Timnit W. Gebru (born May 13, 1983, with other sources citing 1982, 1982/1983, or 1983/1984 in Addis Ababa, Ethiopia) is an Ethiopian-Eritrean computer scientist, engineer, and activist against racism whose parents emigrated from Eritrea.^{[3,49,2,111,127,109,8,85,60]} Gebru earned her BS, MS, and PhD degrees from Stanford University, where she worked under the supervision of Fei-Fei Li at the Stanford AI Lab and completed her 2017 dissertation, 'Visual computational sociology: computer vision methods and challenges'.^[87] Her academic and professional work focuses on artificial intelligence (AI), computer vision, algorithmic bias, data mining, fairness in machine learning, and the societal impact and ethics of technology.^{[3,49,5,2,111,116,30,42,109,8,85]} An outspoken advocate for diversity and equality in the technology sector, she argues that researchers, developers, and source data must all be diverse in order to effectively detect bias.^[112,130,63] Gebru is a co-founder of 'Black in AI', an organization and community formed to increase the participation and representation of Black researchers and specialists in artificial intelligence development and research.^{[49,14,32,130,63,135,17]}

Earlier in her career, Gebru worked at Apple from 2004 to 2013 on signal processing, before conducting research at Microsoft and Microsoft Research on the societal impacts of artificial intelligence.^[52,4] Among her research findings in 2017 was that facial recognition algorithms recognize dark-skinned individuals significantly worse than light-skinned individuals.^[113] In December 2021, Gebru founded the Distributed Artificial Intelligence Research Institute (DAIR), serving as its executive director; the independent institute works with researchers globally—with a particular focus on Africa and African immigration—to document and examine the consequences and ethical impacts of artificial intelligence on minority populations.^{[34,51,2,127,135,21]}

In 2018, Gebru joined Google, where she served as the technical co-lead of the Ethical Artificial Intelligence Team until December 2020.^{[5,33,2,9,114,4,60]} In December 2020, public controversy erupted over Gebru's abrupt departure and dismissal from Google after she co-authored a research paper examining the risks and biases of large language models (LLMs)—popularizing the term 'stochastic parrots' to describe how language models mimic human text without actual awareness or deep understanding of meaning.^{[5,32,42,6,13,7,8,121,122,23,4]} The paper, titled 'On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?' and later published in the proceedings of the ACM FAccT '21 conference, was co-authored by Gebru and other researchers, including four colleagues from Google.^[32] According to Google AI head Jeff Dean and corporate management, the paper had been submitted for publication without waiting for Google's standard internal review and allegedly ignored recent research on techniques to mitigate bias. Google management ordered Gebru to either retract the unpublished paper or remove the names of all Google-affiliated authors, including her own.^[5] Gebru rejected the order, requesting an explanation along with the identities and specific feedback of the internal reviewers, and warned that if Google refused, she would discuss a departure date or potentially resign. Google refused her conditions and terminated her employment immediately, stating that it had accepted her resignation, whereas Gebru maintained that she had not formally resigned but had only presented resignation as a conditional threat.^[16,5,49] Her controversial dismissal ignited widespread debate across the technology industry regarding academic freedom, artificial intelligence ethics, corporate governance in major tech companies, and diversity in AI research.^[91,3,14]

Gebru has received widespread international recognition for her contributions to artificial intelligence ethics and machine learning bias.^[116,30] In 2019, she won VentureBeat's AI Innovations Award in the AI for Good category alongside Joy Buolamwini and Inioluwa Raji for their research on demographic bias and errors in facial recognition systems.^[104] In 2021, she was named one of the World's 50 Greatest Leaders by Fortune magazine and selected as one of Nature's 10 people who helped shape science.^[1,89,90,42] In 2022, Time magazine included her on its list of the world's 100 most influential people.^{[89,1,90,42,88]}

