The last few months have taught us a lot about America. Our country is facing the twin crises of COVID-19 and racism. While the former is novel and the current crisis is in part (actually, largely) due to a lack of leadership by our top political officials, the latter is perhaps the oldest problem that stubbornly never disappears. In this post, I discuss, in order: policing (including one benign encounter with a police officer), anti-racism in academia and AI, and what I will try to do for my anti-racist education. I will discuss what I am reading, where I am donating to, and what I can commit to doing in the near future.

Policing. I was as appalled as many others from watching videos of police treatment of African-Americans in this country, especially with the George Floyd case, and I share the concerns many have over police conduct against Blacks. On the other hand, I also believe there has to be a police presence — or law enforcement more broadly — of some sort. The 1969 Murray-Hill riots in Canada, for example, where a strike by Montreal police lead to widespread lawless activity, demonstrates just how badly society depends on law enforcement, and makes me worry that the absence of police presence can lead to anarchy.

Growing up, I was told to be extra cautious around the police, and to make my hearing disability clear and upfront to any police officers to avoid misunderstandings. There have been tragic cases of deaf people being harmed and even killed by law enforcement officers who presumed a deaf person could hear and was engaging in indifference or disobedience of law enforcement commands. I know my situation is not the same as and is far milder than what many Blacks experience. While I am not white, people often think I am white by my physical appearance, so my racial composition has not been problematic.

In my life, I have been stopped by the police a grand total of zero times. Well, except for (arguably) one case where Berkeley was running a random “sobriety test” on a Friday night, and police officers were stopping every car on the street that led to my apartment. That night I wasn’t driving home from a party; I was working in the robotics lab until 9:00pm.

When it was my turn, my conversation with the police officer went like this:

Me: Hello. Nice to meet you. Just to let you know I’m deaf and may not fully understand everything you say. But I’m happy to answer any questions you have. I am curious about what is happening here.

Police officer [smiling]: Gotcha. This is a random test that we’re having to check all drivers here. In any case I don’t smell any alcohol on you, so you’re free to go.

That’s it! I have otherwise never spoken to a police officer in any driving-related context, and my few other interactions with police officers have similarly been under extraordinarily uneventful and non-threatening situations. When people such as United States Senator Tim Scott of South Carolina get stopped by the police at the Senate as he describes in this interview, then I wonder how our society can fix this.

That said, I also want to take a data-driven approach to let sober facts dictate my beliefs, rather than emotions or one-time events. Dramatic videos only show a small fraction of all police activity. Given the authority, trust, and power we give to police officers, however, the bar for their code-of-conduct should be high.

To summarize, I don’t think we should get rid of the police. I do believe we need to continue and improve training of police officers, the majority of whom do not have a college education, and to provide support (and better pay) to the good police officers while firing the bad ones. It may also be helpful if we can collectively reduce the need for police officers to deal with non-critical cases such as parking tickets and jaywalking so that they can prioritize the truly dangerous criminals. I can’t claim to be an expert on policing, so I will continue learning as much as I can about this area.

Anti-Racism in Academia and Artificial Intelligence. The Berkeley EECS department, like many similar ones in the country, is heavily dominated by Whites and Asians, and has very few Blacks, so discussion of race and racism (at least from my conversations) tend to involve the White/Asian dynamic with limited commentary about other groups.

The good news is that there’s been recent discussion about how to be anti-racist, with increased focus on Blacks. There was an email sent out by the chairs of the department which linked to statements by much of the faculty affirming their support for anti-racism. Several department-wide reading groups, email lists, and committees now exist for supporting anti-racism. A PhD student in the department, Devin Guillory, has a manuscript on combating anti-Blackness with a specific focus on the Artificial Intelligence community.

I think it’s important for the AI community to discuss the broader impacts of how our technologies can be used both for good and for bad, particularly when they can exacerbate existing disparities. One recent technology that is worth discussing is facial recognition. While I don’t do research in this area, my robotics research often uses technologies based on Deep Convolutional Neural Networks that form the bedrock for facial recognition.

