[Warning: long read]

A year ago, I listed all the books that I read in the year 2016. I listed 35 books with summaries for each, and grouped them into categories by subject. I’m pleased to announce that I am continuing my tradition with this current blog post, which summarizes all the books I read in 2017.

As before, I am only listing non-fiction books, and am excluding (among other things) textbooks, magazines, and certainly all the academic papers1 that I read. Books with starred titles (like ** this **) are those that I especially enjoyed reading, for one reason or another.

In 2017, I read 43 books, which is eight more than the 35 I reported on last year. Yay! The book categories are:

  1. Artificial Intelligence and Robotics (11 Books)
  2. Technology, Excluding AI/Robotics (5 Books)
  3. Business and Economics (5 Books)
  4. Biographies and Memoirs (6 Books)
  5. Conservative Politics (3 Books)
  6. Self-Help and Personal Development (3 Books)
  7. Psychology and Human Relationships (4 Books)
  8. Miscellaneous (6 Books)

Within each section, books are listed according to publication date.

I hope you enjoy this blog post! For 2018, I hope to continue reading lots and lots of non-fiction books with a heavy focus on technology, businesses, and economics. For the full set of these “reading list” posts, see this page.

Group 1: Artificial Intelligence and Robotics

Yowza! From the 11 books here, you can tell that I’m becoming a huge fan of this genre. ;-)

  • ** Incognito: The Secret Lives of the Brain ** is a thrilling 2011 book by neuroscientist David Eagleman of the Baylor College School of Medicine. (I consider this book as “AI” in this blog post, though you could argue that “Psychology” might be better.) It is clearly designed for the lay reader with interest in neuroscience, like me, due to a number of engaging examples that thrill the reader without going overboard with the technical content. Eagleman describes how we don’t actually have that much control over our brain, that there are so many unexpected contradictions with how we think, and mentions a few interesting neuroscience factoids. Did you know, for instance, that half of a child’s brain can be removed and the child can still survive? On a technical note, I was impressed with how Eagleman referenced a few machine learning papers from Michael I. Jordan and Geoff Hinton in his footnotes about hierarchical learning. From the perspective of a computer scientist, the most interesting part was when he talked about the brain being a team of competing rivals. This is awfully similar to the idea behind Generative Adversarial Networks an enormously successful and well-cited paper that came out in NIPS 2014 … three years after this book was published! I have no idea how a non-computer scientist was able to almost predict this, but it shows that cross-collaboration between neuroscientists may be good for AI. He doesn’t get everything right, though. He mentions more than once that artificial neural networks have been a failure. Well… this book was published in 2011, and Alex-Net came out in 2012, so that kind of flopped quickly. Despite this, I hope to see Eaglemen write another book about the brain so that I can see a revised perspective. Incognito also contains interesting perspectives on neuroscience and the law. Eagleman doesn’t take sides but doesn’t go in too much depth either. He says the “bar” for blameworthiness will change depending on available neuroscience, which he says is a mistake (and I agree).

  • ** The Most Human Human: What Artificial Intelligence Teaches Us About Being Alive ** is an engaging 2011 book written by Brian Christian, who also (co-)authored another book I read this year, Algorithms to Live By. This book’s main focus is on the Turing Test, and it plays a greater theme in this one more than any of the other AI books I’ve read. Simply put, while we’re so obsessed about getting a computer to fool human judges (the “most human computer”), Christian argues that an equally important criteria is the “most human human.” In other words, in the Turing Test, who is the human that can most convince the judges that he/she is human? The book’s chapters are explorations of the different factors that make us human, among other things our ability to barge and interrupt, our use of “um” and “uh”, our constant sidetracking, and so forth. Intuitively, these are hard for a computer to model. Christian has a computer science background, so some of the book covers technical concepts such as entropy, which he argues we need to be making as high as possible; low entropy means we’re not saying anything worth knowing more about. And yet, these seem to be the most negatively encouraged aspects of our society, which is quite odd in Christian’s opinion. I enjoyed reading most of the book because it stated observations that seem obvious to me in retrospect, but which I never gave much thought. That’s the best kind of observation. (It’s like Incognito to some extent, and indeed the Incognito author praises this book!) The biggest drawback is that it never goes through a blow by blow of the actual Turing test! I mean, c’mon, I was looking forward to that, and Christian essentially ruined it by fast forwarding to the end, when he mentions he won the title of the “most human human.” Well, congratulations dude, but why wasn’t there at least a complete transcript in the book???

  • ** Our Final Invention: Artificial Intelligence and the End of the Human Era ** is a 2013 book by documentary filmmaker James Barrat exploring the rise of AI and its potential existentialist risk. This is not far off the mainstream of AI researchers and programmers as it sounds. In fact, Peter Norvig and Stuart Russell include a brief discussion about it at the end of their famous AI textbook. Russell has also explicitly said that he’s clearly worried about superintelligence. So what is superintelligence? I view it as AI that is so far advanced that it becomes better and better, and surpasses humans in just about every quality imaginable.2 I think I enjoyed reading this book, even if it is a tad too sensational. There isn’t that much technical detail, which is OK since it’s a popular science book. Barrat makes an excellent point that scientists need to make their work accessible to the public. I agree — that’s partly why I discuss technical stuff on this blog — but I also think that people have got to start learning more math on their own. It needs to be a two-way partnership. Moving on, an unexpected benefit of reading Our Final Invention was that I learned about the work done by I.J. Good, Eliezer Yudowsky, and others from the Machine Intelligent Research Institute. I’m embarrassed to admit that I didn’t know about those two people beforehand, but now I will remember their names. Unlike MIRI in most Berkeley AI research groups, such as the ones I’m in, we don’t give a modicum of thought to existential risks of AI, but the topic is garnering more attention. One final comment about the book: Barrat mentions that no computer is better than a child at object recognition. Well, whoops. They are now! He talks a lot about neural networks and how we don’t understand them, which by now feels old and I wish authors would take note of all the people workong on this area. I’d like to see an updated version of Our Final Invention in 2018, with the last five years of AI advancement taken into consideration.

  • ** Superintelligence: Paths, Dangers, Strategies ** is a 2014 book by Oxford philosopher Nick Bostrom.3 His philosophy background is apparent in the way Superintelligence is written, though it is obviously much easier to read than a real, academic philosophy paper. In this book, Bostrom considers when AI grows to the point where machines are “superintelligent.” That term can be broadly understood as when machines are so powerful and intelligent that they effectively have complete control over the future of the universe. Why, Bostrom says, can we assume that superintelligence is friendly? We cannot, he concludes. The book is about different ways we can get to superintelligence (i.e., “paths”) including AI, emulating the brain, collective superintelligence (think a super-charged Internet) and so forth. There are also “dangers” and “strategies”. Bostrom convincingly explains why superintelligence poses an existential risk to humanity, and also explains what strategies we may take to counter it, such as by uploading appropriate values to the agent. Unfortunately, none of his solutions are clear-cut. There are two things you will notice when reading this book. First, almost every assumption has a counterexample or unexpected consequence. Bostrom often comes up contrived scenarios for this purpose. Second, Bostrom frequently cites Eliezer Yudkowsky’s work. I first learned about Yudkowski by reading James Barrat’s Our Final Invention (see above). If you like Yudkowsky, you’ll like Bostrom. Taking a more general view, Superintelligence is meant to be a serious academic-style discussion, but not a recipe that can be easily followed, because it assumes so many things and continues to make the reader feel like every case is hopelessly complicated with advantages and disadvantages abound, both obvious and non-obvious. Overall, I’m happy I read this book even if it is wildly premature. It made me think hard about any assumptions I make in my work.

  • What to Think About Machines That Think: Today’s Leading Thinkers on the Age of Machine Intelligence collects responses based on a 2015 survey of the EDGE question: “what do you think about machines that think?” This was sent to about a hundred or so experts in a variety of fields, mostly different academics and well-known authors. Obvious inclusions were Nick Bostrom (of Superintelligence fame), Eliezer Yudkowsky, Stuart Russell, Peter Norvig, and others, but there were also some interesting new additions. I of course did not know the vast majority of the people here. This book is a bit of an unusual format; each author’s answer to this question took up 1-4 pages. There were no constraints otherwise, so the answers varied considerably. For instance, I like Steven Pinker’s comment of why people don’t think AI will “naturally develop along female lines […] without the desire to take over the world.” Gee, isn’t that stereotyping, Pinker?? There were also some amusing responses, such as when someone said that he himself was an AI and people didn’t know it (!!) as well as alarmingly short answers saying “machines can’t think”. Most responses were along the same theme of: “AIs taking over the world aren’t going to happen anytime soon, but they are affecting us now, sometimes in subtle ways, and [insert ‘novel’ insight here].” Overall, while I like the idea of the book format, I think the utility that I derive from reading is more about understanding a long, engrossing story. This is not necessarily a bad book, and I can see it being useful for someone who can only read books in short 3-5 minute spurts at a time, but it’s not my style.

