Bias in the tech workplace or technology relating to the betterment or destruction of race relations.
Technology and Race (21)
Find narratives by ethical themes or by technologies.
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- 5 min
- Venture Beat
- 2021
Relates the story of Google’s inspection of Margaret Mitchell’s account in the wake of Timnit Gebru’s firing from Google’s AI ethics division. With authorities in AI ethics clearly under fire, the Alphabet Worker’s Union aims to ensure that workers who can ensure ethical perspectives of AI development and deployment.
- Venture Beat
- 2021
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- 5 min
- Venture Beat
- 2021
Google targets AI ethics lead Margaret Mitchell after firing Timnit Gebru
Relates the story of Google’s inspection of Margaret Mitchell’s account in the wake of Timnit Gebru’s firing from Google’s AI ethics division. With authorities in AI ethics clearly under fire, the Alphabet Worker’s Union aims to ensure that workers who can ensure ethical perspectives of AI development and deployment.
Discussion Prompts:
How can bias in tech monopolies be mitigated? How can authorities on AI ethics be positioned in such a way that they cannot be fired when developers do not want to listen to them?
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- 4 min
- OneZero
- 2020
A group of “Face Queens” (Dr. Timnit Gebru, Joy Buolamwini, and Deborah Raji) have joined forces to do important racial justice and equity work in the field of computer vision, struggling against racism in the industry to whistleblow against biased machine learning and computer vision technologies still deployed by companies like Amazon.
- OneZero
- 2020
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- 4 min
- OneZero
- 2020
Dr. Timnit Gebru, Joy Buolamwini, Deborah Raji — an Enduring Sisterhood of Face Queens
A group of “Face Queens” (Dr. Timnit Gebru, Joy Buolamwini, and Deborah Raji) have joined forces to do important racial justice and equity work in the field of computer vision, struggling against racism in the industry to whistleblow against biased machine learning and computer vision technologies still deployed by companies like Amazon.
Discussion Prompts:
How can the charge led by these women for more equitable computer vision technologies be made even more visible? Should people need high degrees to have a voice in fighting against technologies which are biased against them? How can corporations be made to listen to voices such as those of the Face Queens?
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- 5 min
- Business Insider
- 2020
This article tells the story of Timnit Gebru, a Google employee who was fired after Google refused to take her research on machine learning and algorithmic bias into full account. She was terminated hastily after sending an email asking Google to meet certain research-based conditions. Gebru is a leading expert in the field of AI and bias.
- Business Insider
- 2020
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- 5 min
- Business Insider
- 2020
One of Google’s leading AI researchers says she’s been fired in retaliation for an email to other employees
This article tells the story of Timnit Gebru, a Google employee who was fired after Google refused to take her research on machine learning and algorithmic bias into full account. She was terminated hastily after sending an email asking Google to meet certain research-based conditions. Gebru is a leading expert in the field of AI and bias.
Discussion Prompts:
How can tech monopolies dismiss recommendations to make their technologies more ethical? How do bias ethicists such as Gebru get onto a more unshakeable platform? Who is going to hold tech monopolies more accountable? Should these monopolies even by trying to fix their current algorithms, or might it be better to just start fresh?
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- 12 min
- Kinolab
- 2016
“Hidden Figures” chronicles the journeys of Katherine Johnson (Taraji P. Henson), Dorothy Vaughan (Octavia Spencer), and Mary Jackson (Janelle Monáe), three black women who worked on the space missions at the Langley Research Center in Hampton, Virginia in 1961. All three women persist against segregation and abject racism as they climb the ladder and make important contributions to the space mission. While Katherine becomes the first black woman on Al Harrison’s Space Task Group, Mary Jackson pursues her dream of becoming an engineer at NASA by petitioning to take courses at an all white school, and Dorothy Vaughan attempts to learn the programming language Fortran in order to ensure that herself and fellow human computers are not replaced by the newest IBM 7090 computer.
- Kinolab
- 2016
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- 12 min
- Kinolab
- 2016
Hidden Figures Part II: Goals of Equity and Women of Color in the Workplace
“Hidden Figures” chronicles the journeys of Katherine Johnson (Taraji P. Henson), Dorothy Vaughan (Octavia Spencer), and Mary Jackson (Janelle Monáe), three black women who worked on the space missions at the Langley Research Center in Hampton, Virginia in 1961. All three women persist against segregation and abject racism as they climb the ladder and make important contributions to the space mission. While Katherine becomes the first black woman on Al Harrison’s Space Task Group, Mary Jackson pursues her dream of becoming an engineer at NASA by petitioning to take courses at an all white school, and Dorothy Vaughan attempts to learn the programming language Fortran in order to ensure that herself and fellow human computers are not replaced by the newest IBM 7090 computer.
Discussion Prompts:
How is the history of the oppression of Black people in America responsible for a lack of diversity in workplaces, including those involving science and technology in the present? What do technology companies in the current day need to consider in order to ensure that their workforce is diverse and equitable? What does the specific case of Dorothy being initially denied access to the Fortran book reveal about the past and present accessibility of minority groups to fluency in digital technologies? What needs to happen inside of and outside of the technology industry to ensure better opportunities for women of color in technology-focused workplaces? What role does implicit bias play in all of these considerations?
Hidden Figures: I Work Like a Dog-
- 10 min
- Kinolab
- 2018
This narrative provides two different case studies of remote-controlled vehicles in the story of T’Challa’s attempts to properly rule his country, Wakanda. T’Challa, also known as the superhero Black Panther, makes use of this technology to put a stop to criminals who threaten his people and his power. In the first clip, T’Challa and his companions track down Ulysses Klaue, a notorious criminal who formerly stole from Wakanda, down the streets of Busan, Korea. In the second clip, agent Everett Ross makes use of the technology to pilot a drone, which he uses to shoot down autonomous drones carrying weapons from Wakanda to the rest of the world.
- Kinolab
- 2018
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- 10 min
- Kinolab
- 2018
Remote Controlled Driving of Vehicles
This narrative provides two different case studies of remote-controlled vehicles in the story of T’Challa’s attempts to properly rule his country, Wakanda. T’Challa, also known as the superhero Black Panther, makes use of this technology to put a stop to criminals who threaten his people and his power. In the first clip, T’Challa and his companions track down Ulysses Klaue, a notorious criminal who formerly stole from Wakanda, down the streets of Busan, Korea. In the second clip, agent Everett Ross makes use of the technology to pilot a drone, which he uses to shoot down autonomous drones carrying weapons from Wakanda to the rest of the world.
Discussion Prompts:
When operating vehicles remotely, how is it easy for the driver to become desensitized to the surroundings of the vehicle? Might entertainment technology such as violent video games play a role in such desensitization? What phenomena of a street or other driving environment may or may not be abstracted into a digital map of the vehicle’s surroundings?
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- 27 min
- Cornell Tech
- 2019
Podcast about worker quantification in factors such as hiring, productivity and more. Dives into the discussion on why we should attempt a fair making of algorithms. Warns specifically about how algorithms can find “proxy variables” to approximate for cultural fits like race or gender even when the algorithms is supposedly controlled for these factors.
- Cornell Tech
- 2019
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- 27 min
- Cornell Tech
- 2019
Quantifying Workers
Podcast about worker quantification in factors such as hiring, productivity and more. Dives into the discussion on why we should attempt a fair making of algorithms. Warns specifically about how algorithms can find “proxy variables” to approximate for cultural fits like race or gender even when the algorithms is supposedly controlled for these factors.
Discussion Prompts:
What are the dangers of having an algorithm involved in the hiring process? Is efficiency worth the cost in this scenario? Can humans ever be placed in a binary context?
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