TA-fall-2023 Letters to a Young Technologist. Note: there are 5 total letters on this webpage. (https://letterstoayoungtechnologist.com/What-is-Technology) Confucius and the Whistleblower by Peter Wei (https://www.palladiummag.com/2022/03/04/confucius-and-the-whistleblower/) The Ones Who Walk Away From Omelas by Ursula K LeGuin (https://shsdavisapes.pbworks.com/f/Omelas.pdf)
Slick Tom Cruise Deepfakes Signal That Near Flawless Forgeries May Be Here by Emma Bowman (https://www.npr.org/2021/03/11/975849508/slick-tom-cruise-deepfakes-signal-that-near-flawless-forgeries-may-be-here) Using AI to Detect Seemingly Perfect Deep-Fake Videos by Edmund L. Andrews (https://hai.stanford.edu/news/using-ai-detect-seemingly-perfect-deep-fake-videos) Watch: Fairness Accountability Transparency and Ethics in Computer Vision (https://www.youtube.com/watch?v=0sBE5OyD7fk&list=PLMfRT7Ik6baEjup3PAqbcCbp5dlP4TclS&index=31&ab_channel=RemiDenton)
Race After Technology, by Ruha Benjamin, chapter 1 (link coming soon) U.S. Watched George Floyd Protests in 15 Cities Using Aerial Surveillance, by Zolan Kanno-Youngs (ProQuestDocuments-2023-08-21.pdf ) The Problem with Blaming Robots for Taking our Jobs by Jane Hu (The Problem with Blaming Robots for Taking Our Jobs _ The New Yorker.pdf )
Autonoumous Vehicle Case Study (Autonomous Vehicles Case Study.pdf ) Never Mind the Trolley: The Ethics of Autonomous Vehicles in Mundane Situations (Himmelreich-NeverMindTrolley-2018.pdf )
Captcha if you can: how you’ve been training AI for years without realising it by James O’Malley (https://www.techradar.com/news/captcha-if-you-can-how-youve-been-training-ai-for-years-without-realising-it) Underpaid Workers are being forced to train biased AI on mechanical turk by Aliide Naylor (https://www.vice.com/en/article/88apnv/underpaid-workers-are-being-forced-to-train-biased-ai-on-mechanical-turk) The Trust Imperative: A Framework for Ethical Data Use (https://bigdata.fpf.org/wp-content/uploads/2015/11/Etlinger-The-Trust-Imperative.pdf)
The Problem with Intelligence, by Stephen Cave (https://dl.acm.org/doi/pdf/10.1145/3375627.3375813) The Experience Machine (https://rintintin.colorado.edu/~vancecd/phil3160/Nozick1.pdf) Don’t be fooled by charistmatic robots, by Karla Erickson (Don’t be fooled by charismatic robots _ Salon.com.pdf )
In Scramble to respond to Covid-19, hospitals turned to models with high risk of bias, by Elise Reuter. (https://medcitynews.com/2021/04/in-scramble-to-respond-to-covid-19-hospitals-turned-to-models-with-high-risk-of-bias/) More than a Glitch: confronting race, gender, and ability bias in tech by Meredith Broussard. Chapter 8 (https://web.s.ebscohost.com/ehost/ebookviewer/ebook/bmxlYmtfXzMzMDkwNzNfX0FO0?sid=7cc4f64f-efb3-4910-bfa8-1d874c2f538f@redis&vid=0&format=EB&lpid=lp_135&rid=0)
Limiting racial disparities and bias for wearable devices in health science research, by Colvonen et. al (https://academic.oup.com/sleep/article/43/10/zsaa159/5902283)
Invisible Women, by Caroline Criado Perez. Chapters 10 & 11 (https://web.s.ebscohost.com/ehost/detail/detail?vid=0&sid=68078bd0-62d0-474a-9f19-ce810b963815%40redis&bdata=JnNpdGU9ZWhvc3QtbGl2ZQ%3d%3d#AN=2030243&db=nlebk)
The Tyranny of Metrics by Jerry Z. Muller. Chapters 1,2, and 9 (https://ebookcentral.proquest.com/lib/grinnell-ebooks/detail.action?docID=5214923)