  • ** Machines of Loving Grace: The Quest for Common Ground Between Humans and Robots **, is a 2015 book by NY Times journalist John Markoff. Though a journalist, Markoff has frequently written about AI-related topics and has good connections in the field. Machines of Loving Grace gives an impressively balanced view of the history of Artificial Intelligence (AI) and Intelligence Augmentation (IA), which can be roughly thought of as HCI (I might view it as a subset of HCI). Obviously, I am more interested in the AI aspect. Markoff covers topics such as self-driving cars (unsurprisingly), and Rodney Brooks’ Baxter robot, which has been used in many research papers that I’ve read. But more surprising from a Berkeley perspective, Markoff also mentioned Pieter Abbeel’s work, though this was his clothes folding experiment, and not his later, more exciting DeepRL stuff from 2014 and onwards. I was also — unsurprisingly — interested in Markoff’s description of the history of how the neural network pioneers met each other (e.g., Terence Sejnowski, Geoffrey Hinton, and Yann LeCun). For the IA side, the most prominent example is Apple’s Siri, which interacts with humans, though I don’t have much to say about it because I have never used Siri. Yes, I’m embarrassed. On the AI vs IA dilemma, Markoff notes people such as John McCarthy and Doug Engelbart on opposite sides. And of course who could forget Marvin Minsky who decimated the field of neural networks with his legendary 1969 book? I decided to read this based on Professor Ken Goldberg’s brief Nature article, and was pleased that I did so, mostly (again) to learn about history (since I’m trying to become like one of those AI experts…) and the importance of ensuring that, at least for AI applied to the real world, we keep the human interaction aspect in mind.

  • Rise of the Robots: Technology and the Threat of a Jobless Future is a 2015 book by technologist Martin Ford, who warns that our society is not prepared to handle all the future technological advances with robots automating out jobs. He begins by arguing that IT advances have not been as useful as electricity and other breakthroughs, and indeed that is a key theme from Robert Gordon’s The Rise and Fall of American Growth. To make the point clear, in response to Ray Kurzwiel saying that smartphones have provided incalculably large benefits to their owners, Ford counters with: “in practice, they may offer little more than the ability to play Angry Birds while standing in an unemployment line.” Ford continues by citing sources and reasons for the decline of the middle class in America. This part of the book is not controversial. Ford then raises the point that the IT revolution, along with not just robotics but also machine learning, means that even “high-skilled” jobs are at risk of being automated out. We now have machines that can write as well as most humans, that play Jeopardy! (as expected, IBM’s Watson was mentioned) and which perform better at image recognition and language translation using Deep Learning. Ford worries that, in the worst case, an elite few with all the wealth will hoard it and be guarded in a fortress by robots. Yes, he admits this is science fiction (and he discusses the Singularity, probably not the best idea…) but the point seems clear. Ford concludes the book with what he probably wanted to discuss all along: Universal Basic Income to the rescue! I heard about this book from Professor Ken Goldberg’s brief Nature article, who is critical of Ford “falling for the singularity hype” and his “extremely sketchy” evidence. I probably don’t find it as bad, and lately I’ve been thinking more seriously about supporting a Universal Basic Income. We might as well try on smaller scales, given that the best we can hope for in the future is more debt and safety net cuts with Republicans (now) or more debt inefficient bureaucracy with Democrats (in 2018/2020).

  • Our Robots, Ourselves: Robotics and the Myths of Autonomy, a 2015 book written by MIT professor David A. Mindell, is the third robotics-related book that I read based off of Professor Ken Goldberg’s brief Nature article. Mindell has an unusual background, being a Professor of Aeronautics and Professor of the History of Engineering and Manufacturing (I didn’t even know that was a department). He’s also a pilot. So this book brings together his expertise when he discusses what it means for robots to be automated. Our Robots, Ourselves discusses five realms: sea, land, air, war, and space, and shows that in all of those, it is not straightforward to claim that robots are being more and more autonomous at the expense of the human aspect. In addition, Mindell tells stories of the natural conflict between increasing automation and human employees. For instance, with sea, what does it mean for geologists and scuba-diving analysts if robots do it for them? Does it detract from their job? A similar thing rings true for pilots. We need some way of humans taking over in emergencies, and pilots are worried that increasing automation will lower the prerequisite skills for the job and/or reduce the job’s purpose. Next, consider war. People who once fought on the front lines or as air force pilots are feeling resentful that those who manage drones remotely are getting respect and various honors. Mindell argues that increasing automation must also go along with better human-robot interaction, a topic which is rightfully becoming increasingly important for academia and the world. After reading this book, I now believe I do not want systems to be fully autonomous (a huge issue with self-driving cars) but instead, I want the automation to work well with humans. That’s the key insight I got from this book.

  • ** Algorithms to Live By: The Computer Science of Human Decisions ** is a 2016 book co-authored by writer Brian Christian and Berkeley psychology professor Tom Griffiths. It consists of 11 chapters, each of which correspond to one broad theme in computer science, such as Bayes’ Rule, Overfitting, and Caching. Most of these topics are related to algorithms and machine learning, which wasn’t particularly surprised to me given the authors’ backgrounds. I also know Professor Griffiths publishes machine learning papers on occasion, such as his groundbreaking 2004 paper Finding Scientific Topics. Algorithms to Live By lists how the major technical issues and questions related to these topics can have implications for actions in our own lives, such as dating, parking cars, and designing our rooms/desks (this example with caching always comes up). The authors point out how, in practice, the algorithms people engage in for these activities can be surprisingly correct or well off the mark of optimality, where here the metric is based on mathematical proofs. Of course, whenever we talk about mathematical proofs, we have to be clear on what assumptions we make, which will drastically affect our options, and which in fact can often validate some of the seemingly irrational activities that humans perform. I tremendously enjoyed reading this, though admittedly it was easier for me to digest the material given that I knew the main idea of the computer science concepts covered. It was nice to get a high-level overview, though, and I still learned a lot from the book since I have not studied every computer science subfield in detail. My final thought is that, just like when I read The Checklist Manifesto last year and tried to think about utilizing checklists myself, I will try and see if I can incorporate some of the authors’ suggestions in my own life.

  • ** Thinking Machines: The Quest for Artificial Intelligence and Where It’s Taking Us Next ** is a recent 2017 book by journalist Luke Dormehl. I found out about it by reading Ray Kurzweil’s favorable book review in The New York Times. Kurzweil remarks that Luke is a journalist who “actually knows the technical details.” I think that’s true, though there is virtually no math in this book, or at least very little of it compared to Pedro Domingos’ book. In Thinking Machines, Dormehl mentions the backpropagation algorithm which has powered Deep Learning, but only at a very high level (obviously). He also talks about Deep Learning’s history, which I know already (and it could have been derived right from Stanford’s CS 231n slides) but it’s good to have here. Dormehl writes about the by-now famous story that “neural networks were ignored for a while then they became popular and are now known as Deep Learning,” which Professor Jitendra Malik would remark is “more marketable.” As far as technical material goes, it’s correct, so no worries. Dormehl includes a substantial amount of material about sensors, the Internet of Things (similar to Thomas L. Friedman’s Thank You For Being Late) and of course about AI ethics, laws, and the singularity. These are not new themes, but the difference between this book and others is that it’s very recent and current, which is useful due to the fast-growing pace of AI, so it was able to cover AlphaGo from DeepMind. I consider it a broad “story” about AI, and less opinionated compared to James Barrat’s Our Final Invention. It’s of reasonable length (not too long, not too short) and great for a wide audience of readers. Overall, I enjoyed reading the book, and it kept me up late longer than I should have.

