12 books that AI researchers are reading this summer
A woman sits on a bench in New York's Central Park. The summer sun is shining. The air is warm. As people jog by and play with their dogs, she quietly sips her morning coffee as she opens a book on her phone. Dipping into her summer reading list, she's happy to have a little time to herself with a book she's been excited to dive into.
This woman easily could be Lydia Chilton, assistant professor of computer science at Columbia University and an artificial intelligence (AI) researcher. Chilton, though, is not about to read the latest John Grisham thriller or even Elizabeth Gilbert's "City of Girls," which is likely in a lot of beach bags and on backyard tables this year.
No, Chilton is eager to delve into Jerry Z. Muller's "The Tyranny of Metrics," which is focused on quantifying human performance and how it threatens our schools, businesses, and healthcare. After that, she's likely to turn to one of the two other books on her summer reading list: "The Book of Why: The New Science of Cause and Effect" by Judea Pearl and Dana Mackenzie, and Barbara Tversky's "Mind in Motion: How Action Shapes Thought."
Yeah, these really aren't books on the average summer reading lists being touted by popular book blogs or getting thousands of likes on Facebook.
Chilton has been working with deep learning, a form of machine learning inspired by the structure and function of the brain, for about two years and other forms of AI for another five years or so. That work not only affects her research and academic career, but it also ignites her curiosity and drives her to learn as much as she can about AI and the social, ethical, and futuristic ideas in the world around it.
"Anytime I have a free moment, I think about what's next on my list of books to read," says Chilton, who emphasizes she reads books on her phone rather than traditional paper books. "Most of the things I'm being drawn to now are the applications of AI in different areas. I love books on ways people are thinking about related AI topics. I love to get insights from books. I love getting the bigger picture."
Who needs science fiction when you have science?
Many AI researchers see summer as the perfect opportunity to read, since they might be teaching fewer classes or have vacation time. Rather than dive into a page-turner, they dive deeper into their passion: AI. It's an opportunity to look beyond creating code and complicated algorithms and take a broader look at whom AI will affect, how robots and other smart machines will interact with humans, and what the world would look like if AI were ubiquitous and highly advanced.
"There is a danger that AI will become all about algorithms and machines, but AI should always be about humans and society," says Ashok Goel, professor of computer science in the School of Interactive Computing at Georgia Institute of Technology. "We want to write algorithms—that's our bread and butter. But it's important to think about what it means in terms of its relationship to humans and society. This keeps us grounded and makes sure we think about humans and society."
Goel, who has been working with AI since 1984 and is working on creating AI that can aid human creativity, believes so strongly in broadening researchers' thoughts around AI that he has people in his design and intelligence lab—PhD and master degree students, other faculty, and researchers—all reading the same six books this summer. And every Tuesday, as they meet for lunch, they discuss the books' ideas over sandwiches and salad.
"This helps a lot," says Goel, who adds that they're looking for a higher purpose to their work. "I might read a book and I may get one interpretation out of it, but by getting six to 10 interpretations, we challenge each other. We can synthesize something. It makes us talk about and think about the kind of research we should do and the type of research we should not do."
Every summer for the past 10 years or so, Goel's research team has voted on an activity to do together. One summer, they watched science fiction movies. Last year, they voted to read about questions of ethics around artificial intelligence. This summer, they voted to read about AI and its influence on society, as well as about AI and humans working together. Then they voted on which books to read.
"I think [the researchers] love it," says Goel. "We all love it. It gives meaning and purpose to our work. We're not just programming code. We love doing code, but this gives us a higher meaning. We become not just computer programmers but scientists trying to build new ways of thinking that might help humans and society."
So what are Goel and his fellow researchers reading this summer?
One book, "The Man Who Lied to His Laptop: What We Can Learn About Ourselves from Our Machines" by Clifford Nass and Corina Yen, focuses on what our relationships with technology can tell us about our relationships with other humans. Another, "The Fourth Age" by Byron Reese, looks at what it means to be you and how robots and AI will challenge our assumptions of who we are.
Yi Zhuang, a senior staff engineer at Twitter who is working on the social network's next-generation machine learning platform, doesn't have a summer vacation, but he does have a few books he'd like to read while he sits in front of his air conditioner over the next few months. And he's excited and optimistic about making his way through his reading list this summer.
Like Columbia's Chilton, the Twitter engineer is reading Pearl's "The Book of Why," which in part looks at the essence of human thought and the development of AI.
Zhuang also is having a little fun. One of the books on his reading list is John Carreyrou's "Bad Blood: Secrets and Lies in a Silicon Valley Startup." Focused on the shocking rise and fall of a biotech startup in Silicon Valley, the book is giving Zhuang a look inside a story of corruption in his own part of the world.
For Sergey Serebryakov, a research engineer at Hewlett Packard Labs in Palo Alto, Calif., summer is a time for relaxing reading. His idea of relaxing reading, though, may be slightly different than most people's.
Serebryakov, who specializes in working with AI and machine learning, is reading "The Story of Earth: The First 4.5 Billion Years, from Stardust to Living Planet" by Robert M. Hazen. After reading a series of books about the universe by Michio Kaku, an American theoretical physicist and futurist, Serebryakov wants to focus on learning more about Earth.