Timnit Gebru was born and raised in Addis Ababa, Ethiopia, to parents of Eritrean origin.^[35,2] Her father died when she was five years old, after which she was raised by her mother.^[105] When the war between Ethiopia and Eritrea broke out when she was 15 years old, she was deported, and at the age of 16 she moved to the United States after applying for and receiving political asylum.^{[35,106,115,2,4]} After completing high school in Massachusetts, she began studying electrical engineering at Stanford University in 2001, where she earned her bachelor's and master's degrees.^[115,4,24] While in college, Gebru joined Apple as an intern, designing circuits for audio components in the hardware division; she was offered a full-time position the following year and contributed to the development of circuits and signal processing algorithms for the first iPad. During her time at Apple, she developed an interest in computer vision software to detect humans.^[125]

Gebru returned to the Stanford Artificial Intelligence Laboratory to pursue doctoral research in computer vision and computer science under the supervision of Fei-Fei Li, earning her PhD in 2017 with the dissertation Visual computational sociology : computer vision methods and challenges in Computer Vision.^{[4,35,9,36,26]} Her doctoral research investigated the use of data mining and computer vision methods on large collections of publicly available images to study social and demographic patterns, analyzing the money spent by governmental and non-governmental organizations to collect community information. By combining deep learning with Google Street View across more than 15 million images from the 200 most populous cities in the United States, she demonstrated that socioeconomic attributes such as voting patterns, income, race, and education levels can be inferred from observations of cars.^[107] She presented this work at the 2017 LDV Capital Vision Summit competition, where she won, and the research received broad media coverage from outlets including BBC News, Newsweek, The Economist, and The New York Times.^{[108,59,60,109,19]} During her doctoral studies in 2016, Gebru co-founded the organization Black in AI with researcher Rediet Abebe to promote collaboration, visibility, and increased representation of Black researchers in the field of artificial intelligence.^{[35,9,36,32,23]}

After completing her doctorate, Gebru conducted postdoctoral research for a year at Microsoft Research in the Fairness, Accountability, Transparency, and Ethics in AI (FATE) group.^[22,11] In 2018, she co-authored the landmark Gender Shades study with Joy Buolamwini of the MIT Media Lab, demonstrating that commercial automatic facial recognition systems perform significantly worse on people of color and women, with Black women being 35% less likely to be recognized than white men.^{[37,38,39,24,97,117]} The findings had substantial practical consequences on recommendations and bans regarding facial recognition systems in the United States. In another 2018 paper, Gebru and her co-authors examined the creation and maintenance of datasets in machine learning, highlighting a lack of standardized documentation and arguing that questions regarding task validity, data ownership, and data usage are critical social rather than purely technical issues.^[2] In 2019, Gebru joined other researchers in signing a letter calling on Amazon to stop selling facial recognition technology to law enforcement after MIT research found its software struggled more with darker-skinned women than systems from other companies, and she stated in an interview with The New York Times that the technology was currently too dangerous for law enforcement and security use.^[88,51]

In 2018, Gebru joined Google AI, where she co-led the Ethical Artificial Intelligence team with Margaret Mitchell, researching technology's capacity to advance social good.^[110,67,11] In 2020, Gebru co-authored the paper "On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?" with five researchers, including University of Washington linguist Emily M. Bender, outlining the environmental and economic costs of the computing power needed for large language models, biases resulting from unfiltered web scraping, the models' inability to understand underlying concepts, and their potential to deceive people.^[39,126,87] In December 2020, Google requested that Gebru withdraw the paper or remove her name; following her refusal, her employment was abruptly terminated.^{[33,2,40,9,41,110,127]} Conflicting accounts surrounded her departure: Google AI Director Jeff Dean claimed the paper did not meet internal quality requirements, while a Montreal-based Google AI employee noted publications were typically screened only for sensitive disclosures rather than quality; Gebru stated her dismissal stemmed from her criticisms of Google's minority recruitment practices and AI biases, whereas Google maintained that her departure followed an ultimatum she issued.^{[39,9,14,118]} The dismissal triggered widespread controversy over research freedom in tech companies, leading over 1,400 Google employees and 1,900 external supporters to sign an open letter condemning her firing.^[9,39]

