Describes limitations and shortfalls of current digital technologies, particularly when compared to human capabilities.
Limitations of Digital Technologies (22)
Find narratives by ethical themes or by technologies.
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- 7 min
- The Verge
- 2019
Reliance on “emotion recognition” algorithms, which use facial analysis to infer feelings. Credibility of the results in question based on inability of machines to recognize abstract nuances.
- The Verge
- 2019
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- 7 min
- The Verge
- 2019
AI ‘Emotion Recognition’ Can’t Be Trusted
Reliance on “emotion recognition” algorithms, which use facial analysis to infer feelings. Credibility of the results in question based on inability of machines to recognize abstract nuances.
Discussion Prompts:
Can digital artifacts potentially detect human emotions correctly? Should our emotions be read by machines? Are emotions too complex for machines to understand? How is human agency impacted by discrete AI categories for emotions?
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- 4 min
- VentureBeat
- 2020
A study on the engine of TaskRabbit, an app which uses an algorithm to recommend the best workers for a specific task, demonstrates that even algorithms which attempt to account for fairness and parity in representation can fail to provide what they promise depending on different contexts.
- VentureBeat
- 2020
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- 4 min
- VentureBeat
- 2020
Researchers Find that Even Fair Hiring Algorithms Can Be Biased
A study on the engine of TaskRabbit, an app which uses an algorithm to recommend the best workers for a specific task, demonstrates that even algorithms which attempt to account for fairness and parity in representation can fail to provide what they promise depending on different contexts.
Discussion Prompts:
Can machine learning ever be enacted in a way that fully gets rid of human bias? Is bias encoded into every trained machine learning program? What does the ideal circumstance look like when using digital technologies and machine learning to reach a point of equitable representation in hiring?
- Wired
- 2021
Youtube algorithm’s struggle to distinguish chess-related terms from hate speech and abuse has revealed shortcomings in artificial intelligence’s ability to moderate online hate speech. The incident reflects the need to develop digital technologies capable of processing natural languages with a sufficient degree of social sensitivity.
- Wired
- 2021
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- Wired
- 2021
Why a YouTube Chat About Chess Got Flagged for Hate Speech
Youtube algorithm’s struggle to distinguish chess-related terms from hate speech and abuse has revealed shortcomings in artificial intelligence’s ability to moderate online hate speech. The incident reflects the need to develop digital technologies capable of processing natural languages with a sufficient degree of social sensitivity.
Discussion Prompts:
Where do you draw the line between freedom of speech and online community conduct and regulations? What are some problems you think AI will experience in moderating hate speech like slurs?
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- 10 min
- MIT Technology Review
- 2020
This article explains the ethical warnings of Timnit Gebru against training Natural Language Processing algorithms on large language models developed on sets of textual data from the internet. Not only does this process have a negative environmental impact, it also still does not allow these machine learning tools to process semantic nuance, especially as it relates to burgeoning social movements or countries with lower internet access. Dr. Gebru’s refusal to retract this paper ultimately lead to her dismissal from Google.
- MIT Technology Review
- 2020
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- 10 min
- MIT Technology Review
- 2020
We read the paper that forced Timnit Gebru out of Google. Here’s what it says.
This article explains the ethical warnings of Timnit Gebru against training Natural Language Processing algorithms on large language models developed on sets of textual data from the internet. Not only does this process have a negative environmental impact, it also still does not allow these machine learning tools to process semantic nuance, especially as it relates to burgeoning social movements or countries with lower internet access. Dr. Gebru’s refusal to retract this paper ultimately lead to her dismissal from Google.
Discussion Prompts:
How should models for training NLP algorithms be more closely scrutinized? What sorts of voices are needed at the design table to ensure that the impact of such algorithms are consistent across all populations? Can this ever be achieved?
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- 7 min
- The Verge
- 2020
PULSE is an algorithm which can supposedly determine what a face looks like from a pixelated image. The problem: more often than not, the algorithm will return a white face, even when the person from the pixelated photograph is a person of color. The algorithm works through creating a synthetic face which matches with the pixel pattern, rather than actually clearing up the image. It is these synthetic faces that demonstrate a clear bias toward white people, demonstrating how institutional racism makes its way thoroughly into technological design. Thus, diversity in data sets will not full help until broader solutions combatting bias are enacted.
- The Verge
- 2020
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- 7 min
- The Verge
- 2020
What a machine learning tool that turns Obama white can (and can’t) tell us about AI bias
PULSE is an algorithm which can supposedly determine what a face looks like from a pixelated image. The problem: more often than not, the algorithm will return a white face, even when the person from the pixelated photograph is a person of color. The algorithm works through creating a synthetic face which matches with the pixel pattern, rather than actually clearing up the image. It is these synthetic faces that demonstrate a clear bias toward white people, demonstrating how institutional racism makes its way thoroughly into technological design. Thus, diversity in data sets will not full help until broader solutions combatting bias are enacted.
Discussion Prompts:
What potential harms could you see from the misapplication of the PULSE algorithm? What sorts of bias-mitigating solutions besides more diverse data sets could you envision? Based on this case study, what sorts of real-world applications should facial recognition technology be trusted with?
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- 10 min
- The New Yorker
- 2020
This article contextualizes the BLM uprisings of 2020 in a larger trend of using social media and other digital platforms to promote activist causes. A comparison between the benefits of in-person, on-the-ground activism and activism which takes place through social media is considered.
- The New Yorker
- 2020
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- 10 min
- The New Yorker
- 2020
The Second Act of Social Media Activism
This article contextualizes the BLM uprisings of 2020 in a larger trend of using social media and other digital platforms to promote activist causes. A comparison between the benefits of in-person, on-the-ground activism and activism which takes place through social media is considered.
Discussion Prompts:
How should activism in its in-person and online forms be mediated? How does someone become an authority, for information or otherwise, on the internet? What are the benefits and detriments of the decentralization of organization afforded by social media activism?