The Blurb On The Back:
Capitalism is dying. Profits soar while inequality rises and innovation stalls. Something has to give.
For the past century, the story of capitalism has been the story of a market dominated by money and firms. We use prices to judge goods, and what we’re willing to pay signals how useful a good is to us. Firms coordinate massive efforts, such as mass-producing cars, by controlling the flow of information and centralising decision making, while providing stable employment. But the data we generate about ourselves and the data manufacturers generate about their products enable algorithms to connect buyers and sellers much more efficiently than markets based on price ever could. These same forces make the rigid control of information unnecessary, enabling ever-smaller groups of people to work together effectively. Large, centralised firms could wither away to nothing more than a person and their computer: more AirBnB than Holiday Inn.
This fusion of big data and artificial intelligence will lead a new kind of capitalism: data capitalism.
This could mean a more sustainable, egalitarian economy, but the end of the firm – including the end of stable employment – carries great risks as well. Viktor Mayer-Schönberger, the bestselling co-author of Big Data and Thomas Ramge, writer for The Economist, show how modern technological change is killing capitalism as we know it, and what comes next.
Thanks to the Amazon Vine Programme for the review copy of this book.
You can order REINVENTING CAPITALISM IN THE AGE OF BIG DATA by Viktor Mayer-Schönberger and Thomas Ramge from Amazon UK, Waterstone’s or Bookshop.org UK. I earn commission on any purchases made through these links.
The Review (Cut For Spoilers):
Viktor Mayer-Schönberger is Professor of Internet Governance and Regulation at Oxford University. Thomas Ramge is technology correspondence for Brand eins. This is a widely general look at how the use of data could replace existing price or money based capitalism and in turn change the meaning of the firm as a means of carrying out business that refuses to examine how data is generated and AI created and therefore is of theoretical use only.
The central premise of the book is that there is going to be a fundamental reconfiguration and reinvention of the capitalist economy to address the fact that markets will or need to move away from price determining transactions to data determining them, thus allowing for a greater match up between buyer and seller needs. This is quite an assumption and one that does all the heavy lifting in the book.
However, while there is no denying that better capture and use of data by corporate parties is going on and the authors demonstrate how this has assisted various companies name-checked throughout the book, the authors make zero attempt to interrogate how data is captured and how data is used. Also, while they push the view that data transfer will replace money as the means of determining market transactions, they can’t avoid the fact that money is still the grease that keeps the economy going. They do look at some of the fall out of this (e.g. an acknowledgement that it may reduce the number of jobs, potentially necessitate a form of universal basic income) but the fact remains that money will remain important and the authors’ position seems to be that individuals will suffer the consequences while corporations will gain even more data and potentially be encouraged to share this more, meaning that individual needs are better met. Personally, I don’t see how that is a reinvention of capitalism so much as an evolution.
What also bothered me about the book is that there is a big assumption that AI will assist in the collection and processing of data to make markets more efficient. However this assumes that data and AI is in some way natural and is not shaped by the desires and prejudices of the controlling entity. The authors seem to assume that this will all be neutral or work to benefit the market, but there’s no reason to believe that. For example, they also assume that Amazon’s algorithms and data collection is there to benefit customers and give them better matches – although this may have been true once, certainly at the time this book was published in 2018 and as has been the case since – the business model has shifted to selling promotional space to sellers so that they appear high up the search lists regardless of how good or relevant the product is. The same is true of Google, which puts paid promotional sites and adverts above search results. And again, the point to be made here is that these big companies do so because they value the money they get from this activity more than they do the data collection and matching.
The authors seem to accept that companies use AI/data to reduce costs – e.g. they use the example of Fukoku Insurance in Japan, which replaced claims assessors with AI – but there is no analysis on whether this has made for a better experience for customers, e.g. by looking at how many customers get the full value of their claim compared with before. That’s a shame because the big argument of this book is improvements in transactions so it would be nice to see some examples of how this move to data is actually benefitting customers rather than just a description of how it is intended to work.
There are some interesting ideas in the book. For example, the suggestion of a data tax as a way of fostering innovation is an interesting one although I’m not sure how practical it would be in reality because again, it is not clear how government would be able to use that data and also there would need to be so many safeguards to ensure that forced data sharing with smaller companies is of benefit that it would be difficult to implement in practice.
All in all, I came away from the book feeling like it had such broad brush ideas that it’s the equivalent of writing about flying cars in the 1950s. Ultimately, I just didn’t see how there is enough here to be of practical analytical benefit going forward and I certainly wasn’t convinced that we’re going to see any changes in capitalism or corporate structures any time soon.