Information: The New Language of Science
Source: https://archive.org/details/informationnewla0000vonb ↗
Von Baeyer, a physicist at the College of William and Mary, writes a broad popular history of information as a scientific concept — from Boltzmann's statistical mechanics and the entropy connection, through Shannon's mathematical theory, to quantum information and the holographic principle.
The book's strength is its range: it treats thermodynamics, genetics, neuroscience, and quantum computing as chapters in a single story about how information became the unifying concept of modern science.
Von Baeyer is careful to distinguish between the colloquial sense of "information" and its technical meanings in different fields, a distinction many popular accounts blur.
The writing is accessible without sacrificing rigour, making it a reliable introduction for readers coming to information theory from any direction.
It occupies a useful middle ground between Shannon's original papers and the more specialised treatments that followed.
Central argument
Von Baeyer argues that information is not merely a metaphor borrowed across disciplines but a genuine unifying scientific concept — one that connects Boltzmann's entropy, Shannon's communication theory, genetics, and quantum mechanics into a single coherent framework. The central thesis is that 'information' underwent a transformation from a loose colloquial term into a precise technical quantity, and that this shift has reorganised how science understands physical reality itself, up to and including the holographic principle's claim that the universe's content can be described as information encoded on a boundary surface. The book traces this arc as intellectual history, showing how each field independently converged on information as its foundational currency.
Critique
Because the book was published in 2003, its treatment of quantum information and complexity stops short of developments — in quantum error correction, algorithmic information theory, and the black hole information paradox — that have since sharpened or complicated the very unifications it celebrates. More substantively, von Baeyer's ambition to tell a single story across thermodynamics, genetics, neuroscience, and quantum computing risks papering over the fact that 'information' is not technically the same quantity in each of these domains; the entropy of a thermodynamic system and the Shannon entropy of a message share mathematical form but not physical interpretation, and a popular history may not be the right format to hold that tension honestly.
Why it matters for product
The book's core move — distinguishing between colloquial and technical meanings of a concept that everyone thinks they already understand — is directly applicable to how product leaders handle metrics and data culture: teams routinely conflate 'having data' with 'having information,' and von Baeyer's framework provides intellectual grounding for demanding precision about what a given signal actually measures and what decisions it can legitimately inform. More concretely, the idea that information is a physical constraint, not an abstract resource, reframes prioritisation: just as Shannon showed that channel capacity is a hard limit, product organisations have finite cognitive and coordination bandwidth, and treating that as an engineering problem rather than a motivation problem changes how you design team structures and discovery processes.