Interesting Books In 2020

There have been a lot of things we haven’t been able to do during the last nine months. But it’s been a good time for reading ebooks and listening to audiobooks. So my on-again-off-again tradition of highlighting interesting books that I have read in the year is on again.

These books have not all been published during the last year, but are ones I’ve read this past year and thought worth mentioning to other folks who read this blog.  You’ll note that this is an eclectic combination of books on technology, government, the economy and other non-fiction – but that’s the range of topics that my blog is about.

Anyway, here’s my list for 2020 and a blurb as to why each book is on the list.  I have obviously eliminated from the list the many other books that I’ve read, which I would not recommend you spend your time on. 😊

Technology, AI/Machine Learning and Science

  1. David Carmona – The AI Organization: Learn from Real Companies and Microsoft’s Journey How to Redefine Your Organization with AI (2019). Perhaps too many examples from Microsoft, but it is a really good book from A to Z on artificial intelligence.
  2. Cliff Kuang and Robert Fabricant – User Friendly: How the Hidden Rules of Design Are Changing the Way We Live, Work, and Play (2019). Very interesting review of the leading good (and sometimes bad) user interfaces.
  3. Matthew O. Jackson – The Human Network: How Your Social Position Determines Your Power, Beliefs, and Behaviors (2019). Good, understandable explanations of network measures and phenomena in various domains.
  4. Damon Centola – How Behavior Spreads: The Science of Complex Contagions (2018). Provides a nuanced view of the best time to use weak or strong ties, especially in leading changes in an organization or community.
  5. Eric Topol – Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again (2019). Although it is mostly about the ways that artificial intelligence can re-humanize the patient-doctor relationship, it even has a pretty good, understandable review of general artificial intelligence and machine learning concepts.
  6. Lisa Feldman Barrett – How Emotions Are Made: The Secret Life of the Brain (2017). The title highlights emotions, but this book is not just about emotions. It instead offers a paradigm shift about how the brain works.
  7. Jodie Archer and Matthew L. Jockers – The Bestseller Code: Anatomy of a Blockbuster Novel (2016). interesting book, better and more nuanced than the usual summaries about machine learning models to predict the success of books.
  8. Leonard Mlodinow – The Drunkard’s Walk: How Randomness Rules Our Lives (2009). Interesting explanations of the implications of probability theory and how most people get probability wrong.
  9. Scott Rigby and Richard M Ryan – Glued to games: how video games draw us in and hold us spellbound (2011). Good review of computer-based games, especially the psychological aspects.

Leadership And Business

  1. Jim McKelvey – The innovation stack: building an unbeatable business one crazy idea at a time (2020). Good, insightful and sometimes funny book by one of the co-founders of Square, with the proposition that success is the result of a chain (better word than stack) of innovations rather than just one big one.
  2. Scott Kupor – Secrets of Sand Hill Road: Venture Capital and How to Get It (2019). If you want to know how venture capitalists look at startups, this tells you how.
  3. Geoffrey G. Parker, Marshall W. Van Alstyne, Sangeet Paul Choudary – Platform Revolution: How Networked Markets Are Transforming the Economy – and How to Make Them Work for You (2017). While other books on the subject go more deeply into the broader policy implications of platforms, if you want to start a platform business, this is your best, almost required, user manual.
  4. Daniel Coyle – The Culture Code: The Secrets of Highly Successful Groups (2018). Culture is a frequently used word to explain the forces that drive behavior in organizations, but too often the concept is fuzzy. This book is one of the clearest and best on the subject.
  5. Dan Heath – Upstream: The Quest to Solve Problems Before They Happen (2020). Good, as usual for the Heath brothers, well written down to earth, but important concepts underneath and guidance at looking at the more fundamental part of problems that you are trying to solve.
  6. Matt Ridley – How Innovation Works: And Why It Flourishes in Freedom (2020). Includes many short histories of key innovations, not just invention, with an emphasis on the iterative and collaborative nature of the innovation process. Ridley advocates curtailing IP protections, thus providing more tolerance of risky experiments/innovations.
  7. Rita McGrath – Seeing Around Corners: How To Spot Inflection Points In Business Before They Happen (2019). Columbia Professor McGrath has made clear that no strategy is sustainable for a long time and in this book, she helps you figure out when you are at good or bad inflection points.