Following her departure from Google, Gebru became an independent researcher and founded the Distributed Artificial Intelligence Research Institute (DAIR) in 2021 to document the impacts of artificial intelligence on marginalized communities, with a particular focus on Africa and African diaspora communities in the United States.^[53] In 2021, the journal Nature named her one of the ten people who shaped science that year, and Fortune magazine listed her among the "World's 50 Greatest Leaders"; in 2022, Time magazine included her on its list of the 100 Most Influential People.^[11,18,1,42] In 2022, Gebru collaborated with Niloufar Salehi on developing effective machine translation tools for high-stakes contexts such as healthcare.^[120,119] In 2023, together with philosopher Émile P. Torrès, she coined the acronym TESCREAL to describe a set of ideologies common among artificial general intelligence proponents (transhumanism, extropianism, singularitarianism, cosmism, rationalism, effective altruism, and longtermism), an area in which Gebru has frequently voiced criticism of Effective Altruism.^[12] Her public comments surrounding the 2023 Hamas attack on Israel drew criticism as antisemitic after she shared a video containing the slogan "From the River to the Sea."^[42]

Timnit Gebru was born and raised in Addis Ababa, Ethiopia, to parents of Eritrean origin.^{[14,4,50,15,138,16]} Her father, an electrical engineer who held a PhD, died when she was five years old, and she was raised by her mother, an economist, while her two eldest sisters also became electrical engineers.^{[15,50,14,20,16,138,4,17]} At the age of 15, during the Eritrean–Ethiopian War, she fled Ethiopia after some of her family members were deported to Eritrea and forced to fight in the conflict.^{[138,15,16,4]} She was initially denied a United States visa and lived briefly in Ireland—or Iceland according to Italian sources—before eventually receiving political asylum in the United States, an experience she described as miserable or harrowing, joining her mother and older sisters who already lived there.^{[16,15,51,138,4]} Gebru settled in Somerville, Massachusetts, to attend high school, where she reported immediately experiencing racial discrimination when some teachers refused to allow her to take certain Advanced Placement courses despite her high academic achievement.^{[17,52,51,21,14,138,15,16,4]}

After completing high school—or following her undergraduate studies according to Fula sources—an encounter Gebru had with law enforcement set her on a course toward technology ethics. When a Black female friend of hers was assaulted in a bar, Gebru called the police to report it, but instead of filing an assault report, the police arrested her friend and remanded her to a cell, or took her to a hospital according to Fula sources. Gebru described this encounter as a pivotal moment and a stark example of systemic racism.^[51,23] In 2001, Gebru was admitted to Stanford University, where she earned Bachelor of Science and Master of Science degrees in electrical engineering.^{[17,3,16,24,52,23,139,18,51]} During the 2008 United States presidential election, she canvassed in support of Barack Obama.^[18,23,24] Gebru also worked at Apple, developing signal processing algorithms for the first iPad.^[18,17,140]

In 2017, she earned her doctorate in computer vision at Stanford University under the supervision of Fei-Fei Li.^{[24,23,52,18,51,142]} She used data mining of publicly available images to explore alternatives to the costly data collection conducted by governmental and non-governmental organizations.^{[14,19,18,96]} By combining deep learning with Google Street View across more than 15 million images from the 200 most populated U.S. cities, her research estimated neighborhood demographics, showing that socioeconomic attributes such as income, race, education, and political leaning could be inferred from cars—including that a higher proportion of pickup trucks compared to sedans (or convertibles, according to Vietnamese sources) correlated with higher Republican voting.^{[20,14,18,59,60]} The work received extensive coverage from media outlets including BBC News, Newsweek, The Economist, and The New York Times.^[21,20,22] Gebru presented her doctoral research at the 2017 LDV Capital Vision Summit competition, winning the competition and establishing collaborations with industry members, entrepreneurs, and venture capitalists.^{[22,53,26,59,21,51,23]}

