My year in books — 2020
This was a difficult year in the real world, but it was a great year in the book world. I learned new things, I got exposed to new perspectives, and I experienced wonderful fantasy worlds. The most important lessons I learned from these year’s readings are that: (1) it is important to be intentional about hearing from a diverse set of voices; the intention itself can go a long way in ensuring the diversity of the experiences you get exposed to; and (2) when it comes to ethics, it is critical to acknowledge that different people have different views, and make an effort to hear those different views (which makes point (1) above even more important).
For 2020, aside from just learning and enjoying the reading process, I also set myself two goals — to expose myself to a more diverse set of views, and to learn more about ethics and computing/AI.
Regarding the goal of reading from a more diverse group of authors: at the end of 2019, I realized that more than two thirds of the books I was reading were authored by white male authors. They were all great books, but knowing there are limits to a group’s experiences, I wanted to expose myself to a wider set of views. I made a conscious decision to read a woman-authored book for the first two books I picked for 2020. After that, I let myself guided only by topics of interest and friend recommendations (without explicit consideration to the author demographics) — but I still ended up with a diverse pool of authors (54% women authors; 17% minority authors). I believe just my original intention to increase the diversity of the authors of the books I was reading made a difference in the choices I made, without any change in other criteria for book selection.
Regarding the goal of learning more about ethics and computing/AI: there are a few books I picked explicitly for the purpose of learning more about this topic — “Invisible Women,” by Criado Perez; “Ethics and Data Science,” by Loukides, Mason and Patil; “Sex, Race, and Robots,” by Howard; and “Whistleblower” by Fowler. There are also books that are not explicitly about ethics and computing, but address topics that are closely relevant, including “White Rage” by Anderson; “White Fragility” by DiAngelo; “We Should All Be Feminists” by Ngozi Adichie; and “AI Superpowers” by Lee. The core message I got from these books is that acknowledging that different people have different views on ethics is critical to ensuring a productive and … yes, ethical conversation on ethics. When it comes to ethics, we need to read both deep and wide, and make sure we do our best to understand other people’s take on what constitutes ethical behavior.
And now, for my own “2020 book awards” …
The winners:
Invisible Women: Data Bias in a World Designed for Men, by Caroline Criado Perez. This book has changed the way I think about data. It makes a very strong and well-supported argument in favor of data disaggregation for decisions in all aspects of life: health, transportation, technology, arts, and more. The book is a great account of women’s lives in a world designed for men — on how in numerous domains, the shallowness that comes with dealing with data “as a whole” is leading to inequities. Not surprisingly, when there is a majority that dominates, the data is “dominated” by that majority as well; it follows that using such data in its entirety, without zooming in on the minorities, leads to inequities, which is what happens in many aspects of life. Not only did this book change how I regard data and the inequalities it can ensue, but it has already positively impacted multiple projects I work on.
Sex, Race, and Robots: How to be Human in the Age of AI, by Ayanna Howard. It was one of my favorite books on bias in AI. I really appreciated its objective view on bias — acknowledging that it is a natural behavior that we cannot escape — while still trying to formulate constructive solutions. Even more, because … “No one will escape [untouched] by the issue of bias in AI. No matter how privileged you imagine you are, there is always someone with a bias against you. And when that bias comes from a robot, wrapped in silicon and steel, it could be an unstoppable force.” … addressing bias in AI should be everybody’s problem!
The runner-ups:
AI Superpowers: China, Silicon Valley, and the New World Order, by Kai-Fu Lee. I enjoyed this book not only for the crisp comparison between US and China when it comes to technology and AI, but also for the strong message that we need to start rewarding socially beneficial activities (e.g., child or elderly care), and that AI should shift focus from studying the human brain to studying the human heart — e.g., understanding human emotions and developing empathetic machines.
Spillover: Animal Infections and the Next Human Pandemic, by David Quammen. I found this back in March, but ended up reading only in November, as the whole idea of a pandemic was overwhelming enough as it was and I needed to accumulate enough “courage” to read it. It is a big book — in many different ways. Wonderfully written, packed with tons of scientific details, and yet often reading like a thriller that you cannot put down. The pessimistic conclusion of this book is that things are just getting worse — given the sharp increase in human population (we are an outbreak!), and all the impact we had on climate, forests, etc. The optimistic conclusion is that we are a *smart* species, and we can make smart choices. Which makes a huge difference, as counteracting these zoonotic spillovers will eventually come down to individual decisions (e.g., in our context: wearing a mask or not, going to crowded places or not, etc)
Here is to a wonderful 2021 — in the real world, and in the book world!
