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Karen Hao

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Karen Hao
EducationMassachusetts Institute of Technology (BS)
Occupations
  • Journalist
  • Data scientist
  • Engineer
Notable credit(s)The Atlantic (2023–Present)
The Wall Street Journal (2022–2023)
MIT Technology Review (2018–2022)
Quartz (2017–2018)
Websitewww.karendhao.com
Karen Hao
Simplified Chinese郝珂灵[1]
Transcriptions
Standard Mandarin
Hanyu PinyinHǎo Kēlíng

Karen Hao is an American journalist and data scientist. Currently a contributing writer for The Atlantic and previously a foreign correspondent based in Hong Kong for The Wall Street Journal and senior artificial intelligence editor at the MIT Technology Review, she is best known for her coverage on AI research, technology ethics and the social impact of AI.[2][3] Hao also co-produces the podcast In Machines We Trust and writes the newsletter The Algorithm.[4]

Previously, she worked at Quartz as a tech reporter and data scientist and was an application engineer at the first startup to spin out of X Development. Hao's writing has also appeared in Mother Jones, Sierra Magazine, The New Republic, and other publications.

Early life and education

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Hao graduated from The Lawrenceville School in 2011.[5] She studied at the Massachusetts Institute of Technology, graduating with a B.S. in mechanical engineering and a minor in energy studies in 2015.[6][7] She is a native speaker in both English and Mandarin Chinese.[2]

Career

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Hao is known in the technology world for her coverage of new AI research findings and their societal and ethical impacts. Her writing has spanned research and issues regarding big tech data privacy, misinformation, deepfakes, facial recognition, and AI healthcare tools.

In March 2021, Hao published a piece that uncovered previously unknown information about how attempts to combat misinformation by different teams at Facebook's using machine learning were impeded and constantly at odds by Facebook's drive to grow user engagement.[8][9][10] Upon its release, leaders at Facebook including Mike Schroepfer and Yann LeCun immediately criticized the piece through Twitter responses.[11] AI researchers and AI ethics experts Timnit Gebru and Margaret Mitchell responded in support of Hao's writing and advocated for more change and improvement for all.[12]

Hao also co-produces the podcast In Machines We Trust, which discusses the rise of AI with people developing, researching, and using AI technologies.[13] The podcast won the 2020 Front Page Award in investigative reporting.[14]

As a data scientist, Hao occasionally creates data visualizations that have been featured in her work at the MIT Technology Review and elsewhere.[15] In 2018, her "What is AI?" flowchart visualization was exhibited as an installation at the Museum of Applied Arts in Vienna.[16]

She has been an invited speaker at TEDxGateway, the United Nations Foundation, EmTech, WNPR, and many other conferences and podcasts.[17][18] Her TEDx talk discussed the importance of democratizing how AI is built.[19]

In March 2022, she was hired by The Wall Street Journal to cover China technology and society, while being based in Hong Kong.[20]

Selected awards and honors

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  • 2019 Webby Award nominee for best newsletter, as a writer of The Algorithm[4]
  • 2021 Front Page Award in investigative reporting, as a co-producer for In Machines We Trust[14]
  • 2021 Ambies Award nominee for best knowledge and science podcast, as a co-producer for In Machines We Trust[21]
  • 2021 Webby Award nominee for best technology podcast, as a co-producer for In Machines We Trust[22]

References

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  1. ^ "Karen Hao in Twitter". Archived from the original on April 4, 2022. Retrieved August 12, 2022.
  2. ^ a b "Karen Hao". Educational Technology. 2020-01-14. Archived from the original on 2020-12-04. Retrieved 2021-03-22.
  3. ^ Hao, Karen. "Karen Hao". The Atlantic. Retrieved 2023-10-13.
  4. ^ a b "The Algorithm | The Webby Awards". The Webby Awards. Retrieved 2021-03-22.
  5. ^ "2018 Report of Giving - The Lawrenceville School". Issuu. 2018-11-26. Retrieved 2021-03-22.
  6. ^ "Karen Hao". MIT Club of Northern California. Retrieved 2021-03-22.
  7. ^ "Marketing AI Profile: Karen Hao". MarketMuse. 2019-03-05. Retrieved 2021-03-22.
  8. ^ "He got Facebook hooked on AI. Now he can't fix its misinformation addiction". MIT Technology Review. Retrieved 2021-03-22.
  9. ^ "AI Weekly: Facebook, Google, and the tension between profits and fairness". VentureBeat. 2021-03-12. Retrieved 2021-03-22.
  10. ^ Vincent, James (2021-03-11). "Go read this story on how Facebook's focus on growth stopped its AI team from fighting misinformation". The Verge. Retrieved 2021-03-22.
  11. ^ Greene, Tristan (2021-03-12). "Facebook AI boss Yann LeCun goes off in Twitter rant, blames talk radio for hate content". Neural | The Next Web. Retrieved 2021-03-22.
  12. ^ Zakrzewski, Cat. "Analysis | The Technology 202: Walter Isaacson says new discoveries will come from people who appreciate 'microchips and molecules'". Washington Post. ISSN 0190-8286. Retrieved 2021-03-22.
  13. ^ "MIT Technology Review premieres "In Machines We Trust" podcast" (Press release). Retrieved 2021-03-22.
  14. ^ a b "2020 Front Page Awards". THE NEWSWOMEN'S CLUB OF NEW YORK. Retrieved 2021-03-22.
  15. ^ "Artificial Intelligence in Court, Data Visualizations & Tech Journalism with Karen Hao at MIT Tech Review". Experian Global News. Retrieved 2021-03-22.
  16. ^ "UNCANNY VALUES — Artificial Intelligence & You". Uncanny Values. Retrieved 2021-03-22.
  17. ^ "Karen Hao". TEDxGateway - India's Largest Ideas Platform (Mumbai, India). Archived from the original on 2021-03-04. Retrieved 2021-03-22.
  18. ^ Session 6: Value versus Values: Balancing the Benefits of Big Data for Gender, retrieved 2021-03-22
  19. ^ Why We Need To Democratise How We Build AI | Karen Hao | TEDxGateway, retrieved 2021-03-22
  20. ^ Hao, Karen [@_KarenHao] (31 March 2022). "Hello!! Today is my first day at the Wall Street Journal. I'll be covering China tech & society and moving to Hong Kong in May. So excited to work with such talented colleagues. 😍" (Tweet) – via Twitter.
  21. ^ "2021 NOMINEES". The Ambies — Awards for Excellence in Audio. Archived from the original on 2021-03-04. Retrieved 2021-05-24.
  22. ^ "NEW Webby Gallery + Index". NEW Webby Gallery + Index. Retrieved 2021-05-24.
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