilation through ad campaigns with iconic brands like Levi, Apple, and Olay, while doing impactful research, influencing legislation, and founding the Algorithmic Justice League.

When I connected with Timnit, she made me feel both seen and heard. Situated at one of the leading computer vision labs in the world, she took me under her wing and helped me refresh the computer vision knowledge I had gained as an undergraduate. She didn’t question my abilities. She expanded them. She didn’t approach my ambitions with doubt. She became first an intellectual companion and soon a dear friend. I am not alone.

At 24, Agent Deb has co-authored some of the most visible and impactful papers on algorithmic auditing. Before finishing her undergraduate degree, she was the lead author of the Actionable Auditing paper that put Amazon on its toes. We had so much fun together working on the Black Panther Scorecard and continue to collaborate as she leads algorithmic harms research for AJL’s CRASH project.

You get better data. The more you simply ask people how they feel or what they think in a given situation, the better your model for them becomes. And that in turn means your guesses at how they’re thinking and feeling will be more accurate. So we have a bit of a paradox: If you want to be able to read people’s minds more effectively, you need to stop trying to read their minds and just ask instead.

When I had the experience of coding in a white mask to have my face detected and decided to change research directions to explore algorithmic bias, it was then Timnit reached out to me as a late-stage PhD candidate at Stanford. She gave me the encouragement and validation to continue my exploration even as some colleagues around me at MIT were indifferent to the work or questioned my abilities. “Are you sure you want to do that kind of work?… It involves a lot of math.” This kind of questioning seemed to dismiss my degree in Computer Science from Georgia Tech achieved with highest honors. Why should I be afraid of math?

Dr. Gebru is an all-star researcher whose pioneering work on Datasheets for Datasets, Model Cards for Modeling, along with our joint work on facial analysis technology and much more has shifted how entire industries and research communities approach artificial intelligence. As a co-founder of Black In AI, she continues to pay it forward by ensuring there are meaningful opportunities for Black people often marginalized in A.I.