🚨Groundbreaking Scholarship! At long last, science has bravely confirmed the shocking news: Pumping your body full of cross-sex hormones might mess with your fertility. Yes, after hundreds of pages of jargon and a systematic review (bless the PubMed warriors), the experts have discovered that: - Testosterone does things to ovaries. - Estrogen does things to testes. - Cutting off natural hormones affects baby-making. Truly revolutionary. (fb)

𝐂𝐚𝐧 𝐓𝐫𝐮𝐦𝐩’𝐬 𝐀𝐈 𝐄𝐎 𝐑𝐞𝐚𝐥𝐥𝐲 𝐅𝐢𝐱 𝐀𝐈 𝐁𝐢𝐚𝐬? Universities are likely to de-emphasize this AI bias issue; after all, many would be guided by the principle of unencumbered free speech. Universities will likely be concerned about student cheating, the deskilling of reading and writing, and the augmentation or replacement of faculty with AI tutors. Arguably, a sense of morality and observed progress can center the merit, colorblindness, and individual-centered value system in AI models. There has been significant historical progress over the past half-century to justify this approach to addressing current AI bias. In the arena of societal issues, legislative and judicial opinions have joined with cultural shifts. Take the example of Loving v. Virginia (1967), which struck down bans on interracial marriage. Paralleling that change in law, the Gallup Poll has measured the cultural acceptance of interracial marriage from about four percent in 1958 to over 94 percent in recent times. This is just one metric, but it dovetails with the words of Chief Justice John Roberts (2007): “The way to stop discrimination on the basis of race is to stop discriminating on the basis of race.” That formula is a short step away from colorblindness. The more recent case Students for Fair Admission, Inc. v President and Fellows of Harvard College presses the shift further away from equity to equality. It held that college race-based admissions programs violate the Equal Protection Clause of the Fourteenth Amendment. My experience suggests that the fairness-aware and precautionary principles that govern AI models would likely lead to a workaround. It would assume the prevalence of systemic racism regardless of significant progress in this arena. Perhaps I am wrong, but NIST testing along these lines would discover and reform persistent algorithmic bias that assumes facts not in evidence and weighs its assumptions accordingly. Indeed, there remains ongoing tension between the various approaches to values and risk factors discussed here. Implementing the Preventing Woke AI in the Federal Government faces significant challenges. In my view, these are resolvable. If you’re wondering how a Trump-informed chatbot would respond to the question “Is there still racism in America?” the reply would likely follow an observation made by Shelby Steele: 𝑇ℎ𝑒 𝑜𝑝𝑝𝑟𝑒𝑠𝑠𝑖𝑜𝑛 𝑜𝑓 𝑏𝑙𝑎𝑐𝑘 𝐴𝑚𝑒𝑟𝑖𝑐𝑎𝑛𝑠 𝑖𝑠 𝑜𝑣𝑒𝑟 𝑤𝑖𝑡ℎ. 𝑌𝑒𝑠, 𝑡ℎ𝑒𝑟𝑒 𝑎𝑟𝑒 𝑒𝑥𝑐𝑒𝑝𝑡𝑖𝑜𝑛𝑠. 𝑅𝑎𝑐𝑖𝑠𝑚 𝑤𝑜𝑛’𝑡 𝑔𝑜 𝑎𝑤𝑎𝑦 — 𝑖𝑡 𝑖𝑠 𝑒𝑛𝑑𝑒𝑚𝑖𝑐 𝑡𝑜 𝑡ℎ𝑒 ℎ𝑢𝑚𝑎𝑛 𝑐𝑜𝑛𝑑𝑖𝑡𝑖𝑜𝑛, 𝑗𝑢𝑠𝑡 𝑙𝑖𝑘𝑒 𝑠𝑡𝑢𝑝𝑖𝑑𝑖𝑡𝑦. 𝐵𝑢𝑡 𝑡ℎ𝑒 𝑜𝑙𝑑𝑒𝑟 𝑓𝑜𝑟𝑚 𝑜𝑓 𝑜𝑝𝑝𝑟𝑒𝑠𝑠𝑖𝑜𝑛 𝑖𝑠 𝑔𝑜𝑛𝑒 … 𝐵𝑒𝑓𝑜𝑟𝑒 𝑖𝑡 𝑤𝑎𝑠 𝑎 𝑞𝑢𝑒𝑠𝑡𝑖𝑜𝑛 𝑜𝑓 𝑏𝑙𝑎𝑐𝑘 𝑢𝑛𝑖𝑡𝑦 𝑎𝑛𝑑 𝑝𝑟𝑜𝑡𝑒𝑠𝑡; 𝑛𝑜 𝑚𝑜𝑟𝑒, 𝑖𝑡 𝑖𝑠 𝑛𝑜𝑤 𝑢𝑝 𝑡𝑜 𝑢𝑠 𝑎𝑠 𝑖𝑛𝑑𝑖𝑣𝑖𝑑𝑢𝑎𝑙𝑠 𝑡𝑜 𝑔𝑒𝑡 𝑎ℎ𝑒𝑎𝑑. 𝑂𝑢𝑟 𝑝𝑟𝑜𝑏𝑙𝑒𝑚 𝑛𝑜𝑤 𝑖𝑠 𝑛𝑜𝑡 𝑟𝑎𝑐𝑖𝑠𝑚, 𝑜𝑢𝑟 𝑝𝑟𝑜𝑏𝑙𝑒𝑚 𝑖𝑠 𝑓𝑟𝑒𝑒𝑑𝑜𝑚. May the transformation begin. Read Joe Nalven's latest: (fb)