Category: Books

Summary: The late Doug Engelbart was the inventor of the mouse, but that is the least interesting thing about him. He is the creator of “The Mother of All Demos”, a 1968 demo that included hypertext, teleconferencing, word processing, hypermedia, and, yes, the mouse. The 1968 demo was so amazing that he was accused of faking the whole thing.

“The Engelbart Hypothesis: Dialogs with Douglas Engelbart” by Valerie Landau, Eileen Clegg, and, yes, Douglas Engelbart, is an interview of Engelbart followed by a series of short pieces by luminaries who knew and were motivated by Engelbart’s vision (Alan Kay and Vint Cerf among others.) The interviews cover a lot of Engelbart’s thoughts on machines augmenting the human intellect and enabling groups of humans to achieve more than they could individually. If you’ve read Augmenting Human Intellect: A Conceptual Framework, Engelbart’s famous whitepaper which ended up leading to the mother of all demos, there is a lot that is presented along those lines. There is also a lot of biographical material here of interest, for example the story about his talk that perhaps indirectly led to Moore’s work on Moore’s law. All in all a fine introduction to these ideas and emphasizes how much the human part of the story motivated Engelbart. The second half interviews give perspective on how others have taken what Engelbart conceived and moved it to the ‘real world’.

Rating: Read Augmenting Human Intellect: A Conceptual Framework. If you find that fascinating, you’ll love this book. Note: the Kindle version of the book has some severe formatting problems. These problems don’t make it totally unreadable but there are footnotes/asides that need to be un-winded from the main flow of the text.

Speculative: Out speculating one of the greatest speculators of the twentieth century seems like a huge task. One of the central original ideas of Engelbart’s augmentation strategy was to work towards augmenting programmers. There are a lot of reasons that this was a great starting point, but ever since I can remember reading about this I’ve wondered what sorts of tools I would use to augment doing theoretical physics. When I try to take apart what I am doing when thinking about a theory problem, it is amazing how much of it is just involved in creating the structures to conceptualize the problem. Each new problem, at least for me, leads to a new domain specific language for the problem. Frustratingly some of the components of this step should be handled more adeptly by a computer. Some people do this by resorting to tools like Mathematica to “play” with examples. But it feels like there is a missing tool which is not so tightly coupled to our math notation, but is both geometric and automatic. Somewhere between a CAD and Mathematica it feels like there is a space for visualized mathematics that a theorist could use to think through their problems (I will admit that I am a geometry guy, not an algebraist. When I meet one the later my mind can barely grasp how they are thinking. Likely they have a tool they would like too.)

Summary: The late Doug Engelbart was the inventor of the mouse, but that is the least interesting thing about him. He is the creator of “The Mother of All Demos”, a 1968 demo that included hypertext, teleconferencing, word processing, hypermedia, and, yes, the mouse. The 1968 demo was so amazing that he was accused of faking the whole thing.

“The Engelbart Hypothesis: Dialogs with Douglas Engelbart” by Valerie Landau, Eileen Clegg, and, yes, Douglas Engelbart, is an interview of Engelbart followed by a series of short pieces by luminaries who knew and were motivated by Engelbart’s vision (Alan Kay and Vint Cerf among others.) The interviews cover a lot of Engelbart’s thoughts on machines augmenting the human intellect and enabling groups of humans to achieve more than they could individually. If you’ve read Augmenting Human Intellect: A Conceptual Framework, Engelbart’s famous whitepaper which ended up leading to the mother of all demos, there is a lot that is presented along those lines. There is also a lot of biographical material here of interest, for example the story about his talk that perhaps indirectly led to Moore’s work on Moore’s law. All in all a fine introduction to these ideas and emphasizes how much the human part of the story motivated Engelbart. The second half interviews give perspective on how others have taken what Engelbart conceived and moved it to the ‘real world’.

Rating: Read Augmenting Human Intellect: A Conceptual Framework. If you find that fascinating, you’ll love this book. Note: the Kindle version of the book has some severe formatting problems. These problems don’t make it totally unreadable but there are footnotes/asides that need to be un-winded from the main flow of the text.

