Maurer, Stephen M., Digital Publishing: Three Futures (and How to Get There) (December 3, 2017). Available at SSRN: https://ssrn.com/abstract=3081940

“The usual assumption that copyright rewards creativity is a fiction. In practice, most authors earn very little compared to their publishers. This article asks what services, if any, publishers supply to justify these payments. We argue that the only reasonable candidate is search, i.e. finding worthwhile titles among the million or so books written each year. For most of the 20th Century, there was just one search technology: Human judgment. This led to a complex ecosystem of editors, bookstore owners, reviewers and other middlemen. The difference in the 21st Century is the emergence of a second technology – “Big Data” – that could make traditional methods obsolete. But in that case what new institutions will implement it? Depending on how Big Data evolves, we can anticipate three futures. In the first, the technology never advances much beyond its existing capabilities so that current institutions continue in something like their present form. We argue that is already an improvement over mid-20th Century publishing. At the same time, the advent of e-readers allows new forms of price discrimination that could significantly improve economic efficiency. Judges should reform the Second Circuit’s Apple decision to make this happen. More powerful “Big Data” technologies will force deeper changes. These will almost certainly start with massive vertical integration. Our second future analyzes the case where today’s dominant on-line retailers continue expanding up- and downstream. Despite obvious concerns, we argue that clearing away costly middlemen will almost certainly improve social welfare on net. We also consider an alternate future in which today’s dominant publishers preempt retailers by creating an open search platform. Taking search outside traditional proprietary models can radically improve consumer welfare, but only if legislators are prepared to make correspondingly large adjustments to copyright law. Finally, we ask which of our three futures is most likely. We argue that Big Data algorithms are inherently voracious, so that the future belongs to whichever institutions collect the biggest and most useful datasets. We identify the conditions under which proprietary solutions can outperform open source and vice versa. The article concludes by asking what judges and policymakers should do to create a level playing field so that the most efficient institutions really do emerge if and when technology makes them possible.