tl;dr I’m pro-actively consuming more media featuring women, e.g. by going through lists like this on wikipedia: list of 21st century women by occupation
Lately I’ve been thinking* about how to identify what might be contributing to my “unconscious” biases, and actively counteracting them. The idea is to track what sort of daily input we’re consuming — as a silly example, if we almost always encounter bulldogs as aggressive dangerous dogs, then when we see a bulldog we’ll assume it’s aggressive by default.
* Due to another conversation, saved for another blog post, about concrete tips for diversifying applicant pools. Many of my friends are now in hiring positions, and facing frustrations with working without support in their companies, even from the Human Resources department, on how to diversify the applicant pool even, not even the company itself.
In the past I’ve thought about creating machine learning algorithms to identify the sort of consistent image I see on, for instance, youtube of 8tracks.com or other sites, where techno seems to be accompanied by scantily clad women (or just closeups of their butts or their busts or feet or whatever). For instance, doing some sort of gender swap in with hot pics of men instead.
However, an even simpler thing to do, is simply to tally the number of hours I spend consuming media, both well-intentioned media and not, which doesn’t counteract the consistent image I get day-to-day of not seeing women in positions of power, importance, and influence.
For instance, on average I likely spend 10+ hours a week nowadays listening to podcasts, of which maybe 20% is narrated by a woman. I have female peers, but I don’t interact often at all with women in positions of power / senior women.
As a result, I’d like to consume media, not specifically about women, but authored by women. Women founders, giving talks about how they created their companies; women CEOs, talking about making billion dollar decisions; women keynote speakers, and other ordinary forms of everyday media (well, ordinary to me).
I’m actually having a hard time finding a “stream” or pre-made mix of such material. But I think I’ll start out by finding lists of movies. I looked through them, and now I’m making a prioritizing of movies to watch:
- Ocean’s 8
- Legally Blonde
- Suffragette (film)
- Hidden Figures
- Crazy Rich Asians
- Star Wars: The Last Jedi
- Sicario (2015)
- Erin Brockovich (2000)
- Hunger Games (#2, #3)
- Flashdance (1983)
- Lady Bird
- Gone girl
- Nothing But The Truth
- Mad Max: Fury Road (2015)
- The Avengers
- Atomic Blonde
- Ghost in the Shell
- Star Wars: The Force Awakens
- Wonder Woman
- The Sound of Music
- Hunger Games (#1)
- Kill Bill
- Kiki’s Delivery Service
- Princess Mononoke
- Jane Austen: Gone with the Wind
- Pride and Prejudice
Eh? TV series
- The Great Jang-Geum (TV series.. though it’s set in those old palatial times)
Well, those were a really partial and unordered list of movies to watch. What I really want to find nowadays are online videos (talks) and especially podcasts, but it’s hard to find ones that don’t focus at all on the fact that they’re women…. A perfectly fine thing, just not what I’m looking for. I don’t need to be any more sensitized; I actively work on being de-sensitized. I just want to counter my unconscious bias by explicitly feeding myself a better “diet” of media consumption.
In the meantime, back to learning about the OpenAI gym, POMDPs, numerical methods, all that jazz.
- Audrey Hepburn
Updates (further sources I found) 17 Oct 2018:
- Search results for “biography” | Kanopy
- Catherine the Great – Not Quite Catherine Yet – Extra History – #1 – YouTube
- Category:Female foreign ministers – Wikipedia
- 25 women in robotics you need to know about – 2018 | Robohub