Speculative: Out speculating one of the greatest speculators of the twentieth century seems like a huge task. One of the central original ideas of Engelbart’s augmentation strategy was to work towards augmenting programmers. There are a lot of reasons that this was a great starting point, but ever since I can remember reading about this I’ve wondered what sorts of tools I would use to augment doing theoretical physics. When I try to take apart what I am doing when thinking about a theory problem, it is amazing how much of it is just involved in creating the structures to conceptualize the problem. Each new problem, at least for me, leads to a new domain specific language for the problem. Frustratingly some of the components of this step should be handled more adeptly by a computer. Some people do this by resorting to tools like Mathematica to “play” with examples. But it feels like there is a missing tool which is not so tightly coupled to our math notation, but is both geometric and automatic. Somewhere between a CAD and Mathematica it feels like there is a space for visualized mathematics that a theorist could use to think through their problems (I will admit that I am a geometry guy, not an algebraist. When I meet one the later my mind can barely grasp how they are thinking. Likely they have a tool they would like too.)

Summary: In grad school a small group of friends would often debate “Nature versus Nurture” over beers. Thing is, I could never remember which side I wanted to defend and so had to make my arguments “flexible”. The Sports Gene: Inside the Science of Extraordinary Athletic Performance by David Epstein feels like that argument restricted to the world of extreme athletic ability. Epstein wants to understand what makes elite athletes and what role genetics plays in these extraordinary athletes. How much does practice matter (are there naturals)? Are there specific genes that one can point to or is it a confluence of multiple genes or does genetics play no role? More difficult, what about regional effects like certain Kenyans being amazing long distance runners? Epstein romps through a large number of sports trying to flexibly suss out the answer to the role of genetics in athletics.

Rating: Worth your time if you like sports. Causality is difficult in this field, and at times Epstein drops back on a data machine gun with anecdotal grenades (those this data and these anecdotes are mostly interesting.) At other times he is careful to not push the causality bar too far. Even in cases like the distinction between woman and men in sports convincing evidence is surprising hard to come by. Discussion of the variance of the 10,000 hour rule was my favorite part (along with observations about why baseball hitters are good: hint it is not reaction time!)

Speculation: Thinking about the difficulty of experiments in this field: will there someday be advertisements in magazines “Couples: Participate in a Study Identifying Genes for Long Distance Running?”

Summary: In grad school a small group of friends would often debate “Nature versus Nurture” over beers. Thing is, I could never remember which side I wanted to defend and so had to make my arguments “flexible”. The Sports Gene: Inside the Science of Extraordinary Athletic Performance by David Epstein feels like that argument restricted to the world of extreme athletic ability. Epstein wants to understand what makes elite athletes and what role genetics plays in these extraordinary athletes. How much does practice matter (are there naturals)? Are there specific genes that one can point to or is it a confluence of multiple genes or does genetics play no role? More difficult, what about regional effects like certain Kenyans being amazing long distance runners? Epstein romps through a large number of sports trying to flexibly suss out the answer to the role of genetics in athletics.

Rating: Worth your time if you like sports. Causality is difficult in this field, and at times Epstein drops back on a data machine gun with anecdotal grenades (those this data and these anecdotes are mostly interesting.) At other times he is careful to not push the causality bar too far. Even in cases like the distinction between woman and men in sports convincing evidence is surprising hard to come by. Discussion of the variance of the 10,000 hour rule was my favorite part (along with observations about why baseball hitters are good: hint it is not reaction time!)

Speculation: Thinking about the difficulty of experiments in this field: will there someday be advertisements in magazines “Couples: Participate in a Study Identifying Genes for Long Distance Running?”