  • ** Heart of the Machine: Our Future in a World of Artificial Emotional Intelligence ** is a 2017 book also recommended by Ray Kurzweil. The author is Richard Yonck, founder and president of Intelligent Future Computing, a company which provides advice on the impact of technology on business and society (is this called “consulting”?). Heart of the Machine, like many AI-related books, discusses recent research and commercial advances, but it emphasizes an emotional perspective. It discusses how we got to affective computing and the rise of emotional machines. The first part contains a little history and discusses some of the labs that are working on this (e.g., the MIT Media Lab). The second, like the first, shows how many companies are measuring emotions, in part using advances in AI and Big Data analysis, and cautions us about the uncanny valley. The third part of the book is about the future, and obviously sexbots play a role. What I remember most form the book are its anecdotes, one of the most touching of which was when someone wanted to marry a robot, and a parent opposed this. Will this be the future of marriage? The first step is interracial marriage, then the next is same-sex marriage, and the last (?) step is human-machine marriage. Yonck shows his academic side by citing some ACM/IEEE International Conference on Human-Robot Interaction papers. That’s a niche-style conference but will likely grow into something much larger in the coming years (see the 2018 website here), similar to how NIPS grew from a niche into an enormous conference with thousands of attendees each year. Finally, I appreciated that Yonck said we are already merging with technology in some ways. For instance, many deaf people opt for cochlear implants to better interact in a hearing world. (I likely would have one had I been born a few years later and if hearing aids were not already highly successful for me.) We already merge with technology so much, and this is likely to increase in the future.

Group 2: Technology, Excluding AI/Robotics

These are books loosely related to technology, though excluding AI and robotics, as I discussed those in the previous section.

  • ** The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies **, co-authored by Erik Brynjolfsson and Andrew McAfee. Both authors are from MIT: Brynjolfsson is a professor of management and McAfee a research scientist. The authors appear to take the opposite perspective of economist Robert Gordon (author of The Rise and Fall of American Growth, which I discuss later), a point that they emphasize repeatedly: they argue that we are now at an inflection point and that we are on our way towards better times, and not stagnation. Their key rebuttal to Gordon is that innovation is due to recombination. Sure, we may not invent brand new things like electricity, but the IT revolution was all about combining stuff that had previously existed, and that will continue onwards as more people are able to try new things. As expected, they provide the usual disclaimers (at least from the technologically elite) that technological growth isn’t always great, that people fall behind, etc. To their credit, both men propose solutions, which I think are reasonable and — crucially in today’s politics — are widely agreed upon by economists across the entire political spectrum. For instance, they mention the universal basic income but seem to prefer the more mainstream “earned income tax credit” idea, and I think I can agree. One major quibble I have is that the book has one chapter to AI, but the actual AI portion of it is only two and a half pages long. And this for what might be the biggest technology advance of the 21st century! Fortunately, they seem to have given it greater attention since the book was first published. I bought The Second Machine Age in December 2016 as a Christmas gift, and they included a new introduction saying that they had underestimated progress in AI, particularly with deep neural networks, a topic which I frequently blog about here! (Incidentally, I saw Brynjofsson’s praise for a MOOC on Deep Learning … even MIT professors are going to MOOCs4 to learn about the subject!) The book is relatively straightforward to read and oozes more excitement compared to Gordon’s book. There is a book website for more details if you are interested. Brynjofsson and McAfee have since written more about Deep Learning, as you can see from their NY Times article after AlphaGo famously beat Go super-duper star Lee Sodol. I feel extremely fortunate to be in a position where, though I’m not the one creating this stuff, I can understand it.

  • ** How Google Works ** is a 2014 book (updated in 2017) with a self-explanatory title, written by two of the most knowledgeable people about Google, Eric Schmidt and Jonathan Rosenberg. The former was the CEO of Google from 2001 to 2011 until he stepped down to be come “Executive Chairman” of Google (and then Alphabet later). So … basically he’s shuffling around titles without loss of power, I think.5 Jonathan Rosenberg6 was a longtime Product Manager for Google, and now he is advisor to Alphabet CEO Larry Page. These two men thus know a lot about Google and are well-qualified to talk about it. The book is an entertaining mix of the lessons they’ve learned about working at Google, how to scale it up, etc. I was particularly impressed about stories such as how Jeff Dean et al. found a note from the CEO who complained that “these ads suck”. So in one weekend, despite them not being on the ads team, they were able to fully diagnose the problem. Wow, that’s Google for you. The main takeaway from this book is that I need to be a better smart creative. The only way I know how to do this is by always learning, whether by coding or (as I try to do) read a lot of books. That being said, the book does suffer from trying to describe many concepts that I would argue are obvious and well-known. Many themes, such as “think 10x better, not incremental” are common in books that combine technology and business, such as Peter Thiel’s Zero to One book, which I read last year. Another is that “you can’t apply the lessons you learn in business school” which is again something commonly assumed in the tech industry. Another is “hiring is the most important thing you can do” but Joel Spolsky has already said something similar earlier on his blog. I don’t mean to completely negate the benefits of this book; it seems to maintain just enough of the “uniqueness” balance to make it a worthwhile read. Homer alert: I wish the authors would write a follow-up book where they discuss Artificial Intelligence. After all, current Google CEO Sundar Pichai has made it a point to emphasize AI for Google. To be fair, they mention it as one of the “things that might happen in the next five years”, so right now we’re smack dab in the middle of that time period. I’ll keep watch in case they publish a sequel later. On a final note, reading this book made me want to work at Google!

  • ** Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy ** is a 2016 book by mathematician-turned-data scientist and author (and MathBabe founder) Cathy O’Neil who argues that the use of large datasets in industry and government contexts has, well, increased inequality in our society. She describes stories about how the use of big data to predict whether someone will commit a crime or default on a loan has a harmful feedback loop on the poor and minorities. (Blacks are the minority group emphasized the most in the book.) Why is there a feedback loop? Minorities are more likely to be around people who are committing crimes, and the “birds of a feather” mentality among big data algorithms is that they tend to relate people to those who bear similar qualities. Whereas in the past, for instance, a banker might not have relied on big data but on his instincts to grant or deny loans, which would hurt women and minorities, nowadays we mostly have data algorithms to determine that, but even so, algorithms have their own biases and values (indeed, this is an academic research topic, see the BAIR Blog post on this which also uses Google’s “labeling blacks as gorillas” example of algorithms trained on wrong data). O’Neil calls for increased transparency in these algorithms, which she calls Weapons of Math Destruction (WMDs), and for the people working on these algorithms to better understand the values that are inherent in the models. I enjoyed most of the short, fast-paced book and highly recommend it. It’s also worth noting that O’Neil regularly writes columns about this subject area, which interested readers should check out.

  • ** Thank You for Being Late: An Optimist’s Guide to Thriving in the Age of Accelerations ** is Thomas L. Friedman’s most recent book, published in late 2016 (though the manuscript was done before the outcome of the presidential election). For a long time, I’ve been following Friedman’s Sunday weekly columns at The New York Times, which has served as a preview for what’s to come in the book: Moore’s Law, the refugee/migration crisis, unstable governments, droughts and climate change, and the polarization at the highest level of American politics. Friedman goes through these and discusses topics much like he did in The World is Flat, though I think he tempers his idiosyncratic writing style. He mentions at one point a handful of policy changes he’d like to do, and claims he’s neither left nor right politically and that those labels are now outdated. For instance, he’s very free trade (right) but also for single-payer health care (left). I was duly impressed from the book because it taught me much about how the world works today. It also made me appreciate that I’m in a position where I can take advantage of what the world has to offer. Thank You for Being Late also mentioned several technical topics that I’m passionate about. It was really nice to see a mainstream, “non-technophobe” talk about Moore’s Law, GitHub7, and even TensorFlow/Deep Learning (!!); he explained these topics as well as he could given the non-technical nature of the targeted audience. I also appreciated the surgeon general’s comment in the end that America’s biggest killer “was not heart disease, but isolation” which is ironic given how we are more connected than ever before. Ultimately, I want to be part of that acceleration and, of course, to ensure that the vast majority of Americans aren’t left behind (including myself!). The book, however, made me concerned about the future. I finished this just a few days before Trump was inaugurated so … hopefully things will be OK.

  • What to Do When Machines Do Everything: How to Get Ahead in a World of AI, Algorithms, Bots, and Big Data is a recent 2017 book by three leaders from Cognizant, a firm which I didn’t know about beforehand. This book takes the now-standard view (at least among many technology thinkers) that automation will be overall better for us, destroying some jobs but also creating new ones and clearing out old drudgery. One thing the authors note which I haven’t heard before is that they subscribe to the “S-Curve”: we’re in a “stall” zone, but for the next two decades, we will experience dramatic economic growth with more equalizing effects as it relates to income distribution. I find this hard to believe, unfortunately. Another perspective the authors bring is that once old entrenched companies make more of a digital transition, that’s when we’ll really see GDP take off. Regarding the book style, it’s short and written in a mini-textbook style. The abbreviations in it were a bit corny but I enjoyed the examples, at least the ones they had. I surprisingly didn’t seem to enjoy it as much as some other similar books, probably because some of their advice is really high level and generic, over-simplifying things. All in all, I think the book is mostly correct on a technical level but may not be my style.

