Life Itself, by Robert Rosen, was a book I picked up by chance based upon the recommendation of somebody I follow on Twitter who is involved with Complex Systems, a topic that I find interesting. Now, since I have finished reading it, I’ve totally forgotten why it was recommended or what context it was recommended within, but nevertheless, I finished it and enjoyed it. Oh right, the Complex Systems part!
It’s was definitely a stretch for me to read. I didn’t expect quite as much math as there was in the book, despite the fact that nearly all of it you can work out fairly simply as you go along. The hardest part in the beginning was following the notation, since I have not done “math” for a long time, and never really knew all of my Greek alphabet. But by the end of the book I knew a Sigma and a Phi better than when I started.
I should have been less surprised than I was at the math to be honest. The math turns out to be necessary, or at least the notation and formality with which Rosen uses to make his case. While the book is philosophical in nature, it is also precise in it’s goal – providing a scientific answer to what “life” is. The mathematical notation and models that Rosen builds are key to his answer.
The book was really something I enjoyed reading even though it was a hard read. While I may not have gotten the math as well as possible, I feel like I understood 90% of it or so. There is one chapter on “state” and recursivity, which I thought was trickier than the others, but mostly because of the derivative analogies. It’s been too long since I have thought about a derivative, and differential equations are beyond what I ever got to.
However, while the rest of the math in the book took some serious concentration for me to get initially, by the end I was working through the notation much more easily than in the early chapters. I didn’t really expect ‘Category Theory’ to play a role in this book, but Rosen explains it and the notation doesn’t really get too complicated.
While I would butcher the position of Rosen’s “Life Itself,” if I was to try to explain it technically, I totally got behind his ultimate take, which is that an organism is not equal to a machine by itself. In fact most of the book is building up in a formal manner to this compelling conclusion. Rosen spends a long time showing how machines and mechanisms are modeled in a formal manner, and why this is fundamentally incompatible with modeling an organism.
He puts it as follows in the end, in perhaps his most concise take:
A material system is an organism, if and only if, it is closed to efficient causation.
Throughout the book we are introduced to Gödel’s Theory, and later, to Alan Turing’s work as Rosen builds up his critique of where the metaphors of machine and mechanism fail to describe life in an adequate sense. In the end he argues that an organism cannot be described syntactically in the same way as a machine. Helping understand this of course is the book.
While I am not a scientist, the fact that life and organism as machine is the prevailing metaphor used to describe it by the sciences is something that is not lost on me. It was heartening to find Rosen’s final take and his position that the soma, or what is alive, is more than can be defined by the syntax of a machine. His book explains this position wonderfully.
In addition to critiquing the contemporary “life as machine” metaphor prevalant within science, Rosen offers a potential new idea or model for biology in describing and studying life, that of, “Relational Biology.” I won’t attempt to go into it here, but the book does, and it is founded on how the mechanistic model cannot successfully describe an organism through reduction.
Also fascinating is his comparison of the so-called “hard” and “soft” sciences and the reasoning behind this. Deriving this difference and drawing a parallel to Gödel’s Theorem made for interesting reading early on in the book, and set the stage for the rest of the text.
Overall if you are up for a challenging read this is a very good book. Rosen is a great writer, and while the math is challenging, and required to understand the book, if you’re up to it, you may come away with an inspiring read concerning life, and how it’s more than the machine metaphor commonly given can offer.
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© Copyright 2021, Tyler Rhodes