Also known as the "Second Digital Disruption."
Thanks first to Eugene for inviting us to blog about our new article, The Second Digital Disruption: Data, Algorithms & Authorship in the 21st Century.
Our article is about the impact of the most significant change in the consumption of entertainment in the past two decades: the advent of streaming. Today, we all are familiar with streaming services for music (Spotify, Tidal, Apple) and for video (YouTube, Netflix, Hulu, Amazon Prime, Pornhub).
Streaming has obviously had a big economic impact—in the music industry, for example, the major streaming services are now bigger and richer than the major record companies.
Less obvious, at least so far, has been streaming's impact on creativity. But we think this is going to be the big story going forward. Think about this—Netflix is not only the biggest video streaming service, it has emerged in the last 5 years as a major Hollywood studio. We take that to be an important signal about the future. Steaming services are going to be content producers.
To see why, we need only look at the recent litigation over the Time Warner-ATT merger. In their brief before the District Court for the DC Circuit, Time Warner and ATT argued:
Time Warner has no access to meaningful data about its customers and their needs, interests, and preferences. In most cases, Time Warner does not even know its viewers' names. This data gap impedes its ability to compete with Google, Facebook, and other digital companies.… Whereas digital companies have the data and the technology to deliver advertisements that are both specifically addressed (shown) to a particular viewer and tailored to that viewer's specific needs and interests, Time Warner cannot target its television advertising in those ways, creating an increasing competitive disadvantage for the company. The data gap also gives online video programmers a competitive advantage in the production and aggregation of content based on extensive data about the content preferences of their viewers.
Digital distribution, in short, is not merely a means of distributing content; it is fundamentally a communications channel for data about content preferences and consumption. And Time Warner was worried about being left out in the cold, unable to collect the consumer data that in the future will give competitive advantage in the creation of new content.
This is the key feature of what we've referred to as the "second digital disruption"—enabled by massive amounts of data about consumer habits and preferences, distributors, who are now also creators, can increasingly tailor content to those preferences.
This is especially true for large firms, whose dominant role in content distribution gives them access to data about consumer preferences and behavior in a scale and scope that smaller rivals are hard-pressed to replicate.
The allure of what we call "data-driven authorship" is simple but powerful: content producers collect and analyze massive troves of consumer data to lower the risk of failure—i.e., the risk that a particular piece of creative content will be a bomb and not a blockbuster.
As lawyers, we want to understand these changes and how they are reshaping creative industries. We focus also on how the advent of streaming and data-driven authorship has changed or will change fundamental features of intellectual property law and theory.
For years intellectual property theorists have described shifts away from the traditional authorial role, but usually in terms of the increasing centrality of corporate and shared authorship. The advent of digital distribution, and the introduction of data mining, together add a critical new dimension to this process.
To be sure, reacting to or anticipating the market is not new. But the ability to quickly analyze millions or even billions of data points and to rapidly use what is learned to shape new creativity—especially in an age where AI and machine learning techniques are rapidly advancing—raises new questions about the meaning of "authorship", as well as about the strength of the moral justification for copyright.
These developments also raise central questions about copyright's dominant consequentialist justification. In particular, the advent of data-driven authorship forces us to reassess some of the received wisdom regarding the centrality of copyright to creative production, and whether copyright's traditional justification as a spur to creativity has much traction in a world where the ability to gather and analyze massive amounts of data is a central criterion, and perhaps, in the future, the central criterion, of creative success.
This observation has positive analytic implications: it can, for example, help explain why some industries remains creative in the face of extensive copying. It also has normative ones: the rationale for strong intellectual property protection in film, music, and other content industries is diminished the more the risk of failure is reduced.
We look forward to digging into these issues on the blog this week. Tomorrow, we'll write a bit more about Netflix and how that firm has used data-driven authorship to break into the elite circle of Hollywood studios.