I never thought much about Wikipedia until its pages appeared at the top of Google searches – and not just Google. If you ask Siri or Alexa a question, chances are the source of your answer is Wikipedia as well. Hundreds of AI platforms use Wikipedia data; machine learning trains it. So if women are missing there, they will be missing elsewhere as well.
Women in Science disappeared long before Wiki, of course – in press coverage, the main billing at meetings, the appearance on billboards. They were also not on my radar when I started writing about science decades ago and introduced myself to the “March meeting” from the American Physical Society. The March meeting is a mecca for nerds: nearly 10,000 physicists gather to present their findings on “condensed matter,” which ranges from quantum computers to lasers to intelligent materials. AI and all nano.
A sympathetic black woman noticed my obvious confusion and helped guide me through the maze of discussions, panels, sessions. She was Shirley Ann Jackson, who I later learned was the first black woman to earn a doctorate in theoretical physics from MIT (where, she said, she was mistaken for a maid) . She took me to the reception of women in physics. I was really impressed. Many more physicists were women (and vice versa) than I had imagined. Where were they? Where was i?
Decades later, I had a similar wake-up call at an exclusive Aspen meeting of top physicists in what was then known as string theory – addressing the most fundamental questions of space, time, energy, things. I expected a lot of the material to be exotic and unfamiliar. What seemed really exotic and unfamiliar were the three black men from the elite little group.
For most people, the description of “theoretical physicist” does not immediately conjure up the image of a black person. (Neil de Grasse Tyson is great, but one example doesn’t count, and he’s not one of that particular tribe.) After the Aspen reunion, my ground truth changed. I could imagine black men as theoretical physicists with no problem because I had met them, interviewed them, dragged them.
Then it hit me: pretty much all the female physicists that I know, and all the black female physicists that I know, are people that I have met in person. I hadn’t even noticed their absence until their presence hit me in the face.
My portals are not that diverse. This is why Wikipedia in the Age of the Crown worried me.
A lot of people say they only use Wikipedia as a starting point, as a first reference. After all, everyone knows this is crowdsourcing. It is proudly non-expert. A community of editors ultimately decides what is in, what goes out, what matters, what is true. Because there are so many of them (250,000 edits a day, according to one source), the idea is that the truth will go away.
Yet Wikipedia’s top ranking on Google gives it a credibility and authority that distorts what it is: community consensus. “It’s a problem”, according to Atilus, a leading digital marketing company. In an audit for a client using top notch SEO software, Atilus found Wikipedia at the top or near the top, over and over again, often with a prominent sidebar. On his blog, Atilus asked a not always hypothetical question to illustrate the problem: would you rather trust a doctor who has had rigorous training or people who spend time in health-related or health-related discussion forums? an intern blogging about heart health? This is a big simplification, given that Wiki entries are meant to be dual-sourced and edited. But even when it works, it’s not even close to the truth on the ground.
Granted, Wikipedia isn’t the only source of content that creeps into everything, ubiquitous and inevitable. Could it be your mother or The New York Times. What gives Wikipedia a central place in data heaven is that the popular algorithms that guide us through our noses go to the site to learn. AI reinforces the prejudices that are submitted to them. “Big Data processes codify the past,” writes Kathy O’Neil in her book Weapons of mathematical destruction.