Group 3: Business and Economics

I badly need to better understand the world of business, particularly due to the increasing business-related importance of Artificial Intelligence nowadays.

  • How the West Grew Rich: The Economic Transformation of the Industrial World. This is an old 1986 book by the late economist and historian Nathan Rosenberg and co-author L.E. Birdzell Jr, an attorney and legal scholar, and I have several quick thoughts. The first was that this book was a real slog for me to read. It’s not even close to being the longest book I’ve read8 but I had to struggle through it; I think the writing style of 1986 is different from the one I’m used to today, but I’m also partly to blame since I spaced out my reading over many evenings when I was tired. In any case, this book is about capitalism in some sense, though the authors complain that the term is misleading. Their main argument is that the freedom of business and enterprise from religious and political control was the key factor in explaining the rise of the West, and not other factors generally attributed, such as science or mass production. Judging from the book, the prevailing wisdom at that time may have been mass production, but apparently not to them. It’s a bit interesting to think about what conclusions they make which are still relevant today, like how it’s so hard for Third World countries to catch up. I was also amused at seeing the Soviet Union mentioned so much, and I had to remind myself: 1986, 1986, 1986. (In a shout-out to the AI people reading this, that was the year when Rumelhardt, Willimans, and Hinton published their famous backpropgation paper with “readable math”.) Ultimately, while this book has some good spots in it, I lost focus too much to really benefit from it, and I think The Rise and Fall of American Growth is a vastly superior alternative, unless you want to get a better understanding of European stuff (not just American) and also some discussion about the Middle Ages.

  • Shop Class As Soulcraft: An Inquiry Into the Value of Work, is a 2009 book written by Matthew Crawford, who has one of the most unusual profiles among authors I read. Crawford is a mechanic and works at a bike shop, but he also holds an undergraduate degree in physics and a PhD in political philosophy from the University of Chicago. After his PhD, he worked at a “think tank” (where he had to basically repeat what the oil companies wanted to say about global warming) and at a firm where his job was to basically rewrite abstracts of research papers (what?!?). His true heart lies in building things, where he gets value. Crawford is concerned that today’s white-collar emphasis of the world focuses too much on removing value from humans (whereas mechanics can just point and say “here’s my result!”), and the white-collar blue-collar divide is making the mechanics earn less respect across society. I am indeed concerned that this is true, especially with today’s political divide among the college-educated and non-college educated, and I wish that more people with solid academics, those who have “never failed” had a little more humility. (I certainly feel like I’ve failed a lot and I’m pretty academically credentialed compared to a lot of others.) In a sense, I get the feeling that this book is like Jaron Lanier’s “You Are Not a Gadget” — those two men might see a lot of common ground over their critiques of modern life, though for different reasons. One takeaway from the book is that I’m happy to be where I am since I can try and perform deep work to produce results (code, papers, etc.) that people can look at, as I am doing more frequently on my GitHub account. Unsurprisingly, this was the key point Cal Newport made from this book. Lastly, I can’t resist mentioning one of the most interesting parts of this book. In a footnote in the seventh chapter, he talks about AI in the context of lamenting how humans were often being reduced to simple straightforward rules. His footnote talks about computer science and says the one hope for AI in the future is with neural networks since they’re not reduced to simple rules. Wow … that was in 2009 (before Alex-Net, etc.). Even your bike shop repairman knows about Deep Learning!

  • ** The Lean Startup: How Today’s Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses ** is a 2011 book by software entrepreneur Eric Ries, known for co-founding IMVU and then later for consulting various start-ups through his Lean Startup methodology. In this book, Reis provides a guide for start-ups, which he defines as: “[…] a human institution designed to create a new product or service under conditions of extreme uncertainty”. Note the lack of any comment about company size, and also note the inclusion of extreme uncertainty. This means start-ups can include non-profits, large companies, and even governmental organizations, so long as there is initial uncertainty in their roadmap. The Lean Startup argues that, in order for startups to thrive, they must follow a Build-Measure-Learn feedback loop. Furthermore, that loop must be their competitive advantage compared to slower, bulkier competition. By building Minimum Viable Products, Reis argues that appropriate metrics (not “vanity metrics” as he calls them) and customer feedback can be measured rapidly. Understanding these early results then guides the startup towards the next step, which may or may not involve the painful act of pivoting to change strategies. The book’s advice appears sound and reasonable. While I certainly don’t have much experience in this area to fully critique the book, Reis has famous tech titans such as Sheryl Sandberg and Andrew Ng to vouch for the book, so I think I can trust the advice. (I found out about this book from Andrew Ng’s reading recommendations.) While reading the book, I imagined what I would do if I tried to create (or more realistically, join) a start-up. My PhD program isn’t going to last forever … but I suppose while I’m here, I should emphasize the Minimum Viable Product aspect with respect to research.

  • ** The Hard Thing About Hard Things: Building a Business When There are No Easy Answers ** is a 2014 book by billionaire venture capitalist Ben Horowitz where he recounts his experience running Loudcloud and Opsware as CEO. The book starts out by first describing the CEO experience. Then, Horowitz remarks about the lessons he’s learned and outlines recommendations and guides on what he thinks CEOs should be like. The book concludes with him explaining how he founded the venture capital firm Andreessen Horowitz, which he’s still running today9 to help technical founders become groomed CEOs. The book is fast-paced and feels like a high-octance novel, because Horowitz’s tenure at Loudcloud and Opsware was anything but smooth. Horowitz argues that there are peacetime CEOs and wartime CEOs, of which he was definitely the latter as he estimates he only had “three days of peace” when running the company. Loudcloud and Opsware initially raised a lot of money, but then after the dot-com crash, they struggled a lot and I’m amazed that Horowitz turned it around and eventually sold the company for $1.6 billion to Hewlett-Packard. Reading his story, and Elon Musk’s story (which I’ll get to later), makes me wonder how these two CEOs managed to pull their companies out from the financial brink. I am kind of surprised that something “comes out of nothing,” and one of my disappointments is that it arguably spends a lot of time on Horowitz’s lessons for the CEO whereas I would have preferred more details on his CEO experience (at least, more than what’s in the book) because, again, I don’t understand how companies can go to a billion dollars’ worth of value out of nothing. I really need to step in the shoes of a CEO one of these days. But perhaps I would have better understood this if I understood more about business, and I certainly learned a lot about the business word from reading this book. For instance, I’m embarrassed to say that I only had a vague notion of what it meant for “a company to go public” but reading this book (and checking Wikipedia, Investopedia, and other online resources in parallel) made me better understand the process.

  • ** The Rise and Fall of American Growth: The U.S. Standard of Living Since the Civil War ** is a long book by economist Robert Gordon, published in January 2016. For an academic-style book that’s 762 pages long, it is quite well-known, particularly due to the current debates on economic growth in politics. On Google, you can find pages and pages of reviews for Gordon’s book. Most of them mirror Bill Gates’ review in that they praise Gordon for providing a surprisingly complete historical picture of what American life was like in 1870, and how it was completely transformed in the “great century” to 1970. Gone were the days of darkness, backbreaking labor, endless drudgery in chores, and a stale diet, among other things, and in place of those came the electric light bulb, work conditions in heated and air-conditioned offices, the internal combustion engine (leading to automobiles and the airplane), and shopping centers to buy a variety of food and clothes. Gordon’s thesis is that since 1970, America has been in a long reign of slow growth despite the recent progress in AI, IT, and other tech-related fields. There are two reasons: these advances do not match up with those from previous generations (to echo Peter Thiel, “we wanted flying cars but ended up with 140 characters [Twitter]”), and there are headwinds preventing rapid growth such as income inequality, college debt, and demographic trends. He ends with a brief postscript on policy actions that might be useful to counter these trends; I wish more politicians would take note of them as some of his suggestions have broad appeal nowadays. This book is amazing, and despite my close connection with the technology sector, I agree with his thesis. Bill Gates counters by suggesting we’re on the cusp of medical advances, but I’m heavily skeptical about researchers finding cures for cancer and Alzheimer’s disease. It might be challenging for the average reader to go through a book this long, especially one packed with figures and footnotes. My advice? Read it. It’s worth it. I have probably learned more from this book than I have from any other.

Group 4: Biographies and Memoirs

I am reading biographies of famous people because I want to be famous someday. My aim is to be famous for a good reason, e.g., developing technology that benefits large swaths of humanity. (It is obviously easier to become famous for a bad reason than a good reason.)

  • ** Alan Turing: The Enigma ** is the definitive biography of Alan Turing, quite possibly the best computer scientist of all time. The book was written in 1983 by Andrew Hodges, a British mathematics tutor at the University of Oxford (now retired). I discussed this in a separate blog post so I will not repeat the details here.