In 2016 during her doctoral studies and again in 2018, Gebru returned to Ethiopia with Jelani Nelson to teach as part of the AddisCoder programming initiative.^{[23,17,54,52,51,24,60,26]} While working on her PhD, Gebru authored an unpublished paper addressing her concerns over the future of artificial intelligence and the dangers of a lack of diversity in the field, drawing on her encounters with law enforcement and a ProPublica investigation into predictive policing that highlighted human bias in machine learning. In the paper, she criticized the field's 'boys' club culture', hero-worship of prominent figures, and recounted her experiences with sexual harassment by drunken male attendees at conference gatherings.^[20,54] After completing her PhD, Gebru joined Microsoft as a postdoctoral researcher in the Fairness, Accountability, Transparency, and Ethics in AI laboratory, and she was named an 'Alicorn in Artificial Intelligence' by Selfpreneur.^{[22,19,24,60,26]}

Gebru worked at Apple Inc., where she developed signal processing algorithms for the first iPad.^[17] She revealed that one can predict, with some reliability, how Americans will vote based on the type of vehicle they drive. In 2017, she accepted a job at Microsoft, working in the Fairness, Accountability, Transparency, and Ethics department for artificial intelligence.^[109,8] In 2017, Gebru spoke at the Fairness and Transparency conference, where MIT Technology Review interviewed her about the biases that exist in artificial intelligence systems and how adding diversity to artificial intelligence teams can solve this problem. During the interview with Jackie Snow, when asked how the lack of diversity distorts artificial intelligence and specifically computer vision, Gebru pointed out that biases exist among software developers.^[36] She has also discussed the direction of and biases in artificial intelligence across various podcasts and interviews.^[123,124]

When Gebru attended an artificial intelligence conference in 2016, she noticed that she was the only Black woman among the 8,500 delegates present.^[25,28,29] Together with her colleague Rediet Abebe, Gebru founded Black in AI, a community of Black researchers working in artificial intelligence.^[141] Since 2017, Black in AI has organized workshops at the annual Conference on Neural Information Processing Systems.

She collaborated with MIT in its Gender Shades research group, working with Joy Buolamwini to investigate facial recognition software and finding that Black women are 35% less likely to be recognized than white men.^{[26,27,28,36]} Gebru and other artificial intelligence researchers signed a letter reflecting the systemic problems that reside in Amazon's facial recognition software. A study conducted by MIT researchers shows that Amazon's facial recognition system had more trouble identifying darker-skinned women than the facial recognition software of any other tech company.^[29] In an interview with The New York Times, Gebru further expressed that she believes facial recognition is too dangerous to be used for law enforcement and security purposes at this time.^[14]

Gebru worked at Google in the ethical artificial intelligence department, where she studied the implications of artificial intelligence, seeking to improve technology's ability to do social good.^[25,27] In December 2020, Gebru announced that she had been fired by Google after an alleged dispute over a research paper. Following this, Google workers started the #ISupportTimnit campaign to show solidarity with Gebru.^[30]

In 2004, while studying at Stanford University, Gebru joined Apple as an intern in their hardware division designing circuitry for audio components, and was offered a full-time position the following year.^[55,17] Regarding her work as an audio engineer, her manager told Wired that she was "fearless" and well-liked by her colleagues. During her time at Apple, Gebru developed an interest in software development, particularly computer vision capable of detecting human figures.^[20,56] She went on to develop signal processing algorithms for the first iPad.^[55] At the time, she said she did not consider the potential surveillance applications of such technologies, remarking, "I just found it technically interesting."

During the #AppleToo movement in the summer of 2021—led by Apple engineer Cher Scarlett, who consulted with Gebru—Gebru spoke out about her time at the company, with English and Chinese sources stating this occurred long after leaving Apple, while the Fula source states it was shortly after she left.^[57,54] Gebru revealed that she had experienced "so many egregious things" and always wondered how Apple managed to stay out of the spotlight.^[57,54] She emphasized that accountability at Apple was long overdue, warning that the company could not continue flying under the radar for much longer.^{[59,19,58,57]} Gebru also criticized the media's coverage of Apple and other tech giants, stating that the press helps shield such companies from public scrutiny.^{[58,19,59,57]}

