Flip towards the later pages, you will find the acknowledgements section, where the authors thank various people for helping with the book. Here the authors begin by saying that they have been guided by an advice given by (a certain) Lewis Branscomb: Don’t tell me what I already know. They add that they hope that “the overall narrative we offer” is new to most, even if not all, readers and that it will inspire us to look differently at markets and money, firms and finance and digitisation and data.

However, when the reader turns the last page, he is more likely to wonder if the authors have taken Lewis Branscomb’s advice seriously. The central theme of the book is that we are living in times of big data, and if human “cognitive limitations” (the phrase occurs frequently) hinders us from making full use of the ocean of data, don’t worry, there is ‘machine learning’ to help us with it.

The authors, (one of whom, Viktor Mayer-Schonberger, has another ‘million copy best seller’ called Big Data, under his belt,) simply deify data. They seem to see it as a great leveller, empowering the commonest market participant as much as it does the rich and cognoscenti, and since machines know us better than we ourselves do, they can make better choices for us than we ourselves do.

For as far back as we can remember, capital as a factor of production has always meant money. Finance capitalism yielded two “antagonistic views” — one, (as the authors put it) advocating for a central authority to take over decision making in markets, and the other, defending conventional market with the concept of decentralised information flows.

Over time, a truce of sorts evolved, in the form of market regulations, which according to the authors, was “an acceptance of defeat” (for whom?). The market was tainted, but the alternatives were worse.

From finance to data capitalism

And then came data.

The world is shifting from finance to data-capitalism. The man with data is the king. Data-rich markets will destroy the existing order, money will no longer be in its pre-eminent position, labour markets will be uprooted and millions of jobs endangered, firms thrown out of business, and so on.

After the introduction, the authors move on to ‘Communicative Co-ordination’, starting the chapter with a 50-feet high human pyramid that a certain club in Spain built for records in 2015. Then there are shovelfuls of information about various activities that have been possible only because humans can co-ordinate well with each other — the authors note that Neil Armstrong could not have put his foot on the lunar soil if it were not for the 300,000 people in NASA working to making that happen.

Humans have co-ordinated in the form of ‘markets’ and ‘firm’ and how co-ordination in markets is different from that in ‘firm’ is dealt with in substantial detail. The authors see ‘market’ being in competition with the ‘firm’.

But to find out what is the point of it all, you have to wade through 17 pages to the very last paragraph, where they say that the data age has “introduced an unprecedented counterforce that will push the market forward”.

‘Reinventing Capitalism in the Age of Big Data’ is almost entirely like that. It is full of very interesting anecdotes and mini case studies, but you have to strain yourself hard to see the authors’ point — which is often intuitive.

The very next chapter illustrates this point. It begins with how the fishermen of Kerala earlier used to find it hard to figure out which markets on the coast offered the best price for their catch, and how mobile telephony changed it all. Information is, therefore, important. Up till now, the best instrument of information about a product has been ‘money’.

To underscore how we often overlook the “informational function” of money, the authors make us wonder how difficult it would be to come to an agreement if we were to only barter goods. But money (or ‘price’) has also been used for clever businessmen to obscure information. Then, in the last line of the chapter, the authors come to their point: data is making the market leave behind the “straitjacket of money and price, of constrained information flows and crippled decision-making.”

Banks in trouble

The authors take the readers through ‘capital decline’ where they discuss the problems banks are likely to face. There is rich anecdotal information in the chapter about how start-ups, armed with data, are dis-intermediating banks, organising peer-to-peer lending — connecting borrowers to individual lenders.

As data capitalism replaces finance capitalism, banks are like — here the authors quote venture capitalist Albert Wenger — a Spanish Galleon full of raided gold sinking in a storm. The banks have the capital but lack insight based on information to circumnavigate the perilous weather.

The problem with the book is that the authors labour over the points they try to make. The chapter titled ‘Feedback effects’ demonstrates this. It begins with the anecdote of Air France flight-447, in detail, to show how the aircraft sank into the Atlantic (in 2009) because the computers didn’t learn — broadly, once the pilots ignored the computer’s warning, it judged its input data to be wrong. In the end, the authors pitch for data-sharing which is “so crucial in protecting the decentralised nature of decision-making, so we can preserve not just markets but an open society in general.”

Another instance of lack of clarity is the huge discussion on ‘universal basic income’ in the chapter titled ‘unbundling work’. Obviously, the authors have a reason for putting it there, but their writing style calls upon the reader to figure things out.

And even if the reader obliges, the point is something he already know intuitively: the fusion of big data and artificial intelligence will lead to a new kind of capitalism, called data capitalism.

MEET THE AUTHOR

Viktor Mayer-Schonberger is Professor at the University of Oxford and Thomas Ramge is technology correspondent for business magazine Brand eins and writes for The Economist

 

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