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Timnit Gebru

Timnit Gebru is a mathematics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Timnit Gebru rather than just read about it. In short: Timnit W. Gebru (Amharic and Tigrinya: ትምኒት ገብሩ; 1982/1983) is an Eritrean Ethiopian-born computer scientist who works in the fields of artificial intelligence (AI), algorithmic bias and data mining.

Timnit Gebru — main illustration
Timnit Gebru — illustration

Key takeaways

  • Timnit Gebru belongs to mathematics; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Timnit Gebru to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Timnit Gebru from memory before moving on to harder problems.

Reference excerpt

Timnit W. Gebru (Amharic and Tigrinya: ትምኒት ገብሩ; 1982/1983) is an Eritrean Ethiopian-born computer scientist who works in the fields of artificial intelligence (AI), algorithmic bias and data mining. She is a co-founder of Black in AI, an advocacy group that has pushed for more Black roles in AI development and research. She is the founder of the Distributed Artificial Intelligence Research Institute (DAIR). In December 2020, public controversy erupted over the circumstances surrounding Gebru's departure from Google, where she was technical co-lead of the Ethical Artificial Intelligence Team. Gebru had coauthored a paper on the risks of large language models (LLMs) acting as stochastic parrots, and submitted it for publication. According to Jeff Dean, head of Google AI, the paper was submitted without waiting for Google's internal review, which then asserted that it ignored too much relevant research. Google management requested that Gebru either withdraw the paper or remove the names of all the authors employed by Google. Gebru requested the identity and feedback of every reviewer, and stated that if Google refused, she would talk to her manager about "a last date". Google terminated her employment immediately, stating that they were accepting her resignation. Gebru maintained that she had not formally offered to resign, and only threatened to. Gebru has been widely recognized for her expertise in the ethics of artificial intelligence. She was named one of the World's 50 Greatest Leaders by Fortune and one of Nature's ten people who shaped science in 2021, and in 2022, one of Time's most influential people.

Early life and education Gebru was raised in Addis Ababa, Ethiopia. Her father, an electrical engineer with a Doctor of Philosophy (PhD), died when she was five years old, and she was raised by her mother, an economist. Both her parents are from Eritrea. When Gebru was 15, during the Eritrean–Ethiopian War, she fled Ethiopia after some of her family were deported to Eritrea and compelled to fight in the war. She was initially denied a U.S. visa and briefly lived in Ireland, but she eventually received political asylum in the U.S., an experience she said was "miserable". Gebru settled in Somerville, Massachusetts to attend high school, where she says she immediately started to experience racial discrimination, with some teachers refusing to allow her to take certain Advanced Placement courses, despite being a high-achiever. After she completed high school, an encounter with the police set Gebru on a course toward a focus on ethics in technology. A friend of hers, a Black woman, was assaulted in a bar, and Gebru called the police to report it. She says that instead of filing the assault report, her friend was arrested and remanded to a cell. Gebru called it a pivotal moment and a "blatant example of systemic racism." In 2001, Gebru was accepted at Stanford University. There, she earned her Bachelor of Science and Master of Science degrees in electrical engineering and her PhD in computer vision in 2017. Gebru was advised during her PhD program by Fei-Fei Li. During the 2008 United States presidential election, Gebru canvassed in support of Barack Obama. Gebru presented her doctoral research at the 2017 LDV Capital Vision Summit competition, where computer vision scientists present their work to members of industry and venture capitalists. Gebru won the competition, starting a series of collaborations with other entrepreneurs and investors. Both during her PhD program in 2016 and in 2018, Gebru returned to Ethiopia with Jelani Nelson's programming campaign, AddisCoder. While working on her PhD, Gebru authored a paper that was never published about her concern over the future of AI. She wrote of the dangers of the lack of diversity in the field, centered on her experiences with the police and on a ProPublica investigation into predictive policing, which revealed a projection of human biases in machine learning. In the paper, she scathed the "boy's club culture", reflecting on her experiences at conference gatherings of drunken male attendees sexually harassing her, and criticized the hero worship of the field's celebrities.

Career

2004–2013: Software development at Apple Gebru joined Apple as an intern while at Stanford, working in their hardware division making circuitry for audio components, and was offered a full-time position the following year. Of her work as an audio engineer, her manager told Wired she was "fearless", and well-liked by her colleagues. During her tenure at Apple, Gebru became more interested in building software, namely computer vision that could detect human figures. She went on to develop signal processing algorithms for the first iPad. At the time, she said she did not consider the potential use for surveillance, saying "I just found it technically interesting." Long after leaving the company, during the #AppleToo movement in the summer of 2021, which was led by Apple engineer Cher Scarlett, who consulted with Gebru, Gebru revealed she experienced "so many egregious things" and "always wondered how they manage[d] to get out of the spotlight." She said that accountability at Apple was long overdue, and warned they could not continue to fly under the radar for much longer. Gebru also criticized the way the media covers Apple and other tech giants, saying that the press helps shield such companies from public scrutiny.

… excerpt ends here. Continue reading the full article.

Illustrations

Timnit Gebru illustration
Timnit Gebru: Gebru discussing her findings that one can predict, with some reliability, the way an American will vote from the type of vehicle they drive
Gebru discussing her findings that one can predict, with some reliability, the way an American will vote from the type of vehicle they drive
Timnit Gebru: Gebru speaking at The Web Conference 2019
Gebru speaking at The Web Conference 2019

Worked examples

Example 1 — a first encounter with Timnit Gebru

Start with the simplest possible case. Write down what Timnit Gebru claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In mathematics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Timnit Gebru before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Timnit Gebru ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Timnit Gebru

In research
Timnit Gebru appears in mathematics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Timnit Gebru in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Timnit Gebru is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1983 births, 21st-century African-American women, 21st-century American businesspeople, so understanding it makes those chapters shorter.
In everyday life
Look for Timnit Gebru outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Timnit Gebru in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Timnit Gebru means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Timnit Gebru out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Timnit Gebru in simple terms?

Timnit W. Gebru (Amharic and Tigrinya: ትምኒት ገብሩ; 1982/1983) is an Eritrean Ethiopian-born computer scientist who works in the fields of artificial intelligence (AI), algorithmic bias and data mining.

Why does Timnit Gebru matter?

Because it connects several mathematics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Timnit Gebru?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Timnit Gebru.

Tags

  • 1983 births
  • 21st-century African-American women
  • 21st-century American businesspeople
  • 21st-century American businesswomen
  • 21st-century American social scientists
  • 21st-century American women scientists
  • 21st-century Ethiopian people
  • 21st-century Ethiopian women
  • 21st-century statisticians
  • African-American activists
  • African-American businesspeople
  • African-American businesswomen

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