Rarely is it easy to admit that one is wrong, but I think I was wrong about my initial stance on facial recognition. When I first learned about the capabilities of Convolutional Neural Networks from CS 280 at Berkeley and then the associated facial recognition literature, I dreamed of society deploying the technology to detect and catch criminals with surgical precision. (I don’t have an earlier blog post or other writing about this, so you’ll have to take my word on it.)

Since then, I’ve done almost a complete reversal and now think we should limit facial recognition research and technology, at least until we can come up with solutions that explicitly consider minority interests. Here’s why:

  • I share concerns over potential inaccuracies in the technology when it pertains to racial minorities. For example, a landmark 2018 paper by Joy Buolamwini and Timnit Gebru showed that facial recognition technologies (at least at the time of publication) were far more inaccurate on people with darker skin. While the technology may have gotten more accurate on people with darker skin since it was published, a recent news article about a wrongful arrest of a black man due to facial recognition makes me anxious.

  • I also worry about facial recognition being used to limit and control personal freedom. I see the extreme case of facial recognition technologies in China, where particularly in Xinjiang, they have an extensive surveillance system over the Uighur Muslims. While it’s challenging to make imperfect comparisons across different countries and governance systems, I hope that the United States does not reach this level of surveillance, and the situation there should serve as a warning sign for American residents to be wary of facial recognition systems in our own communities.

When the ACM made the following tweet a few months ago, I was heartened to see pushback by many members of the computer science community. I hope this causes the community to carefully consider the development of facial recognition technologies.

Left: a tweet the ACM sent out regarding facial recognition. (I believe this is the tweet; it's hard to find because they have deleted it.) Right: the ACM's apology.

Anti-Racism More Broadly. As mentioned earlier, as part of my broader anti-racism education, I am pursuing three separate activities which can be categorized as reading books, donating to organizations, and making commitments about my actions now and in the future.

First, in terms of books, I have been reading these in recent months:

  • Evicted: Poverty and Profit in the American City by Matthew Desmond (published 2016)
  • White Fragility: Why It’s So Hard for White People to Talk About Racism by Robin DiAngelo (published 2018)
  • So You Want to Talk About Race? by Ijeoma Oluo (published 2018)
  • Me and White Supremacy: Combat Racism, Change the World, and Become a Good Ancestor by Layla F. Saad (published 2020)
  • Stamped from the Beginning: The Definitive History of Racist Ideas in America by Ibram X. Kendi (published 2016)

I finished the first four books above, and recommend all of them. I am currently working through Ibram X. Kendi’s book. I enjoy reading the books — not, of course, in the sense that racism is “enjoyable” but because I think these are well-written, well-argued books that teach me.

In addition, I also commit to increasing the number of books I read about Blacks or by Black authors. Given that I post my reading list online (see the blog archives), it should be easy to keep me accountable.

Second, I have learned more about, and have donated to, these organizations:

All relate to tech: the first for young Black women, the second for Black researchers in AI, the third for Black and Latinx in tech, the fourth for under-represented minorities more broadly, and the fifth for low-income youth. There are other loosely related organizations that I support and have donated to in the past, but I think the above are the most relevant for the current blog post context.

Third, Going forward, I will commit to anti-racism. I will not shy away from discussing this topic. I will actively help with recruitment and retainment of Blacks within my work environment. I also will avoid comments that show insensitivity in race-related contexts, including but not limited to: “playing the race card,” “I don’t see color,” “All Lives Matter,” “I am not White,” or “I have Black friends.” I also will not claim that my research is entirely disjoint from race. My robotics research is less directly race-related as compared to facial recognition research, but that is different from saying that it has nothing to do with race.

I will be careful to consider a variety of perspectives when forming my own opinions for related events. It may be the case that I believe something which most of my nearby colleagues disagree with. We don’t have to agree on everything, but I would like the academic community to avoid cases similar to how US Senator Dick Durbin smeared fellow US Senator Tim Scott (since apologized), and more generally to avoid treating Blacks as a monolithic group.

Concluding Remarks. While this blog post is coming to a close, the process of being an anti-racist will be a lifelong process. I am never going to claim perfection or that I have passed some “anti-racist threshold” and am therefore one of the “good guys.” This is a lifelong process. I will make many mistakes along the way. I may discuss more about this in some future blog posts. In the meantime, let me know if you have comments or suggestions.