In 2013, Gebru began her PhD in computer vision and joined Fei-Fei Li's research laboratory at Stanford University.^{[52,60,24,61]} Her doctoral studies were supported by the NSF Foundation GRFP fellowship and the Stanford DARE fellowship, both awarded to students who excel in engineering fields.^[131] For her doctorate, Gebru was interested in the amount of money spent by governmental and non-governmental organizations to collect community information, and investigated alternatives using data mining on publicly accessible images.^[18,96] Combining deep learning techniques with Google Street View images, she conducted a study to estimate the demographics and socioeconomic characteristics of United States neighborhoods, demonstrating that attributes such as voting patterns, income, race or ethnic background, and education levels can be inferred from observations of vehicles on the streets.^{[52,60,24,61]} The study showed that if the number of pickup trucks in a neighborhood exceeded the number of sedans, that community was more likely to vote Republican. Analyzing more than 15 million images from the 200 most populous U.S. cities, the work received widespread media coverage, including by BBC News, Newsweek, The Economist, and The New York Times.^[25,19] Having earned her PhD in 2017 under Li's supervision, Gebru presented her research at the LDV Capital Vision Summit competition in the summer of that year, winning the competition and initiating collaborations with entrepreneurs and investors.^[36,14]

During her PhD, Gebru wrote an unpublished article expressing early concerns regarding the risks of artificial intelligence, linking them to her personal experiences with law enforcement and the underrepresentation of women and ethnic minorities in the sector. The article cited a ProPublica investigation into predictive policing in the United States to highlight how machine learning systems could reproduce human biases, criticized the "boys' club culture" of the industry citing incidents of harassment experienced at conferences, and questioned the tendency to idealize prominent figures in the AI field.^[2,14,52] Her concerns were reinforced when she attended the field's premier conference, Neural Information Processing Systems (NIPS), in Montreal, Canada, in 2015, where she observed she was one of only a few Black researchers among 3,700 attendees.^{[63,61,22,62]} When she attended NIPS again the following year, she kept a tally and noted that out of 8,500 delegates, there were only five Black men (or five people of color, according to Italian Wikipedia), and that she was the only Black woman present.^{[62,64,63,14]} To address this lack of diversity, Gebru and her colleague Dr. Rediet Abebe co-founded Black in AI, a community of Black researchers working in artificial intelligence that aims to increase the presence, visibility, and well-being of Black scholars, professionals, and leaders within the field.^{[22,64,36,63,20]} In 2016 and 2018, Gebru returned to Ethiopia as a volunteer instructor for the AddisCoder training program founded by Jelani Nelson.^[21]

In the summer of 2017, Gebru joined Microsoft as a postdoctoral researcher in the Fairness, Accountability, Transparency, and Ethics in AI (FATE) laboratory.^[51,18] Also in 2017, she spoke at the Conference on Fairness and Transparency, where MIT Technology Review interviewed her about biases in AI systems and how increasing diversity on AI teams could mitigate that issue. In her interview with Jackie Snow, when asked how the lack of diversity distorts artificial intelligence and specifically computer vision, Gebru pointed out that biases exist among software developers.^{[65,36,52,51,26]} While at Microsoft, Gebru co-authored a research paper titled "Gender Shades" with Dr. Joy Buolamwini (published in 2018), which became the namesake of a broader Massachusetts Institute of Technology project led by Buolamwini.^[25,36] Investigating facial recognition software, the study revealed that in one particular implementation, Black women were 35% less likely to be recognized than white men (or Black men, according to Fula Wikipedia).^[66,25,31]

Gebru joined Google in 2018, where she co-led the Ethical Artificial Intelligence team alongside Margaret Mitchell.^[65] She studied the social implications of artificial intelligence, seeking to improve technology's ability to benefit society and promote social good.^[67,65] In 2019, Gebru and other artificial intelligence researchers signed a letter calling on Amazon to stop selling its facial recognition technology to law enforcement agencies because it was biased against women, Black people, and people of color.^[68,32] The letter cited a study conducted by Massachusetts Institute of Technology (MIT) researchers showing that Amazon's facial recognition system had greater difficulty identifying darker-skinned females than software from any other technology company.^[68,32,66] In an interview with The New York Times, Gebru further stated that she believes facial recognition is too dangerous to currently be used for law enforcement, security, and anti-terrorism purposes.^[69,67]

