Simulated News and Techno-Tribalism

We have reached a point in the early 21st Century at which media cannot be assumed to directly represent reality.  This is both true in the general and older sense that we may distrust  any narrative, but more importantly it is also now literally true, in a  new sense. We now live in an age in which AI and CGI technologies allow  images, video, audio, and even social network activity patterns to be  rapidly fabricated to a high degree of realism, by anyone wishing to  distort our perception and understanding of things. Such simulation technologies  are only going to become more advanced and integrated into our societal  institutions, so we must think hard (and fast) about how best to  operate in this increasingly strange new world. 

Unfortunately, we have already seen the emergence of negative  reactions to the new technological possibilities and their social  effects. There has been a predictable collapse of trust in news media,  further complicated by state-sponsored disinformation campaigns, and the  co-opting of terms like “fake news” (as a term of criticism) by those  who themselves propagate disinformation. As a kind of secondary  response, we are also seeing a return to tribalism, whereby people trust  information not on the basis of any evidence of its veracity, but on  the older (and less rational) model of ancient tribal societies, which  is to say based on whether those you identify with have chosen to accept  the information or not. Before the age of science and reason began,  “truth” was largely a social function, and now in our hyper-modern age  that seems to be the case again. 

Some may wonder how humanity could have survived and evolved as an  irrational species, often eschewing evidence in favour of social  utility. The simple answer is that social cohesion has survival value,  meaning that individuals tend to survive crises better as part of a  group. By optimizing the human tendency to rely on community-groups in  times of uncertainty, evolution has therefore baked a kind of “default  rationality” into human behaviour, even if that behaviour involves  abandoning explicit, short-term rationality for the shelter of the  tribe. After all, evolution is a statistical phenomenon which “cares”  about entire species rather than individuals, and which certainly has no  concern for explicit logic, cultural values, or anything else we humans  consider important. In short, evolution has “hardwired” us to trust  groups over explicit logic, on the basis that – regardless of the nature  of any given crisis – a group is more likely to survive it than is a  lone individual. 

That simple truth can be a hard pill to swallow for some  “rationalists”. For a long time the field of economics was dominated by  an idealised model of human decision making, in which humans are  expected to always react rationally and optimally, according to  objective self-interest. As empirical evidence gathered by cognitive  psychologists increasingly showed that humans simply don’t work that way,  scientifically-minded economists began to develop the fields of  behavioural and neuro-economics, taking the realities of human cognition  and behaviour into account. I worked in a related field myself (the  psychology of Judgment and Decision Making), and at one conference I  heard an opinion expressed which may well hold the key to negotiating  this new era of technological uncertainty. 

At that conference I attended a meeting of a society which had  recently opened their doors after holding closed (invitation only)  meetings for over forty years. Older luminaries of this group were  complaining that despite decades of ground-breaking research into human  biases and irrationalities, no-one was taking their advice on how to  improve judgment, making it more rational, optimal, and evidence-based.  An engineer visiting the group for the first time then offered an  opinion: Don’t try to explicitly convince people to change how they make  judgments and decisions, because it won’t work. We humans may wish to  change, but evolution has designed us to do certain things in certain  ways, and decision making is one of those things. Instead, the engineer  suggested, we should develop technologies which embody optimal  techniques, and then encourage humans to become dependent upon those  technologies. 

Such a solution perfectly fits our age of Big-Data-driven Artificial  Intelligence. Machines can make more intelligent decisions than us, on  our behalf, according to our own designs and rational intent. The trick is to create interfaces for those systems which encourage human trust,  which in turn means encouraging the sense of tribal loyalty which  evolution has instilled in us. In other words, in an age of big data and  fake news, humans can either retreat into the tribalism of trusting  ill-informed humans, or evolve toward a “higher tribalism” of trusting  Artificial Intelligences. 

 Written for Metric Media by Mathew Twyman
Co-published on Metric Media's official website  

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