We live mythically, even the most rational among us. In the middle of a bromidic Q&A session on Facebook last month, Mark Zuckerberg fielded a question from the cosmologist Stephen Hawking:
I would like to know a unified theory of gravity and the other forces. Which of the big questions in science would you like to know the answer to and why?
Zuckerberg replied that he was “most interested in questions about people,” and he gave some examples of the questions about people that he found most interesting. “What will enable us to live forever?” was one. “How can we empower humans to learn a million times more?” was another.
He then divulged something interesting, if not unexpected, about his perception of the social world:
I’m also curious about whether there is a fundamental mathematical law underlying human social relationships that governs the balance of who and what we all care about. I bet there is.
Call it the Unified Theory of Love.
Zuckerberg’s answer underscores, yet again, what an odd choice we made when we picked a person to oversee the world’s predominant social network. We’ve placed our social lives in the hands of a maladroit young man who believes that human relations and affiliations can be reduced to equations.
The fault, dear Brutus, is not in our stars,
But in ourselves, that we are underlings.
What Brutus saw in stars, Zuckerberg sees in data. Both believe that human affairs are governed by fate.
It’s not hard to understand the source of Zuckerberg’s misperception. Human beings, like ants or chickens, share a certain bundle of tendencies, a certain nature, and if you analyze our behavior statistically that nature will evidence itself in mathematical regularities. Zuckerberg is hardly the first to confuse the measurement of a phenomenon with the cause of the phenomenon. If some amount of data reveals a pattern, then, surely, more data will reveal “a fundamental mathematical law.”
Zuckerberg’s belief that social relations are the output of a cosmic computer running a cosmic algorithm is more than just the self-serving fantasy of a man who has made a fortune by seeing people as nodes in a mathematical graph. It’s an expression, however extreme, of a new form of behavioralism that has recently come into vogue, pulled along in the slipstream of the excitement over “big data.”
From the mid-1950s to the mid-1960s, sociological thinking in the United States was dominated by the behavioralist school. Heirs of the earlier positivists, behavioralists believed that social structures and dynamics could only be understood through the rigorous, scientific analysis of hard data. David Easton, a prominent University of Chicago political scientist, laid out the tenets of the movement in his 1962 article “The Current Meaning of ‘Behavioralism’ in Political Science”:
There are discoverable uniformities in political behavior. These can be expressed in generalizations or theories with explanatory and predictive value. … The validity of such generalizations must be testable in principle, by reference to relevant behavior. … Precision in recording of data and the statement of findings requires measurement and quantification.
The rise of behavioralism reflected a frustration with the perceived subjectivity of traditional modes of sociological and political inquiry, particularly historical analysis and philosophical speculation. History and philosophy, behavioralists believed, led only to ideological bickering, not to unbiased knowledge or reliable solutions to problems. But behavioralism also had technological origins. It was spurred by the post-war arrival of digital computers, machines that promised to open new horizons in the collection and analysis of data on human behavior. Objectivity would replace subjectivity. Technology would replace ideology.
Today’s neobehavioralism has also been inspired by advances in computer technology, particularly the establishment of vast databases of information on people’s behavior and the development of automated statistical techniques to parse the information. The MIT data scientist Alex Pentland, in his revealingly titled 2014 book Social Physics, offered something of a manifesto for the new behavioralism, using terms that, consciously or not, echoed what was heard in the early 60s:
We need to move beyond merely describing social structure to building a causal theory of social structure. Progress in developing this represents steps toward what [neuroscientist] David Marr called a computational theory of behavior: a mathematical explanation of why society reacts as it does and how these reactions may (or may not) solve human problems. … Such a theory could tie together mechanisms of social interactions with our newly acquired massive amounts of behavior data in order to engineer better social systems.
As with their predecessors, today’s neobehavioralists also view the scientific analysis of “big data” as a means of escaping subjective modes of sociological inquiry and the ideological baggage those modes often carry. “The importance of a science of social physics,” Pentland suggested, goes beyond “its utility in providing accurate, useful mathematical predictions.” It promises to provide “a language that is better than the old vocabulary of markets and classes, capital and production”:
Words such as “markets,” “political classes,” and “social movements” shape our thinking about the world. They are useful, of course, but they also represent overly simplistic thinking; they therefore limit our ability to think clearly and effectively. [Big data offers] a new set of concepts with which I believe we can more accurately discuss our world and plan the future.
Zuckerberg will lose his bet, and Pentland and the other neobehavioralists will not discover “a causal theory of social structure” that can be expressed in the pristine language of mathematics. Neobehavioralism will, like behavioralism before it, fall short of its lofty goals, even if it does provide valuable insights into social dynamics. Despite, or because of, their subjective messiness, history and philosophy will continue to play central roles in the exploration of what makes all of us tick. The end of ideology is not nigh.
But there is something that sets neobehavioralism apart from behavioralism. The collection of behavioral data today generates great commercial value along with its value in social research, and there’s an inevitable tension between the data’s scientific and commercial exploitation. That tension will shadow any attempt to, as Pentland put it, “engineer better social systems.” Better for whom, and by what measure? Even if no fundamental mathematical law of social relationships is in the offing, the ability to closely monitor and influence those relationships will continue to provide rich profit potential. One suspects that Zuckerberg’s dream of a Unified Theory of Love is inspired less by cupid than by cupidity.
Image: Detail of Sodoma’s “Cupid in the Landscape.”