In 2020, Gebru co-authored a research paper titled "On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜" with five co-authors.^[70,68] The paper examined the major risks of very large language models, including their environmental footprint and financial costs, the inscrutability and opacity of large models, large language models' inability to understand the language or concepts they process, their potential to perpetuate bias against certain groups, and their risk of being exploited to spread disinformation and mislead people.^[70,68] Regarding the paper's authorship, English and Chinese Wikipedia state that of the six authors, only Emily M. Bender was not employed at Google at the time, whereas Fula Wikipedia states that only Bender was working at Google.^[70] In December 2020, Gebru's employment with Google ended after Google management summoned her to a meeting on short notice and requested that she either retract the paper prior to publication or remove the names of all Google employees from it.^{[2,98,14,52,69]}

In response, Gebru sent an email to an internal collaborative list requesting the identities and rationales of those involved in the decision, advice on revising the paper, and a more transparent review process for future research, offering to withdraw her name and stating that she would work with Google on an employment end date after an appropriate period if her conditions to avoid resignation were not met.^{[2,51,20,98,68]} Gebru also sent a second email to a Google Brain women's email list, accusing the company of "silencing marginalized voices" and dismissing Google's internal diversity programs as a waste of time.^[72] Google declined her requests, and executives Jeff Dean and Megan Kacholia terminated her employment immediately, declaring that the company had accepted her resignation.^{[28,5,71,67,68,14,52,69]} The circumstances of her departure remain disputed, as Gebru and several coworkers stated that she had been fired, while Gebru maintained that she had never offered to resign and had only threatened to do so.^{[27,66,97,14,52,69]} Jeff Dean, Google's head of AI research, addressed Gebru's departure in an email and published internal communications, stating that the paper failed to meet publication standards because it ignored recent research on mitigating bias and environmental impacts, and defending Google's research process as aiming to tackle ambitious problems responsibly.^[70]

Gebru and her supporters blamed Dean's initial email and subsequent silence for catalyzing harassment against her on Twitter by sockpuppet accounts and internet trolls, as well as machine learning researcher Pedro Domingos and businessman Michael Lissack, who described Gebru's work as "propaganda under the guise of science" and allegedly harassed Mitchell, Bender, and other colleagues before Twitter temporarily suspended Lissack's account on February 1, 2021. In the aftermath, nine members of Congress sent a letter to Google asking it to clarify the circumstances around Gebru's exit, and while Spanish Wikipedia states that over 1,200 Google employees and 1,500 researchers signed a protest letter condemning the alleged firing, English, Fula, and Chinese Wikipedia state that roughly 2,700 employees and more than 4,300 academics and civil society supporters signed it.^{[72,73,74,100,30,75,71]} Google's ethical AI research team demanded that Dean and Vice President Megan Kacholia apologize, and called for Kacholia's removal from the team's management chain after she allegedly fired Gebru without notifying Gebru's direct supervisor, Samy Bengio.^{[101,70,14,98]} Margaret Mitchell publicly criticized Google on Twitter for its treatment of employees working to counter AI bias and toxicity, but was later terminated; sources differ on the stated reason, with English, Fula, and Italian Wikipedia reporting she was fired after allegedly creating automated scripts to scan internal servers for evidence of Gebru's mistreatment, while Chinese Wikipedia reports she was fired for allegedly leaking confidential documents and private employee data.^{[76,77,74,11]}

