Courtesy of google.com
Last week, I wrote a blog capped by a cartoon which amused my web manager. (Click) It exposed the gobbledygook terms that accrue to Artificial Intelligence (AI). Apparently, the alphabet soup expresses different purposes. Or, as a tweet from a recent article revealed, “It’s AI if you’re trying to raise money, ML [Machine learning] when you’re trying to hire developers and statistics when you’re actually doing it.” (Robo-Ethics, by Ellen Huet, Bloomberg Businessweek, May 21, 2018, pg. 50.)
Whether all this computer speak is necessary or merely intended to mystify the public, I don’t know. I do believe, early programmers were dreamers who wanted to give shape to the virtual world. I also believe their mistake was in putting too much faith in data collection. The personal information of the many is a temptation that can lead to abuse if left as a monopoly in the hands of a few men.
On the first point, it’s hard to argue against the successes of big data in helping shape our understanding of the world. It has led to the Higgs boson God particle discovery. It has given us new insights into the human body. (Click) Dark matter has become less dark because of it. (Click)
Carrying these wonders to extreme, I wrote a tongue-in-cheek blog that questioned whether we might one day trust robots to serve as judges. (Click) In reality, I don’t believe we will. Data collection, no matter how humongous, brings us no closer to an understanding of what’s fair than can the human heart. In fact, the human heart is likely to skew our decisions and the data we collect.
Computer scientist Kristian Lum gives us an example of how crime statistics become skewed based on who gets arrested and where. “…drug crimes are disproportionately taking place in communities of color.” (“Robo-Ethics,” by Ellen Huet, Bloomberg Businessweek, May 32, 2018, pg. 50.P When researchers applied algorithms to that data set, they found “It would perpetuate or perhaps amplify the historical bias already in the data.” (Ibid, pg. 50.)
Her statement brings me to my second point, the one about information kept in the hands of a few men. The paucity of women in computer science affects the type of data we collect, data being no fixed thing as Lum points out. (Ibid pg. 50.) Unless women plant their flag in the virtual world, they will lose it to the same patriarchy that has dominated the real one for thousands of years.
(photo of founders of Apple, Google, Microsoft, Facebook, Amazon)