  • ** My Beloved World ** is Supreme Court Justice Sonia Sotomayor’s memoir, published in 2013. It’s written from the first person perspective and outlines her life from starting in South Bronx and moving up to her appointment as a judge to US District Court, Southern District of New York. It — unfortunately — doesn’t talk much about her experiences after that, getting appointed to the United States Court of Appeals for the Second Circuit in 1998, and of course, her time on the nation’s highest court starting in August 2009. She had a father who struggled with alcoholism and died when she was nine years old, and didn’t appear to be a good student until she was in fifth grade, when she started to obsess over getting “gold stars.” (I can attest to a similar experience over obsessing to get “gold star-like” objects when I was younger.) She then, as we all know, did well in high school and entered Princeton as one of the first incoming batch of women students and Hispanic students, graduating with stellar academic credentials in 1976 and then going on to Yale Law School where she graduated in 1979. The book describes her experiences in vivid terms, and I liked following through her footsteps. I feel and share her pain at not knowing “secrets” that the rich and privileged students had when I was an undergrad (I was clueless about how finance and investment banking jobs worked, and I’m still clueless today.) Overall, I enjoyed the book. It’s brilliantly written, with an engrossing, powerful story. I will be reminded of her key attribute of persistence and determination and focus which she says were key. I’m trying to pursue the same skills myself. While I understand the low likelihood of landing such tiny jobs (e.g., the tech equivalent of a Supreme Court Justice) I do try and think big and that’s what motivates me a lot. I read this book on a day trip where I was sitting in a car passenger seat, and I sometimes dozed off and imagined myself naming various hypothetical Supreme Court Justices.

  • An Appetite for Wonder: The Making of a Scientist is Richard Dawkins’ first of two (!!) autobiographies, published in 2013 and which accounts for the first half of his life. Dawkins is one of the most famous and accomplished scientists today, not only in terms of raw science but also with respect to public outreach and fame (whether famous, in my opinion, or infamous, if otherwise), so perhaps two books is justified. Dawkins discusses his childhood, which he first spent in Africa before moving to England to attend boarding schools; he remarked that the students seemed to be relatively stronger in Africa. I sometimes wish I had attended boarding schools instead of my standard public schools, since perhaps I would have developed independence faster, so it was interesting to read his perspective. After this, Dawkins talks about his undergraduate years at Oxford10 (where his relatives had gone) and this is where I really want to know what he did, because I’m hoping to use my own “appetite for wonder” in science, since I think Artificial Intelligence is the new electricity. But anyway, Dawkins became a professor at Berkeley (!!) but he quickly left to return to England for another position. This book ends with his publication of The Selfish Gene, a book that I want to read one of these days. I’m impressed: it’s a challenge to write an autobiography, but fortunately, Dawkins’ parents saved a lot of letters and information, so that’s good. The book, however, is likely aimed at a niche audience of readers. It was also interesting to Dawkins used to be religious, before becoming an atheist by his late teens (like me, though I was never religious at all). I also liked his stories about computer programming and research, which were a lot simpler back then but presumably harder due to lack of documentation and the Internet.

  • Brief Candle in the Dark: My Life in Science is Richard Dawkins’ second autobiography, written in 2015 and covering the second half of his life, at least, up to that point (he could theoretically still have 30 more years if he lives long enough). He writes more about his life as a professor at the University of Oxford, including his time as the inaugural Simonyi “Professor of the Public Understanding of Science,” which I have to admit was an odd title when I first read it in the back flap of my copy of The God Delusion. He certainly has helped me understand things in this world, and it’s true that I consider Richard Dawkins to be one my heroes. On the other hand, I’m not sure most lay readers would be willing to slog through both of his autobiographies, so keep this in mind in case you’re on the fence about reading this book. It is a non-chronological history of his academic life about debates (uh oh), being on television, writing books, giving talks, and so forth. Dawkins describes various stories about him with other famous people. I also learned a little more about basic evolution. His previous autobiography highlighted how genes — and not the individual — are the unit of evolution, but in his book The Extended Phenotype, he talks about an extension of natural selection onto the physical world (interesting, though one must not misinterpret this). He also emphasizes, and this is something I agree with, that natural selection can still explain complicated structures today that creationists use as evidence against evolution, such as the eye. Natural selection is the only theory we have of what can work gradually and cumulatively. This is key for developing complicated structures; in the absence of evidence, God should not be the default option. I also liked other tidbits of the book, such as how Dawkins did a lot of “evolutionary programming” — I bet he would be interested in reading the research paper Evolution Strategies as a Scalable Alternative to Reinforcement Learning.

  • ** Elon Musk: Tesla, SpaceX, and the Quest for a Fantastic Future ** is a 2015 biography of Elon Musk, written by technology journalist Ashlee Vance. He documents Musk’s chaotic life, both nowadays as the CEO of SpaceX and Tesla and before, when he was struggling to get his companies off the ground and earlier still, when he started his entrepreneurial spirit by starting Zip2. Musk grew up in South Africa and moved to Canada so that he could get to the United States as quickly as possible. Musk had some initial businesses successes, but was forced out of X.com (which particularly hurt as Musk is the personality who wants full control over his companies), then earned some more success with Tesla and SpaceX before teetering on the brink of collapse at the end of 2008 (you know, like the financial “oopsie” we had). Then later, those companies recovered, Musk married a young actress, divorced, then re-married (then divorced again …). The book concludes with some thoughts on Musk’s wild personality and ambitions, and basically says that there is no one like Musk, who still is holding out hope for humans to go to Mars by 2025. This book is an absolute thrill to read. Vance brilliantly writes it so that the reader often feels like he or she is swept up into “Elon Musk”-mode: hard-working, super-charging, and borderline out of control. After reading it, I kept thinking that my work ethic is too soft and weak, and that I better get back to working sixteen hours a day (or less, if I’ve focused really hard in fewer hours). I have two main criticisms of this book. The first is that I was hoping to see more information from his two wives, and for this I’ll probably have to relegate myself to reading Justine Musk’s blog. The second and most important critique is that when Vance wrote an updated epilogue in January 2017, which was five months before I bought the book at Chicago O’Hare International Airport, he never mentioned Musk’s investment in OpenAI, a nonprofit AI research company which aims to produce, or pave the path to, artificial general intelligence. In their introductory blog post from December 2015, they claim to have 1 billion dollars in investment. I’m not sure how much Musk contributed to that, but it must have been a lot!

  • Keeper of the Olympic Flame: Lake Placid’s Jack Shea vs. Avery Brundage and the Nazi Olympics, a recent 2016 book by Michael Burgess, is one that hits home to me because Jack Shea was my great-uncle. Jack Shea was born and raised in Lake Placid, New York, and as a 21-year-old competitor in the 1932 Winter Olympics, he won two gold medals in speed-skating, becoming a hometown hero and putting Lake Placid “on the map.” A few years later, when it became apparent that the next Winter Olympics were going to be in Nazi Germany, Shea urged Avery Brundage (then in charge of American involvement in the Olympics) to boycott out of concerns over Adolf Hitler’s treatment of Jews and other minorities. Shea did not participate in those controversial Olympics, but the Americans did send a team, with relatively disappointing speed-skating results. The book then discusses more about the intersection between politics and sports, and also talks about the odd déjà vu when Lake Placid again hosted the Winter Olympics in 1980, again with politics causing tension (this time, from the Soviet Union). For obvious reasons, I enjoyed reading this book despite its flaws: it’s short and has obvious typos. I like knowing more about my ancestors and what they did, and the photos were really striking. My favorites include 19-year-old Shea shaking hands with then-governor Franklin Roosevelt, another one with Shea and his extended family (including my grandfather), and a third which shows a pre-teen Shea and his brother, Eugene, already in skates. Eugene, incidentally, lived to be 105 years old (!!) before passing away in October this year (obituary here) and was able to contribute photos and assistance to the author. I got to meet Jack Shea once, and he might very well have lived to be 100 years of age had he not been killed by a drunk driver at the age of 91. This was 17 days before his grandson would end up winning a gold medal in the 2002 Salt Lake City Winter Olympics. In my parent’s home, there is a photo of me with my cousin holding his gold medal (it was heavy!). I also have a separate blog post about this book soon after I read it.

Group 5: Conservative Politics and Thoughts

Well, this will be interesting. I’m not a registered Republican, though I possess a surprisingly large amount conservative beliefs, some of which I’m not brave enough to blog about (for obvious reasons). In addition, I believe it is important to understand people’s beliefs across the political spectrum, though for this purpose I exclude the extreme far left (e.g., hardcore Communists) and right (e.g., the fascists and the Ku Klux Klan).