Summary: In grad school a small group of friends would often debate “Nature versus Nurture” over beers. Thing is, I could never remember which side I wanted to defend and so had to make my arguments “flexible”. The Sports Gene: Inside the Science of Extraordinary Athletic Performance by David Epstein feels like that argument restricted to the world of extreme athletic ability. Epstein wants to understand what makes elite athletes and what role genetics plays in these extraordinary athletes. How much does practice matter (are there naturals)? Are there specific genes that one can point to or is it a confluence of multiple genes or does genetics play no role? More difficult, what about regional effects like certain Kenyans being amazing long distance runners? Epstein romps through a large number of sports trying to flexibly suss out the answer to the role of genetics in athletics.

Rating: Worth your time if you like sports. Causality is difficult in this field, and at times Epstein drops back on a data machine gun with anecdotal grenades (those this data and these anecdotes are mostly interesting.) At other times he is careful to not push the causality bar too far. Even in cases like the distinction between woman and men in sports convincing evidence is surprising hard to come by. Discussion of the variance of the 10,000 hour rule was my favorite part (along with observations about why baseball hitters are good: hint it is not reaction time!)

Speculation: Thinking about the difficulty of experiments in this field: will there someday be advertisements in magazines “Couples: Participate in a Study Identifying Genes for Long Distance Running?”

After realizing how few book I read last year, I’ve decided to make a conscious effort to read more.  As a way to help me keep it up I’ve decided it would be fun to add “reviews” for each of the books I’ve read.  Of course, I’m bad at reviews so I’m taking a slightly different approach, giving a brief summary and then describing the crazy ideas I had while reading the book.

Summary: Suppose I told you that I ran a study where I had experts and monkeys try to predict the price of a stock a month in the future.  My findings where that monkeys were no better than experts.  What would you say?  Would you give up any idea of predicting the price?  What if I then told you that there was a group in my study, monkeys raised on vegetarian diets, who did perform better than the experts and overall proportion of experts?  Would this change your mind about the predictability of stock priced?  What if I had told you instead that the subgroup that outperformed were had instead of being vegetarian monkeys, they were Harvard educated monkeys?

Superforecasting: The Art and Sciences of Prediction by Philip E. Tetlock and Dan Gardner considers these questions for expert predicting world events.  Previous research by these and other researchers had showed that self described experts were no better, on average, to other groups of people.  But this of course does not mean that there aren’t subgroups of people in these studies who might actually be reproducibly good at predictions.  Superforecasting is the story of such a group.

Rating: Worth the time! Assuming you buy the methodology, some ideas for the characteristics of becoming a better predictor.

Speculation: In 8th grade I had a teacher who, like Babe Ruth point his bat to the bleachers, predicted both the fall of the Berlin Wall and the Tienanmen square revolt.  Imagine you had the ability to predict macro political changes, but instead of like my teacher, the predictions pointed to a world you did not want to see.  How could your psyche with stand this?  What is the psychological toll of seeing the future but being unable to impact it enough?

After realizing how few book I read last year, I’ve decided to make a conscious effort to read more.  As a way to help me keep it up I’ve decided it would be fun to add “reviews” for each of the books I’ve read.  Of course, I’m bad at reviews so I’m taking a slightly different approach, giving a brief summary and then describing the crazy ideas I had while reading the book.

Summary: Suppose I told you that I ran a study where I had experts and monkeys try to predict the price of a stock a month in the future.  My findings where that monkeys were no better than experts.  What would you say?  Would you give up any idea of predicting the price?  What if I then told you that there was a group in my study, monkeys raised on vegetarian diets, who did perform better than the experts and overall proportion of experts?  Would this change your mind about the predictability of stock priced?  What if I had told you instead that the subgroup that outperformed were had instead of being vegetarian monkeys, they were Harvard educated monkeys?

Superforecasting: The Art and Sciences of Prediction by Philip E. Tetlock and Dan Gardner considers these questions for expert predicting world events.  Previous research by these and other researchers had showed that self described experts were no better, on average, to other groups of people.  But this of course does not mean that there aren’t subgroups of people in these studies who might actually be reproducibly good at predictions.  Superforecasting is the story of such a group.

Rating: Worth the time! Assuming you buy the methodology, some ideas for the characteristics of becoming a better predictor.