Following public controversy, Alphabet CEO Sundar Pichai issued an apology without admitting wrongdoing or clarifying whether Gebru had been fired or had resigned, and initiated a months-long investigation into the incident.^{[75,77,99,78,11]} Following the review, Dean announced that Google would change its approach for how certain employees exit the company, modify how research papers with "sensitive" topics are reviewed, and report diversity, equity, and inclusion goals to Alphabet's board of directors quarterly, though the review did not clarify whether Gebru's departure was voluntary.^[76,78,14] Gebru responded on Twitter that she had "no higher expectations" because no one took responsibility, and two Google employees subsequently resigned from the company. Google also held a town hall for Black employees to discuss racial discrimination at the company, though employees reported to NBC News that half of the forum was spent disparaging Gebru to make an example of her, and subsequent group psychotherapy sessions with a licensed therapist were criticized by employees as dismissive and insulting regarding the harm caused by Gebru's departure.^[79,11]

In November 2021, the Nathan Cummings Foundation, in partnership with Open MIC and endorsed by Color of Change, filed a shareholder proposal calling for a racial equity audit of Alphabet's adverse impact on BIPOC communities and an investigation into whether Google retaliated against or underpaid minority employees, following an earlier request by Senate Democratic Caucus members led by Cory Booker citing Gebru's departure and research.^{[81,11,83,80,82]} In December 2021, Reuters reported that the California Department of Fair Employment and Housing (DFEH) was investigating Google's treatment of Black women following formal discrimination and harassment complaints, after Gebru and other BIPOC employees reported that Human Resources advised them to take medical leave and EAP therapy when they raised concerns of racism and sexism.^{[82,14,84,85]} Gebru and others maintain that her alleged dismissal was retaliatory and evidence of systemic and institutional racism, while Google stated that it continues to focus on representative and equitable work and thoroughly investigate concerns.^[85,84]

In November 2021, the Nathan Cummings Foundation, in partnership with Open MIC and supported by Color of Change, submitted a shareholder proposal calling for a "racial equity audit" to analyze Alphabet's "adverse impact" on "Black, Indigenous, and People of Color (BIPOC) communities".^[82] Citing Gebru's dismissal, her previous urging for Google to hire more BIPOC, and her research on racial bias in Google's technology, the proposal also called for an investigation into whether Google retaliated against minority employees who raised concerns about discrimination.^[74] This proposal followed an informal request made earlier that year by members of the Senate Democratic caucus led by Cory Booker, who also referenced Gebru's parting of ways with the company. In December 2021, Reuters reported that Google was being investigated by the California Department of Fair Employment and Housing (DFEH) over the company's treatment of Black women, following formal complaints of discrimination and harassment from current and former employees.^[78] Previously, Gebru and other BIPOC employees reported that when they spoke to HR about their experiences with racism and sexism, HR suggested they take medical leave and receive therapy through the company's Employee Assistance Program (EAP). Gebru and others viewed her firing as a retaliatory action and evidence of institutional racism at Google, while Google stated that the company "will continue to focus on this important work and thoroughly investigate any concerns, to ensure that [Google] is representative and equitable."

In June 2021, Gebru announced that she was raising funds to launch an independent research institute modeled on her work leading Google's Ethical AI team and her experience in Black in AI. On 2 December 2021, she launched the Distributed Artificial Intelligence Research Institute (DAIR), an independent research center dedicated to documenting and studying the effects of artificial intelligence on marginalized and vulnerable groups, with a focus on Africa and African immigrants in the United States.^{[47,46,86,14,85]} One of the institute's initial projects plans to use AI to analyze satellite imagery of South African townships to better understand the legacy of apartheid.

Together with American philosopher and historian Émile P. Torres, Gebru coined the neologism acronym TESCREAL to describe and criticize a cluster of interconnected and overlapping futurist philosophies and movements, standing for Transhumanism, Extropianism, Singularitarianism, Russian Cosmism, Rationalism, Effective Altruism, and Longtermism.^[43,44,45] Gebru classifies this movement as a right-leaning influence on Big Tech and compares its proponents to "20th-century eugenicists" for producing harmful projects portrayed as "benefiting humanity".^[46,86,87] Science commentator Anjana Ahuja added that wealthy or clever individuals sometimes bundle strange beliefs under the TESCREAL acronym, claiming that tech experts discuss fuzzy future problems like existential risk from artificial intelligence to distract from real present harms such as algorithmic bias.^[47] Sociologist James J. Hughes, former executive director of the World Transhumanist Association (Humanity+), and Eli Sennesh criticized what they termed the "anti-TESCREAL conspiracy" as "reactive" rather than proactive, arguing that each philosophy has an ignored progressive political wing.^[48] American software developer, entrepreneur, and financial investor Marc Andreessen has at times described himself on his X profile (formerly Twitter), among other things, as a "TESCREAList".^[45]