  • ** Please Stop Helping Us: How Liberals Make it Harder for Blacks to Succeed ** a 2014 book written by Wall Street Journal columnist Jason Riley. It’s no secret that (a) most blacks tend to be liberal, I would guess due to the liberals getting the civil rights movement correct in the 1960s, and (b) blacks tend to have more credibility when criticizing blacks compared to whites. Riley, as a black conservative, can get away with roundly criticizing blacks in a way that I wouldn’t do since I do not want to be perceived as a racist. In Please Stop Helping Us, Riley “eviscerates nonsense” as described by his hero, Thomas Sowell, criticizing concepts such as the minimum wage, unions, young black culture, and affirmative action policies, among other things, for the decline in black prosperity. His chief claim is that liberals, while having good intentions, have not managed to achieve their desired results with respect to the black population. He also laments that young blacks tend to watch too much TV, engage in hip-hop culture, and the like. One of his stories that stuck with me was when a young (black) relative asked him: “why are you so white”, when all Riley did was speak proper English and tuck in his shirt. Indeed, variants of this story are common complaints that I’ve seen and heard about from black students and professionals across the political spectrum. I don’t agree with Riley on everything. For instance, Riley tends to ignore or explain away issues regarding racism as it relates to the lack of opportunities for job promotions or advancement, or when blacks are penalized more relative to others for a given crime. On the other hand, we agree on affirmative action, which he roundly criticizes, pointing out that no one wants to be the token “diversity hire”. To his credit, he additionally mentions that Asians are hurt the most from affirmative action, as I pointed out in an earlier blog post, making it a dubious policy when it come to advancing racial equality. In the end, this book is a thought-provoking piece about race. My impression is that Riley genuinely wants to see more blacks succeed in America (as I do), but he is disappointed that the major civil rights battles were all won decades ago, and nowadays current policies do not have the same positive impact factor.

  • ** The Conservative Heart: How to Build a Fairer, Happier, and More Prosperous America **, is a 2015 book by Arthur Brooks, the president of the American Enterprise Institute, officially a nonpartisan think tank but widely regarded (both inside and outside the organization) as a place for conservative public policy development and analysis. Brooks argues that today’s conservatives, while they have most of the technical arguments right (e.g., on the benefits of free enterprise), lack the “moral high ground” that liberals have. Brooks cites statistics showing that conservatives are seen as less compassionate and less caring than liberals. He argues that conservatives can’t be about being anti-everything: government, minimum wage increases, food stamps, etc. Instead, they have to show that they care about people. They need to emphasize an equal starting line for which people can flourish, which contrasts with the common liberal perspective of making the end product equal (by income redistribution or proportional racial representation). One key point Brooks emphasizes is the need for work fulfillment and purpose instead of lying around while collecting checks from the American welfare state. I liked this book and found it engaging and accessible. It is, Brooks says, a book for a wide range of people, including “open-minded liberals” who wish to understand the conservative perspective. I have two major issues with his book, though. The first is that while he correctly points out the uneven recovery and the lack of progress on fixing poverty, he fails to mention the technological forces that have created these uneven conditions (see my technology, economics, and business related books above), much of which is outside the control of any presidential administration or Congress. The second is that I think he’s been proved wrong on a lot of things. President Donald Trump is virtually none of the stuff that a conservative “heart” would suggest and, well, he was elected President (after this book was published, to boot). I wish President Trump would start following Brooks’ suggestions.

  • Conscience of a Conservative: A Rejection of Destructive Politics and a Return to Principle is a brief 2017 book/manifesto by U.S. Senator Jeff Flake of Arizona. Flake is well known for being one of those “Never Trump” style of Republicans since he remains true to certain Republican principles that have arguably fallen out of favor with the recent populist surge of Trump-ian Republicanism in 2016, such as free trade and limited government spending. And yes, I don’t think Republicans can claim to be the party of fiscal prudence nowadays, since Trump is decidedly not a limited spending conservative. In this book, Senator Flake argues that Republicans have to get back to true, Conservative principles and can’t allow populism and immaturity to define their party. He laments at the lack of bipartisanship in Congress, and while he makes it clear that both parties are to blame, in this book he mostly aims at Republicans. This explains why so many Republicans, including Barry Goldwater’s relatives, dislike this book. (Barry Goldwater wrote a book of the same title, “Conscience of a Conservative”, from which Jeff Flake borrowed the title.) I sort of liked this book but didn’t really like it. It still fails to address the notion of how the parties have fallen apart, and he (like everyone else) preaches bipartisanship without proposing clear solutions. Honestly, I think the main reason I read it was not that I think Flake has all the solutions, but that I sometimes think of myself in Congress in my fantasies. Thus, I jumped at the chance to read a book directly from a Congressman, and particularly a book like this where Flake bravely didn’t have his staff revise it to make it more “politically palatable.” It’s a bit raw and lacks the polish of super-skilled writers, but we shouldn’t hold Senators to such a high writing standard so it’s fine with me. It’s unfortunate that Flake isn’t going to seek re-election next year.

Group 6: Self-Help and Personal Development

I’m reading these “personal development” books because, well, I want to be a far more effective person than I am right now. “Effectiveness” can mean a lot of things. I define it as being vastly more productive in (a) Artificial Intelligence research and (b) my social life.

  • ** How to Win Friends and Influence People: The Only Book You Need to Lead You to Success ** is Dale Carnegie’s famous book based on his human interaction courses. It was originally published in 1936, during the depths of the Great Depression, making this book by far the oldest one I’ve read this year. I will not go into too much depth about it since I wrote a summary in an earlier blog post. The good news is that 2017 has been a much better year for me socially, and the book might have helped. I look forward to continuing the upward trend in 2018, and to read other Dale Carnegie books.

  • ** The 7 Habits of Highly Effective People: Powerful Lessons in Personal Change **, written by Stephen R. Covey in 1989, is widely considered to be the “successor” to Dale Carnegie’s classic book (see above summary). In The 7 Habits, Covey argues that the habits are based on well-timed principles and thus do not noticeably vary across different religious groups, ethnic groups, and so forth. They are: “Be Proactive”, “Begin With the End in Mind”, “Put First Things First”, “Think Win-Win”, “Seek First to Understand, Then to be Understood”, “Synergize”, and “Sharpen the Saw”. You can find their details on the Wikipedia page so I won’t repeat the points here, but I will say that the one which really touches upon me is “Think Win-Win”. In general, I am always trying to make more friends, and I’d like these to be win-win. My strategy, which aligns with Covey’s (great minds think alike!), is to start a relationship by doing more work than the other person or letting the other person benefit more. Specifically, this means that I will be happy to (a) take the initiative in setting meeting times and any necessary reservations, (b) drive or travel farther distances, (c) let the other person choose the activity, and so forth. At some point, however, the relationship needs to be reciprocal. Indeed, I often tell people, subtly or not so subtly, that the true test of friendship is if friends are willing to do things for you just as much as you do to them. With respect to the six other principles, there isn’t much to disagree. There is striking similarity to Cal Newport’s Deep Work when Covey discusses high-impact, Quadrant II activities. Possibly my main disagreement with the book is that Covey argues how these principles come (to some extent) from religion and God. As an atheist, I do not buy this rationale, but I still agree with the principles themselves and I am trying to follow them as much as I can. This book has earned a place on my desk along with Dale Carnegie’s classic, and I will always remember it because I want to be a highly effective person.

  • You are a Badass: How to Stop Doubting Your Greatness and Start Living an Awesome Life is a 2013 book by self-help guru Jen Sincero. It’s deliberately written in a very “teenage”-like way, where the author acts like she’s talking directly to the reader as the self-help coach. The target audience seems to be people who have “screwed up” and feel like their life is not as awesome as it could be. She goes through 27 relatively short chapters, each with different generic advice, though she does repeat this each chapter: love yourself. I definitely need reminders about that, since I don’t feel like I am achieving enough in life. However, I was somewhat skeptical of her advice and in general I am a self-help skeptic since I think it’s better for me to build my technical skills than to try and optimize advice from self-help books. Overall, I did not enjoy this book (largely due to the writing style), and I’m surprised it’s gotten so much critical acclaim and that it’s a best-seller. Yes, I will “love myself” but I can’t see myself remembering many other tidbits about this book that I didn’t already know before (e.g., think positive!!). Perhaps this book would be better suited with some concrete success stories of Sincero’s clients.