Speculation: In 8th grade I had a teacher who, like Babe Ruth point his bat to the bleachers, predicted both the fall of the Berlin Wall and the Tienanmen square revolt.  Imagine you had the ability to predict macro political changes, but instead of like my teacher, the predictions pointed to a world you did not want to see.  How could your psyche with stand this?  What is the psychological toll of seeing the future but being unable to impact it enough?

After realizing how few book I read last year, I’ve decided to make a conscious effort to read more.  As a way to help me keep it up I’ve decided it would be fun to add “reviews” for each of the books I’ve read.  Of course, I’m bad at reviews so I’m taking a slightly different approach, giving a brief summary and then describing the crazy ideas I had while reading the book.

Summary: Suppose I told you that I ran a study where I had experts and monkeys try to predict the price of a stock a month in the future.  My findings where that monkeys were no better than experts.  What would you say?  Would you give up any idea of predicting the price?  What if I then told you that there was a group in my study, monkeys raised on vegetarian diets, who did perform better than the experts and overall proportion of experts?  Would this change your mind about the predictability of stock priced?  What if I had told you instead that the subgroup that outperformed were had instead of being vegetarian monkeys, they were Harvard educated monkeys?

Superforecasting: The Art and Sciences of Prediction by Philip E. Tetlock and Dan Gardner considers these questions for expert predicting world events.  Previous research by these and other researchers had showed that self described experts were no better, on average, to other groups of people.  But this of course does not mean that there aren’t subgroups of people in these studies who might actually be reproducibly good at predictions.  Superforecasting is the story of such a group.

Rating: Worth the time! Assuming you buy the methodology, some ideas for the characteristics of becoming a better predictor.

Speculation: In 8th grade I had a teacher who, like Babe Ruth point his bat to the bleachers, predicted both the fall of the Berlin Wall and the Tienanmen square revolt.  Imagine you had the ability to predict macro political changes, but instead of like my teacher, the predictions pointed to a world you did not want to see.  How could your psyche with stand this?  What is the psychological toll of seeing the future but being unable to impact it enough?

Another slow year on reading. I would like to blame work, but my inability to avoid reading random stuff on the Internet is to blame. I definitely recommend “Governing the Commons”, it’s wonkish but gives an interesting view on a middle way for common goods. (Note that the links below are affiliate links meaning if you click on them and buy items then Amazon gives me $.)

Nonfiction

• Governing the Commons: The Evolution of Institutions for Collective Action (Political Economy of Institutions and Decisions) by Elinor Ostrom – Best non-fiction I read this year. Wonkish.
• The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World by Pedro Domingos – Not quite a popularization, and not enough detail for the technical minded, but a good look into the views of a leading machine learner.
• The New Jim Crow by Michelle Alexander – I tend to avoid political books that I agree with, but this one really drives home how large a problem the U.S. faces in dealing with the mass incarceration of black Americans.
• The Idea Factory: Bell Labs and the Great Age of American Innovation by Jon Gertner – hit or miss, not enough analysis of what made Bell labs special for my liking
• Dreamland: The True Tale of Americas Opiate Epidemic by Sam Quinones – Good journalism.
• The Prize: Who’s in Charge of America’s Schools? by Joshua Foer – Mostly focuses on the political story, not enough on the data side of the world.

