Re: Latest editor's draft of "Ethical Principles for Web Machine Learning"

Thanks for sending this link along, Jason. By curious happenstance, I ended up in a meeting late yesterday with one of the authors cited in the draft, Ninareh Mehrabi (co-author of "A Survey on Bias and Fairness in Machine Learning" https://arxiv.org/pdf/1908.09635.pdf). Looks like he has also co-authored other publications along such lines, for instance "Ethical Considerations in AI-Based Recruitment" (DOI: 10.1109/ISTAS48451.2019.8937920<https://doi.org/10.1109/ISTAS48451.2019.8937920>). [We may want to add that to the bibliography, by the way.]

Ninareh Mehrabi currently has a newly funded National Science Foundation project<https://www.nsf.gov/awardsearch/showAward?AWD_ID=2235916&HistoricalAwards=false> which he was discussing. Here's a summary paragraph about their project:
"Disfluencies in speech are common artifacts in conversation, but they are especially prevalent in individuals who stutter, a community of more than 70 million people worldwide. It is well-documented that people who stutter consistently experience employment discrimination, diminished labor market outcomes, and societal stigma. The increasingly pervasive use of exclusionary voice-activated artificial intelligence (AI), which are designed, trained, and tested without considering communication that varies from societal norms, can act as a barrier to daily life participation and employment access for communities such as individuals who stutter. Worse, such technology can actively discriminate against people with speech differences in employment contexts. Therefore, there is an immediate and compelling need for efforts to reduce these barriers and empower people with communication differences and disorders to fully and equitably access all forms of speech recognition systems, including personal voice assistants, automated phone interfaces, and job-preparation and hiring software."

He had some great observations about the very real ethical considerations of the societal barriers that current AI technology is placing for people with speech related disabilities. It made for an interesting connection to the great presentation that Lionel provided in our RQTF meeting earlier the same day.

--Steve



Steve Noble
Principal Researcher, Accessibility
Psychometrics & Testing Services

Pearson

502 969 3088
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________________________________
From: Jason White <jason@jasonjgw.net>
Sent: Wednesday, February 8, 2023 11:53 AM
To: public-rqtf@w3.org <public-rqtf@w3.org>
Subject: Latest editor's draft of "Ethical Principles for Web Machine Learning"


https://webmachinelearning.github.io/webmachinelearning-ethics/

(Revised as of November last year.)