Hitting the Accelerator

Scott McLemee reviews The Acceleration of Cultural Change: From Ancestors to Algorithms, in which social networks, big data, memes and the like are presented as extreme cases of the creative and disruptive potentials or our tool-oriented species.

November 15, 2017
 
 

In the 2010 film The Social Network, Sean Parker, the first president of Facebook, invokes the spirit of manifest destiny, 21st-century style: “We lived on farms, then we lived in cities, and now we are going to live on the internet!”

To be clear, this piece of dialogue comes from an actor playing Sean Parker, speaking from an Oscar-winning screenplay by Aaron Sorkin -- who probably came up with the line, as it does not appear in Ben Mezrich’s book The Accidental Billionaires (the film’s source material). In any case, it sounds like the quintessential visionary hype of a Silicon Valley entrepreneur -- and in a recent interview, the real-life Parker expressed misgivings about ever indulging in social-media boosterism.

"The thought process that went into building these applications," he said, "was all about: 'How do we consume as much of your time and conscious attention as possible?'" The solution was to create “a social-validation feedback loop” by “exploiting a vulnerability in human psychology” at the neurochemical level: “a little dopamine hit every once in a while” from seeing that “someone liked or commented on a photo or a post or whatever.” When a network “grows to a billion or two billion people … it literally changes [people’s] relationship with society, with each other … God only knows what it's doing to our children's brains."

Well, it’s a little late now! one thinks. You might’ve thought of that before you went and destroyed human civilization. The image of hardy pioneers forging a new life on the frontier does not serve a plausible analogy for the future to be extrapolated from his remarks. The line at a methadone clinic -- narrowly focused but comfortably numb -- might be a better fit.

When the interview with Parker made the news last week, I was in the middle of reading The Acceleration of Cultural Change: From Ancestors to Algorithms by R. Alexander Bentley and Michael J. O’Brien, published by MIT Press. The authors take a long view of cultural change in which the more recent developments -- social networks, memes, big data -- come into perspective as extreme cases of the creative and disruptive potentials of our tool-oriented species. (Some of our primate cousins are able to use tools, but we are uniquely dedicated to doing so, as well as dependent on that ability.)

Bentley is a professor of anthropology at the University of Tennessee and O’Brien a professor of history at Texas A&M University, San Antonio. In collaboration, they prove fairly insouciant about disciplinary boundaries -- and willing to go wherever the muse of popularization leads them, including a couple of pages spent on Gilligan’s Island.

Trimming back the digressions and abstracting from the examples, we find an argument along roughly the following lines.

An important study in the early 1990s found a strong relationship between the size of the primate brains (in particular, of the neocortex) and the number of members in the social groups typical of their species. On the basis of that correlation, and using the fossil remains of early hominids, it was possible to estimate that our distant ancestors tended to live in bands of about 150 members -- a figure called “Dunbar’s number,” after its discoverer, who identified it “as being the typical limit of real -- defined as meaningful -- social relationships that a person will have.” Decades later, studies have found that the pool of friends or followers on social media with which an individual has significant or sustained interactions tends to come in at Dunbar’s number, more or less.

Putting that finding to the side for a moment, it’s obvious that our ancestors eventually began to form social groups many orders of magnitude greater in scale than the original Dunbar number-sized cohorts. The latter had developed weapons for hunting that, the archaeological evidence suggests, remained unchanged for hundreds of thousands of years -- a pace that, the authors note, was literally slower than the movement of glaciers.

“If the tools had been constrained by brainpower,” they write, “we would expect changes in parallel with brain size, yet we don’t see them. Alternatively, maybe hominids needed larger groups for technological change to occur. Yet this applies to more complex technologies, where it pays to learn from the expert in the group … In the case of Pleistocene stone tools, probably every individual could knap a hand ax without necessarily learning from an expert -- if there even was one.”

The point here is not to choose a single cause that would explain the quantum leap but to identify the factors (increasing brainpower, group size, technical innovation, training) that reinforced each other as early human society began growing beyond the Dunbar limit. Culture began not just to change but also to evolve: “Evolution means there are different variants transmitted between generations, over which these variants are sorted as some are transmitted more frequently than others.”

For most of human history, the winnowing process tended to favor forms of knowledge and technology that were specific to a place, region or group -- with irrelevant details or inessential changes stripped away and the important elements rendered compact, formulaic and memorable. Innovations can be transmitted, as well, but only after proving themselves and finding a place in a deep order.

“Without the kind of vetting that has long typified cultural transmission,” the authors say, “culture is bound to accumulate a lot of junk.” While oral transmission “prunes away superfluous details, rendering it more learnable and relevant,” nothing of the sort happens with, say, a viral video: it “gets copied identically millions of times without being streamlined by the transmission process and actually accumulates more junk in the form of comments and metadata.”

Furthermore, the act of looking something up online generates data that search engines use to calculate the value or pertinence of information for others who might do a similar search: “Within a shallow time depth, algorithms guide human followers like schools of herring, using popularity as a beacon.”

At the same time, the size of communities of meaningful contact among individuals hovers somewhere around Dunbar’s number. The authors are not alarmists or pessimists; they see the situation as a challenge, not a disaster. “To anticipate the future of cultural evolution,” they write, “think about populations, not individuals, and certainly not yourself. How will variation, transmission and selection be affected? … What wave should we be surfing now, and how will we find the next wave after that?” In any event, don’t ask Alexa.

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