Building a more diverse data science team
We’ve seen no shortage of scandals in artificial intelligence. Several AI projects have been plagued by bias. ProPublica reported that an algorithm built by one private contractor was more likely to rate Black parole candidates as higher-risk than other candidates. A landmark U.S. government study reported that more than 200 facial recognition algorithms had a harder time identifying non-white faces than white faces. Is it surprising that these applications were built by teams lacking diversity? Technology has a remarkably non-diverse workforce. And data science is a special standout, underrepresenting women, Latinx, and Black professionals more than any role in tech.
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Building a More Diverse Data Science Team<https://t.a.email.hbr.org/r/?id=h766d80c1%2Cdde367e%2Cdde3682&s=9OaX0eTtX5nRfPE8pbIDSi-DsxqPenyiZvb8jE7ordY>
Featuring Tianhui Michael Li, the founder and president of The Data Incubator, and author of the recent HBR article, “To Build Less-Biased AI, Hire a More-Diverse Team”
Monday, March 29, 2021 • 1:00 PM Eastern Time (ET)
Complimentary Webinar
REGISTER NOW<https://t.a.email.hbr.org/r/?id=h766d80c1%2Cdde367e%2Cdde3683&s=nL-cvs3fq1M6yZfIwbgP0G3bh2NrcgYyohhGJ_QXOII>
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[Tianhui Michael Li]
Tianhui Michael Li
Founder and president
The Data Incubator
[https://hbr.org/resources/images/webinars/evites/spacer.gif]
ABOUT THE EVENT
We’ve seen no shortage of scandals in artificial intelligence. Several AI projects have been plagued by bias. ProPublica reported that an algorithm built by one private contractor was more likely to rate Black parole candidates as higher-risk than other candidates. A landmark U.S. government study reported that more than 200 facial recognition algorithms had a harder time identifying non-white faces than white faces. Is it surprising that these applications were built by teams lacking diversity? Technology has a remarkably non-diverse workforce. And data science is a special standout, underrepresenting women, Latinx, and Black professionals more than any role in tech.
On Monday, March 29, Tianhui Michael Li, the founder and president of The Data Incubator, a data-science training and placement firm, will be our webinar guest on Ask HBR, and he will look at building less-biased AI by hiring more diverse AI and technology teams.
Li, author of the recent HBR article “To Build Less-Biased AI, Hire a More-Diverse Team<https://t.a.email.hbr.org/r/?id=h766d80c1%2Cdde367e%2Cdde3684&s=A-BPsxZxXA4UrqQLHUgnskX-Lytdgmlv-cpkBNvcd54,”> will offer concrete recommendations for ways to hire more diverse talent while boosting team performance.
For insights on combating bias in AI and developing more diverse AI and tech talent in your organization, join us and Michael Li on March 29. Submit your questions in advance to: askhbr@hbr.org<mailto:askhbr@hbr.org>.
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Building a More Diverse Data Science Team<https://t.a.email.hbr.org/r/?id=h766d80c1%2Cdde367e%2Cdde3682&s=9OaX0eTtX5nRfPE8pbIDSi-DsxqPenyiZvb8jE7ordY>
Featuring Tianhui Michael Li, the founder and president of The Data Incubator, and author of the recent HBR article, “To Build Less-Biased AI, Hire a More-Diverse Team”
Monday, March 29, 2021 • 1:00 PM Eastern Time (ET)
Complimentary Webinar
REGISTER NOW<https://t.a.email.hbr.org/r/?id=h766d80c1%2Cdde367e%2Cdde3683&s=nL-cvs3fq1M6yZfIwbgP0G3bh2NrcgYyohhGJ_QXOII>
FEATURED SPEAKER
[https://hbr.org/resources/images/webinars/evites/spacer.gif]
[Tianhui Michael Li]
Tianhui Michael Li
Founder and president
The Data Incubator
[https://hbr.org/resources/images/webinars/evites/spacer.gif]
ABOUT THE EVENT
We’ve seen no shortage of scandals in artificial intelligence. Several AI projects have been plagued by bias. ProPublica reported that an algorithm built by one private contractor was more likely to rate Black parole candidates as higher-risk than other candidates. A landmark U.S. government study reported that more than 200 facial recognition algorithms had a harder time identifying non-white faces than white faces. Is it surprising that these applications were built by teams lacking diversity? Technology has a remarkably non-diverse workforce. And data science is a special standout, underrepresenting women, Latinx, and Black professionals more than any role in tech.
On Monday, March 29, Tianhui Michael Li, the founder and president of The Data Incubator, a data-science training and placement firm, will be our webinar guest on Ask HBR, and he will look at building less-biased AI by hiring more diverse AI and technology teams.
Li, author of the recent HBR article “To Build Less-Biased AI, Hire a More-Diverse Team<https://t.a.email.hbr.org/r/?id=h766d80c1%2Cdde367e%2Cdde3684&s=A-BPsxZxXA4UrqQLHUgnskX-Lytdgmlv-cpkBNvcd54,”> will offer concrete recommendations for ways to hire more diverse talent while boosting team performance.
For insights on combating bias in AI and developing more diverse AI and tech talent in your organization, join us and Michael Li on March 29. Submit your questions in advance to: askhbr@hbr.org<mailto:askhbr@hbr.org>.
REGISTER NOW<https://t.a.email.hbr.org/r/?id=h766d80c1%2Cdde367e%2Cdde3685&s=LS12Fd1P3n8hRiKEua30ziPFL-jTkIYW06MHm-0uTEQ>
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