Fiction

• Seveneves: A Novel by Neal Stephenson –Three books in one, first book is Stephenson in top form.
• Apex: Nexus Trilogy Book 3 (Nexus Arc) by Ramez Naam – Conclusion to the Nexus trilogy, whole trilogy is worth reading.
• The Three-Body Problem by Cixin Liu, translated by Ken Liu –A slow unraveling of a mysterious nearby world. Actually think the next book (below) is slightly better.
• The Dark Forest by Cixin Liu, translated by Joel Martinsen – Second in series, am eagerly awaiting translation of third.
• Ascension Cycle (The Ascendant Series Book 1) by Michael JC Brown Virtualization to the extreme.
• Fear the Future (The Fear Saga Book 3) by Stephen Moss Conclusion to the fear saga, felt it was not up to the standards of the first book.
• Expanse novels and novella
  • Nemesis Games (The Expanse) by James S.A. Corey – Book 5 of the Expanse. Split story line and no real clean finish, but excellent nonetheless.
  • The Churn: An Expanse Novella (The Expanse) by James S.A. Corey – Amos backstory.
  • The Butcher of Anderson Station: A Story of The Expanse by James S.A. Corey
  • Gods of Risk: An Expanse Novella (The Expanse) by James S.A. Corey
  • The Vital Abyss: An Expanse Novella (The Expanse) by James S.A. Corey
• Beacon 23 serialization
  • Beacon 23: Part One: Little Noises (Kindle Single) by Hugh Howey
  • Beacon 23: Part Two: Pet Rocks (Kindle Single) by Hugh Howey
  • Beacon 23: Part Three: Bounty (Kindle Single) by Hugh Howey
  • Beacon 23: Part Four: Company (Kindle Single) by Hugh Howey
  • Beacon 23: Part Five: Visitor (Kindle Single) by Hugh Howey
• The Great Symmetry by James R Wells
• Edge Station by Michael Glaviano
• The God Organ by Anthony J Melchiorri
• Post-Human Series Books 1-4 by David Simpson
• Warship (Black Fleet Trilogy, Book 1) by Joshua Dalzelle
• Blindsight (Firefall) by Peter Watts

I was not able to get a ton of reading done this year, though I did spend a lot of time reading algebraic geometry texts, which is not reflected in the list below. Certainly the book I enjoyed the most this year was Edward Frenkel’s “Love and Math: The Heart of Hidden Reality”. The subject area itself is fascinating. Definitely read this if you want to know what the Langland’s program is and how it fits in with the bigger picture of modern mathematics. I also loved the way that Frenkel weaved his personal story into the math story in such a smooth manner. The most surprising book for me this year was “A Calculated Life” by Anne Charnock, which I really didn’t like for the first few pages, but which grew and grew into a beautiful story, touching, story.

Non-fiction, ordered by most to least recommended

• Love and Math: The Heart of Hidden Reality by Edward Frenkel
• The Righteous Mind: Why Good People Are Divided by Politics and Religion by Jonathan Haidt
• Moonwalking with Einstein: The Art and Science of Remembering Everything by Joshua Foer
• The Better Angels of Our Nature: Why Violence Has Declined by Steven Pinker
• Where Good Ideas Come From by Steven Johnson
• Team Geek: A Software Developer’s Guide to Working Well with Others by Brian Fitzpatrick and Ben Collins-Sussman
• Getting More: How You Can Negotiate to Succeed in Work and Life by Stuart Diamond
• The Emperor of All Maladies: A Biography of Cancer by Siddhartha Mukherjee

Fiction, ordered by most to least recommended

• Sand Omnibus by Hugh Howley
• A Calculated Life by Anne Charnock
• Fear the Sky (The Fear Saga Book 1) by Stephen Moss
• Fear the Survivors (The Fear Saga Book 2) by Stephen Moss
• Whiskey Tango Foxtrot by David Shafer
• The Old Equations by Jake Kerr
• The Robot Chronicles (The Future Chronicles Book 1) with stories by Hugh Howey, Matthew Mather, Samuel Peralta, David Adams, Ann Christy, Nina Croft, WJ Davies, Patrice Fitzgerald, Jason Gurley, Deirdre Gould, A.K. Meek, Edward W. Robertson, Endi Webb, David Gatewood, and David Simpson
• Cronix by James Hider
• Cibola Burn (The Expanse Book 4) by James S.A. Corey
• Glitch: A Short Story by Hugh Howley
• Diaspora by Greg Egan
• The World of Kurt Vonnegut: Peace in Amber by Hugh Howley
• Legendary Detective at the World’s End (Volume 1) by Kaye Wagner
• Pennsylvania Omnibus by Michael Bunker
• A Not So Singular World by Patrick Hatt