Group 7: Psychology and Human Relationships

These books are about psychology, broadly speaking, which I suppose can include “human relationships”. I thoroughly enjoyed reading all four of these books.

  • ** Thinking, Fast and Slow ** is a famous 2011 book by Daniel Kahneman, winner of the 2002 Nobel Prize in Economics for his work on decision making. This is a book about psychology and how humans think, and much of it is based on Kahneman’s research with Amos Tversky many decades ago. To make the concepts clearer to the reader, Kahneman describes a story consisting of System 1 and System 2. These are the fast and slow parts of our thinking, respectively, so the former represents our immediate intuition and the latter reflects what happens after we expend nontrivial amounts of effort on some task. Thinking, Fast and Slow is filled with informative anecdotes, thrilling insights, and unexpected contradictions about the way humans think, and supplements those with exercises to the reader. (I normally find these annoying, but here they were reasonable.) Possibly the biggest insight I gained is that human thinking is flawed and is easily manipulated, so I better be extra cautious if I have to make important judgments in my life. (For minor life decisions, I don’t have a hope of remembering all the advice in this 400+ page book.) To be clear, I already knew that humans behaved irrationally, but Kahneman does an excellent job in putting my haphazard thoughts about human irrationality on more solid footing. Kahneman augments that with related topics such as overconfidence (a major issue with CEOs and start-ups) and how anchoring, priming, and baselines influence human preferences. After reading the book, all I can say is, I think (pun intended!) Thinking, Fast and Slow lives up to its billing as a true classic.

  • ** To Sell Is Human: The Surprising Truth About Moving Others ** is a 2012 book by best-selling author Daniel Pink. He argues that we should stop focusing on outdated views of salespeople. That is, that they are slimy, conniving, attempting to rip of us off, etc. Today, one in nine work in “sales” but Pink’s chief message to the reader is that the other eight of nine are also in sales. We try to influence people all the time. So in some sense this is obvious. I mean, if I am aiming to get a girlfriend, then I’m trying to influence her based on my positive qualities. For academics, we sell our work (i.e., research) all the time. That’s what Pink means when he says “everyone is working in sales.” He argues that nowadays, the barriers have fallen (he almost says “The World is Flat” a la Thomas L. Friedman) and that salespeople are no longer people who walk door by door to ask people to buy things. That’s outdated. One possible negative aspect of the book is that I don’t think we need this much “proof” that we’re all salespeople. Yes, some people think only in terms of that job, but all you have to do is say: “hey everyone is a salesperson, if you try to become friends with someone, that counts…” and if you tell that to people, all of a sudden they’ll get it and I don’t think belaboring the point is necessary. On the positive side, the book contains several case studies and lists of things to do, so that I can think of these and reread the book in case I want to apply them in my life. Indeed, as I was reading this book, I was also thinking of ways I could convince someone to become friends with me.

  • ** Lean In: Women, Work, and the Will to Lead ** is a well-known 2013 book by Facebook COO Sheryl Sandberg. It’s a semi-memoir which also acts as a manifesto for women (and men) to be more aware of the gender gap in “prestigious positions” and how to counteract it. By such “prestigious positions” I mean CEOs (particularly of top companies), politicians, and other leadership positions. Women occupy fewer of these positions than men in virtually every country in the world, and Sandberg wants this to change. She outlines numerous factors that hold women back, not all of which are obvious. Her first example deals with parking spots reserved for pregnant women, in which she admits she (despite being a woman!) didn’t think about until she became pregnant herself. Pregnancy is a major focus in this book, along with work-life balance, a typical inclusion in books about women and careers. Sandberg also recounts stories about women being quiet in meetings or not taking seats in the center of a meeting table even when prompted to do so, and lowering their hands when people say there are no more questions (despite how men keep their hands up and thus get to ask more questions). This forms the overall basis for her advice that women must “lean in” and be more involved in discussions. I liked reading this fast-paced book but I also almost felt disappointed, since I anticipated much of the material in advance. Perhaps it’s because I read about gender-related issues frequently. Another possible explanation is that it is hard for me to participate in group meetings, so I often spend more time observing people and noticing things rather than focusing on the subject at hand. On a final note, I’d like to mention that I do, in some sense, believe that “other men are the problem, not me” though I would never say this in public to someone, because (a) it’s politically charged, and (b) I could, of course, make a mistake in the future and thus I would be hypocritical and have to eat my own words. In my adult life, I do not believe I have ever done anything blatantly sexist, though I certainly worry a lot about committing “microaggressions” when I interact with women, and do my best to avoid them to make my female (as well as male) conversationalists feel respected and comfortable.

  • ** Originals: How Non-Conformists Move the World ** is a recent 2016 book by famous Wharton professor Adam Grant, also known as the author of Give and Take. I’ve been aware of Grant for some time, in part because he’s been featured in Cal Newport’s writing as someone who engages in the virtues of Deep Work (see an excerpt here). Yeah, he’s really productive, finishing a PhD in less than three years11 and then becoming the youngest tenured professor at his university. But what is this book about, anyway? In Originals, Grant argues that people who “buck the trend” are often ones who can make a difference for the better. As I anticipated ahead of time, Martin Luther King Jr is in the book, but not for all the reasons I thought. One of them — why procrastination might actually have been helpful (i.e., first mover disadvantage) for him when he was crafting his “I Have a Dream” speech, though one was more realistic: focusing on the victims of crimes (blacks facing discrimination) rather than criticizing the perpetrators. Another nice tidbit from Grant was making sure to emphasize the downsides of your work rather than the positives to venture capitalists, as that will help you look more sincere. Other stuff in this book include how to foster a correct sense of dissent in a company (e.g., Bridgewater Associates is unique in this regard because people freely criticize the billionaire founder Ray Dalio). I certainly felt like some of this was cherry-picking, which admittedly is unavoidable, but this book seems to pursue that more than others. Nonetheless, a lot of the advice seems reasonable and I hope to apply it in my life.

Group 8: Miscellaneous

These books, in my opinion, don’t neatly align in one of the earlier groups.

  • ** Knocking on Heaven’s Door: How Physics and Scientific Thinking Illuminate the Universe and the Modern World ** is Harvard physics professor Lisa Randall’s second of three major books. Last year, I read her most recent book Dark Matter and the Dinosaurs, so this is “going back” in time back to 2011. Sorry, I know should have read them in order. But anyway, this book is a fascinating exploration of what I argue are two major topics. First, the Large Hadron Collider — the well-known experimental setup that revealed the Higgs Boson particle in 2012 and earned Peter Higgs an Nobel Prize. Randall describes how the experiment was set up in great detail, but with juuuuuust enough clarity for non-physicists like me to barely follow. I don’t have much knowledge about the LHC, and indeed I didn’t even know it was a fantastic engineering feat; it is an enormous system built deep underground in Europe, as the pictures in the book helped to illuminate. The second major part of the book is about scientific thinking itself: why do scientists revise theories, why is the notion of scale important, why is quantum mechanics important at smaller distances, but why can we “average out” its effects with Newtonian physics? I learned a little about how the Standard Model in physics works, and it was great to see how she describes the scientific approach to thinking. Randall also discusses cosmology in this book, but it’s much shorter relative to particle physics and feels slightly out of place, but fortunately any reader who wants an overview in cosmology should just read Dark Matter and the Dinosaurs. Overall, this is a book that somehow remains fascinating and mostly accessible despite all the physics facts and jargon. It’s tricky to write science books for the general public. Randall does a good job in that when I was reading the book and felt somewhat confused at the jargon, I felt like it was my fault for my incompetence, and not hers. I am now thinking about reading her first book, Warped Passages, or her e-book on the Higgs Discovery. I’ll definitely be on the lookout for any future books she publishes!

  • ** The Signal and the Noise: Why So Many Predictions Fail – But Some Don’t ** is Nate Silver’s 2012 book where he urges us to consider various issues that might be adversely affecting the quality of predictions. They range from the obvious, such as political biases which affect our assessment of political pundits (known as “hedgehogs” in his book), and perhaps less obvious things such as a bug in the Deep Blue chess program which nonetheless grandmaster Gary Kasparov took to meaning that Deep Blue could “predict twenty moves into advance.” I really enjoyed this book. The examples are far ranging: how to detect terrorist attacks (a major difficulty but one with enormous political importance) to playing poker (Silver’s previous main source of income), to uncertainties involving global warming models (always important to consider), and to the stock market (this one is hardest for me to understand given my lack of background knowledge on the stock market, but I am learning and working to rectify this!). The one issue I have is that Silver seems to just assume: hey let’s apply Bayes’ rule to fix everything, so that we have a prior of , and we assume the probability of … and therein lies the problem. In real settings we rarely get those and values to a high degree of accuracy. But I have no issue with the general idea of revising predictions and using Bayes’ rule. I encourage you to see a related critique in The New Yorker. The reality, by the way, is that most current professional statisticians likely employ a mix of Frequentist and Bayesian statistics. For a more technical overview, check out Professor Michael I. Jordan’s talk on Are You A Bayesian or a Frequentist?.