The Economy And Government

  1. Robert H. Frank – Under the Influence: Putting Peer Pressure to Work (2020). Frank is one of the most creative economists around and in this review of behavioral economics, he highlights how people pursue relative positions of wealth, rather than merely being rational maximizers of wealth.  He also offers a good discussion of public policies to pursue, that are based on this understanding of economic behavior.
  2. Stephanie Kelton – The Deficit Myth: Modern Monetary Theory and the Birth of the People’s Economy (2020). Well written, clear exposition of modern monetary theory and the positive and negative consequences of having completely fiat money (no gold standard or fixed currency exchanges). Professor Kelton is an increasingly influential economist and her ideas – whether or not she is given credit – have enabled the US Government to spend more with less angst than used to be the case.
  3. Abhijit V. Banerjee and Esther Duflo – Good Economics for Hard Times: Better Answers to Our Biggest Problems (2019). A review of economics research – and, more important, its limits – in addressing major socio-economic problems.
  4. Matthew Yglesias – One Billion Americans: The Case for Thinking Bigger (2020). Although no one (including me) will agree with everything he proposes, this is an interesting book with some original forward thinking – something we need more of as we face a very changed future.
  5. Michael Hallsworth and Elspeth Kirkman – Behavioral Insights (2020). This is a good overview of the application of behavior research to mostly public policy, especially about the UK.
  6. Paul Begala – You’re fired: the perfect guide to beating Donald Trump (2020). Smart and realistic proposals for the campaign to oppose Trump with many very funny lines.
  7. Jane Kleeb – Harvest the Vote: How Democrats Can Win Again in Rural America (2020). Along with Begala, explains her own success in rural America and more generally what needs to be done by Democrats to regain their old reputation as the party of the majority of people.
  8. Mark Lilla – The Once and Future Liberal: After Identity Politics (2017). Short review of how the Democratic party became dominated by identity politics and, for that reason, provides a bit of background for the previous too books.

Have a happy holiday season and a great, much better, year in 2021!

© 2020 Norman Jacknis, All Rights Reserved

You To Me, You To Them - More About Network Effects

Not that we have to be reminded, but COVID has certainly reminded us of the fact that we are all connected, in varying degrees, and have an impact on each other.  This reminder from a pandemic shouldn’t be a surprise since some of the earliest and best work on real network effects between people has been done by public health experts.

The now classic 2009 book, Connected: The Surprising Power of Our Social Networks and How They Shape Our Lives, by Nicholas Christakis and James Fowler showed the ways that our networks with other people affect, among other things, our emotions, political views, wealth, and health (even body weight).  Given that one of the most important origins of the study of human networks was in public health, it won’t be surprising that Christakis, who specialized in public health, was particularly interested in the long-running Framingham study of health.

For the rest of us, who are not in public health, it would seem that viral pictures and memes on the net form our understanding of network effects.  But there is much more to these connections than simply passing images and memes to one another – even much more than passing diseases to each other.

There have been, at least, three relatively recent books that help describe in more useful and original detail the impact of each of us on each other.  The ideas in these books apply not just to health, but to the economy, business and career success as well.

Robert H. Frank is one of the most creative and insightful economists around.  His book this year, “Under the Influence: Putting Peer Pressure to Work”, is a review of behavioral economics, with an emphasis on network effects.  That includes how it is not only the absolute value of goods and wealth that motivate economic behavior, but our ownership of goods relative to others.  Rather than maximizing wealth, per se, many people want to maximize their relative position.  Thus, he points out that having another billion dollars is not so important to the richest man, as long as he is richer than other men.  (This has important implications for tax policy and other public policies, which he discusses the book.)

Matthew O. Jackson’s 2019 book “The Human Network: How Your Social Position Determines Your Power, Beliefs, and Behaviors” extends the work of Christakis with explanations of network measures and phenomena in the economy.  Those economic phenomena include two very relevant to our times – economic inequality and economic crises (or, to put it more simply, economic bubbles that burst).  He shows how the well-known tendency of people to connect with others who are similar to themselves can generate inequality.

In an elaboration of the old adage – “it’s not what you know, but who you know” – Jackson also describes the various ways that our position in our networks influence our behavior and outcomes for us in those networks.

Of course, you may know some people very well, like family, and others not so well.  As Duncan Watts showed in his 2004 book, “Six Degrees: The Science of a Connected Age”, the people you don’t know so well – those with whom you have weak ties – can connect you to almost anyone else on the globe in just a few steps.

One popular application of that idea is that it is weak ties that are the key to success in finding out about job openings or getting major initiatives accomplished in a large organization.  We’ve all heard about the importance of “networking” in career success.  But, like all such popular ideas, the importance of weak ties has been applied to too many situations, some of which are inappropriate.

That is the point of Damon Centola’s 2018 book, “How Behavior Spreads: The Science of Complex Contagions”.  He provides a more nuanced view of the best time to use weak or strong ties.  If the goal is to quickly pass information – such as about a job opening or a cute meme – then weak ties will indeed do the best job.  However, if the goal is to change the behavior of people, something not as casual as passing along a joke, then having someone lead the change in a networks of strong ties are more effective.

This post can only provide a summary of three of the most interesting authors.  It is worth reading each of these books as well as other books and articles that have contributed to our understanding of this important, but complex, subject of human interactions.

Expect more new knowledge in the future.  After all, there is now a lot of and a growing amount of big data about human interactions that can provide a gold mine to be explored with network analytics, but more generally machine learning and AI.

A final thought … You would expect that the importance of these phenomena of social influence would be built into many models of individual human behavior and then aggregated, network style, into larger models to understand macro phenomena and trends.  Curiously, such network-informed models are few and far between – but that’s a topic for a future blog post.

© 2020 Norman Jacknis, All Rights Reserved