Gebru has also criticized research into artificial general intelligence (AGI) as being rooted in eugenics.^[87] She states that attention should be shifted away from AGI and that attempting to build AGI is an inherently unsafe and risky practice.^[31,32,87]

Gebru, Joy Buolamwini, and Inioluwa Deborah Raji won VentureBeat's 2019 AI Innovations Award in the "AI for Good" category for their research highlighting the significant problem of algorithmic bias in facial recognition.^{[29,30,87,80,88,89,31,132]} In work published in the proceedings of the Conference on Fairness, Accountability, and Transparency, Gebru and Buolamwini argued that algorithms trained on databases that do not adequately represent women, especially non-white women, result in different forms of discrimination.^[133]

In 2021, Gebru was recognized by Fortune magazine as one of the World's 50 Greatest Leaders.^[32] That same year, she was included in a list compiled by the scientific journal Nature of ten scientists who played important roles in scientific developments in 2021.^[90,88,1] While Amharic Wikipedia records that she was selected by Time magazine as one of the 100 most influential people in the world in 2021, English, Fula, and Chinese sources state she was named one of Time's most influential people in 2022.

In 2023, Gebru was named an honoree of the Great Immigrants Awards by the Carnegie Corporation of New York in recognition of her significant contributions to the field of ethical and unbiased artificial intelligence.^[42,91,53] In November 2023, she was also named to the BBC's 100 Women list as one of the world's inspiring and influential women.^[92,31]

Her publications include "Visual computational sociology: computer vision methods and challenges" (also rendered as "Computational visual sociology: computer vision methods and challenges"). On 12 December 2017, Timnit Gebru, Jonathan Krause, Yilun Wang, Duyun Chen (listed as Duyun Deng in Fula Wikipedia), Jia Deng, Erez Lieberman Aiden, and Li Fei-Fei published a paper in the Proceedings of the National Academy of Sciences (vol. 114, no. 50, pp. 13108–13113, Bibcode: 2017PNAS..11413108G, DOI: 10.1073/pnas.1700035114, ISSN: 0027-8424, PMC: 5740675, PMID: 29183967), titled "Using deep learning and Google Street View to estimate the demographic makeup of neighborhoods across the United States" (or "Using deep learning and Google Street View to estimate demographics in US cities"). In 2018, Joy Buolamwini and Timnit Gebru published "Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification" in the Proceedings of Machine Learning Research (vol. 81, pp. 1–15, ISSN: 1938-7288). On 9 July 2020, Gebru contributed the chapter "Race and Gender" (pages 251 to 269; DOI: 10.1093/Oxfordhb/9780190067397.013.16; ISBN: 978-019-006739-7) to The Oxford Handbook of Ethics of AI, published by Oxford University Press and edited by Markus D. Dubber, Frank Pasquale, and Sunit Das. On 1 April 2024, Timnit Gebru and Émile P. Torres published "The TESCREAL bundle: Eugenics and the promise of utopia through artificial general intelligence" in First Monday (vol. 29, no. 4, DOI: 10.5210/fm.v29i4.13636).

Born in 1983 in Addis Ababa, she is a living 21st-century Ethiopian and American computer scientist, artificial intelligence researcher, and social scientist, as well as an alumna of Stanford University. She is an Ethiopian emigrant and refugee in the United States. She has worked at Microsoft and Google, and is also an Ethiopian and African-American activist and businessperson.

External links include the Black in AI website. She is categorized as a living person born in 1983, a 21st-century Ethiopian person, a 21st-century American businessperson, and an American computer scientist. Additionally, she is categorized as a Stanford University alumna as well as an employee of Google and Microsoft.^[139]