  • ** The Soul of an Octopus: A Surprising Exploration into the Wonder of Consciousness ** is a splendid 2015 book by author Sy Montgomery, who has written numerous biology-related books about animals. I would call this entirely a popular science book; it’s more like a combination of the author discovering octopuses and describing her own experience visiting the New England aquarium, learning how to scuba dive, watching octopuses having sex in Seattle, and of course, connecting with octopuses. To be frank, I had no idea octopuses could do any of the things she mentions in the book (such as walking on dry land and squeezing through a tiny hole to get out of a tank). Clearly, aquariums have their hands full trying to deal with octopuses. Much of the book is about trying to connect with the three octopuses the New England aquarium has; the author regularly touches and feeds the octopuses, observing and attempting to understand them. I was impressed by the way Montgomery manages to make the book educational, riveting, and emotional all at once, which was surprising to me when I found out about the book’s title. It’s surely a nice story, and that’s what I care about.

  • Nothing Ever Dies: Vietnam and the Memory of War is a book by USC English Professor Viet Thanh Nguyen, published in 2016 and a finalist for the National Book Award in Non-Fiction that same year. It’s not a recap or history of the Vietnam War (since that subject has been beaten to death) but instead it focuses specifically on how people from different sides (obviously, American and Vietnamese, but also the rest of the world) view the war, because that will shape questions such as who is at fault and should make reparations and also how we can avoid similar wars in the future. It’s an academic-style book, so the writing is a bit dry and it’s important not to read this when tired. I think it provides a useful perspective on the Vietnam War and memories in general. Nguyen travels to many areas in Vietnam and Asia and explores how they view America — for instance, he argues that South Korea attempts to both ally with the US and look down on Vietnam with contempt. I found the most thought-provoking discussion to be about identity politics and how minorities often have to be the ones describing their own experiences. I’ve observed this in the books I read, in which if they’re written by a minority author (and here I’ll include Asians despite how critics of the tech industry bizarrely decide otherwise) are often about said minority. Other interesting (though obvious) insights include how the entire war machine and capitalism of the US means it can spread its memories of the war more effectively than Vietnam can. Thus, the favorable American perspective of the US as attempting to “save” minorities is more widespread, which puts America in a better light than (in my opinion, channeling my inner Noam Chomsky) it deserves.

  • The Once and Future Liberal: After Identity Politics is a short book (describing it as an essay is probably more accurate) written by humanities professor Mark Lilla of Columbia University. This book grew out of his fantastic (perhaps my all-time favorite) Op-Ed in the NYTimes about the need to end identity politics, or specifically identity liberalism. I agree wholeheartedly; we need to stop treating different groups of people as monolithic. Now, it is certainly the case that racism or mistreating of any group must be called out, and white identity politics is often played on the right, versus the variety of identities on the left. Anyway, this short book is split into three parts: anti-politics, pseudo-politics, and politics, but this doesn’t seem to have registered much to me, and the book is arranged in a different style as I might have hoped. I was mostly intrigued by how he said Roosevelt-esque liberalism dominated from roughly 1930 to 1970. Then the Reagan-esque conservatism (i.e., the era of the individual) has dominated from 1980 to 2016 or so, and now we’re supposed to be starting a new era as Trump has demolished the old conservatism. But Lilla is frustrated that modern liberalism is so obsessed about identity, and quite frankly, so am I. He is correct, and many liberals would agree, that change must be aimed locally now, as Republicans have dominated state and local governments, particularly throughout the Obama years. I do wish, however, that he had focused more directly on (a) how groups are not monolithic, (b) why identity politics is bad politics. I know there was some focus, but there didn’t seem to be enough for me. But I suppose, this being a short essay, he wanted to prioritize the Roosevelt-Reagan parallels, which in all fairness is indeed interesting to ponder.

  • ** Climate of Hope: How Cities, Businesses, and Citizens can Save the Planet **, a 2017 book jointly written by Michael Bloomberg and Carl Pope. Surprisingly, considering that I was born and raised in New York state all my life (albeit, upstate and not in the city) the first time I really learned about Bloomberg was when he gave the commencement speech at my college graduation. You can view the video here, and in fact, to the right you can barely see the hands of a sign language interpreter who I really should re-connect with sometime soon. Climate of Hope consists of a series of chapters, which are split into half from Bloomberg’s perspective, half from Pope’s perspective. The dynamics between the two men are interesting. Pope is a “typical” Sierra Nevada member, while Bloomberg is known for being a ridiculously-rich billionaire and a three-term (!!) mayor of New York City.12 The book is about cities, businesses, and citizens, and the omission of national governments is no accident: both men have been critical of Washington’s failure to get things done. Bloomberg and Pope aim their ire at the “climate change deniers” in Washington, though they do levy slight criticism on Democrats for failing to support nuclear power. They offer a brief scientific background on climate change, and then argue that new market forces and the rise of cities (thus greener due to more public transportation and more cramped living quarters) means we should be able to emphasize more renewable energy. One key thing I especially agree with is that to market policies that promote renewable energy — particularly to skeptical conservatives — people cannot talk about how “worldwide temperatures in 2100 will be two degrees higher.” Rather, we need to talk about things we can do now, such as saving money, protecting our cities, creating construction jobs, protecting our health from smog, all these thing we can do right now and which will have the effect of fighting long-term climate change anyway. I enjoyed this easy-to-read and optimistic book, though it’s also fair to say that I tend to view Bloomberg quite favorably and honor his commitment to getting things done rather than having dysfunction in Washington. Or maybe I just want to obtain a fraction of his professional success in my life.

That’s all for 2017!


  1. Most of the academic papers that I read can be found in this GitHub repository

  2. You’ll also notice in that link that Stuart Russell says he thinks superintelligence will happen in “more than 25 years” but he thinks it will happen. Russell’s been one of the leading academics voicing concern about AI. I’m not sure what has been created out of it, except raising a discussion of AI’s risks, kind of like how Barrat’s book doesn’t really propose solutions. (Disclaimer: I have not read all of Russell’s work on this, and I might need to see this page for information.) 

  3. In this interview, Oren Etzioni said that AI leaders were not concerned about superintelligence, and even quoted an anonymous AAAI Fellow who said that Nick Bostrom was “the Donald Trump of AI”. Stuart Russell, who has praised Superintelligence, wrote a rebuttal to Etzioni, who then apologized to Bostrom. 

  4. Of course, this raises the other problem with MOOCs. Only people who have sufficient motivation to learn are actually taking advantage of MOOCs, and these tend to be skewed towards those who are already well-educated. Under no circumstances is Brynjolfsson someone who needs a MOOC for his career. But there are many people who cannot afford college and the like, but who don’t have the motivation (or time!) to learn on their own. Is it fair for them to suffer under this new economy? 

  5. Eric Schmidt got his computer science PhD from Berkeley in 1982. So at least I know someone famous essentially started off on a similar career trajectory as I am. 

  6. I didn’t realize this until the authors put it in a footnote, but Jonathan Rosenberg’s father is Nathan Rosenberg, who wrote the 1986 book How the West Grew Rich which I also read this year. Heh, the more I read the more I realize that it’s a small world among the academic and technically elite among our society. 

  7. This blog is hosted on GitHub and built using software called Jekyll. Click here to see the source code

  8. To compare, How the West Grew Rich is less than half the length of The Rise and Fall of American Growth. In addition, I skipped most footnotes for the former, but read all the footnotes for the later. 

  9. A quick thanks to Ben and Marc for helping to fund Berkeley’s Computer Science Graduate Student Association! 

  10. Dawkins mentions that, if anything was “the making” of him, Oxford was. For me, I consider Berkeley to be “the making of me” as I’ve learned much more, both academically and otherwise, here than at Williams College. 

  11. Usually, someone completing a PhD in 2-3 years raises red flags since they likely didn’t get much research done and may have wanted to graduate ASAP. Grant is an exception, and it’s worth noting that there are also exceptions in computer science

  12. Given the fact that Bloomberg was able to buy his way into being a politician, I really think the easiest way for me to enter national politics is to have enormous success in the business and technology sector. Then I can just buy my way in, or use my connections. It’s unfortunate that American politics is like this, but at least it’s better than having a king and royal family.