"I look at what I've read the last six months or so and it's been mostly professional literature," says Serebryakov. "It's nice to have a chance to read something that is fun. What I read in the summer is different from what I normally read. I don't have a lot of time, so I selected one book I want to read. It's not really science. It's popular science."
For his part, Bart Selman, professor of computer science and director of the Intelligent Information Systems Institute at Cornell University, just can't imagine not reading about artificial intelligence.
"I have a summer reading list, but it is different than [it is] for most people," says Selman, who is working on combining machine learning with automated reasoning. "My reading is related to my work because my work is also sort of my hobby. During the regular academic year, you're teaching, writing grants, and in academic meetings. Summer reading is a combination of relaxing and expanding my knowledge."
Selman, like many other researchers, uses his reading to broaden his take on technology.
"All my reading is about bigger picture issues—things you have to be careful about when you're using AI technology for decision-making," Selman says, noting he's reading Paul Scharre's "Army of None: Autonomous Weapons and the Future of War." "These are not hard technical books. They are general audience books, but they are related to what I do. If your work is fun, then the summer is a good time to read more about it."
Ken Goldberg, the William S. Floyd Jr. Distinguished Chair in Engineering at the University of California, Berkeley, and a founding member of the Berkeley AI Research Lab, has similar goals.
Goldberg's summer reading list includes "Every Tool's a Hammer: Life Is What You Make It" by Discovery Channel star and tech/science figure Adam Savage. Savage writes about fostering creativity and turning ideas into reality. Goldberg also is reading "Machines Like Me" by Ian McEwan, a novel set in an alternative 1980s London that looks at the question of what makes us human.
Steve Sickler, president and COO of Tend.ai, a robotics software startup, is turning his reading attention this summer to "Children of Time," by Adrian Tchaikovsky. The science-fiction novel tackles big topics, like artificial intelligence and the survival of the human race. Sickler, though, is still reveling in Samuel Peralta‘s "The Robot Chronicles."
"I loved the stories, as each was incredibly creative—some AIs dream and some love," says Sickler. "I think reading this kind of speculation opens our minds about robots and AI, whether you fear it or not. Who knows? We'll have to wait 20 years and see if truth is stranger than fiction."
For your copy-and-paste convenience
Thanks to all who shared their recent reading lists with us. Some of the books on those lists are highlighted above, but here's a complete rundown of what our AI experts are reading (or have recently read):
Lydia Chilton, assistant professor of computer science, Columbia University
- The Tyranny of Metrics
- The Book of Why: The New Science of Cause and Effect
- Mind in Motion: How Action Shapes Thought
- The Square and the Tower: Networks and Power, from the Freemasons to Facebook
- Machine, Platform, Crowd: Harnessing Our Digital Future
- Crystallizing Public Opinion (first published in 1923)
Ashok Goel, professor of computer science, Georgia Institute of Technology
- The Man Who Lied to his Laptop: What We Can Learn About Ourselves from Our Machines
- The Fourth Age
- Life 3.0: Being Human in the Age of Artificial Intelligence
- Persuasive Technology: Using Computers to Change What We Think and Do
- Homo Deus: A Brief History of Tomorrow
- Emotional Design: Why we Love (or Hate) Everyday Things
Ken Goldberg, William S. Floyd Jr. Distinguished Chair in Engineering, University of California, Berkeley
- Every Tool's a Hammer: Life Is What You Make It
- Machines Like Me
- The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power
- The Flame: Poems and Notebooks
Matt Man, co-founder and CEO, Indus.ai
Bart Selman, professor of computer science, Cornell University
- Army of None: Autonomous Weapons and the Future of War
- The Idea Factory: Bell Labs and the Great Age of American Innovation
- Einstein: His Life and Universe
- The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World
- Beyond Deep Blue: Chess in the Stratosphere
Steve Sickler, president and COO, Tend.ai
- Children of Time
- Alchemy: The Dark Art and Curious Science of Creating Magic in Brands, Business, and Life
- The Robot Chronicles
- The Wool Trilogy
Sergey Serebryakov, research engineer, Hewlett Packard Labs
- The Story of Earth: The First 4.5 Billion Years, from Stardust to Living Planet
- Deep Learning (Adaptive Computation and Machine Learning series)
- Algorithms in Strings, Trees and Sequences
- The Effective Modern C++
Peter Stone, professor of computer science, University of Texas, Austin
- The Jasons: The Secret History of Science's Postwar Elite
- Educated: A Memoir
- The Weight of Ink
Yi Zhuang, senior staff engineer, Twitter
- The Book of Why: The New Science of Cause and Effect
- Bad Blood: Secrets and Lies in a Silicon Valley Startup
- Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow
- Basic Economics, Fifth Edition: A Common Sense Guide to the Economy
- Sapiens: A Brief History of Humankind
- Principles: Life and Work
- Clean Architecture: A Craftsman's Guide to Software Structure and Design
Want more summer reading? Consult these guides:
This article/content was written by the individual writer identified and does not necessarily reflect the view of Hewlett Packard Enterprise Company.