Complex Intelligence
A friend who works with Artificial Intelligence told me: “It is possible that there are highly context dependent and complex things about humans, but in terms of intelligence it does not look that way. With the brain there is nothing that isn’t computable. The brain is a computer like any other.” I begged to differ and claimed, a bit flippantly, that our brains do much more than solve differential equations.
Our present digital culture is oriented towards the objective and the quantifiable more than the subjective and the qualitative. The software we work with reflects the analytical minds of the people who built it, such as my friend. The downside of all this is a possible failure to understand and capture the paradoxical elements of life.
Traditional science was a project that aimed to get closer and closer to certainty. The new sciences of complexity are making it clear that this is not possible. Complexity sciences present paradoxes as being normal in everyday life. The dominant scientific way of thinking tries to eliminate paradox. An encounter with paradox, such as seeing the same thing differently from different points of view, has been understood as a sign of not thinking properly and thus has led to attempts to resolve or eliminate the paradox. What the new sciences are suggesting is that the dynamic patterns of knowing are inherently paradoxical and context-dependent.
A new language is appearing as scientists attempt to describe the complex dynamics in which phenomena are no longer perceived as certain. It is slowly accepted that things can be both predictable and unpredictable, knowable and unknowable at the same time. To force this complexity into a reduced number of cognitive patterns would be enormously repressive.
The question of what technology dealing with Artificial Intelligence is doing to our cognitive patterns has been the subject of strong opinions but few robust studies. Some scholars claim that the brain has always been adapting to new tools. New neural patterns emerged when people began speaking, reading or writing. Digital tools and software code are just the next step, they say. Man is seen as his or her own maker — a maker of life through new tools and new practices enabled by those new tools.
The real question here is whether modern society is in effect de-skilling people in the conduct of the practices of everyday life because of our tools. We have more machines than our ancestors, but less idea of how to use them well. We have more connections with people, but less understanding of people who are not like us. Our social tools have in a way helped to re-create tribalism: solidarity with others like yourself (in your own echo chambers) and aggression against those who differ. Tribalism involves thinking you know what other people are like without really knowing them. Modern media give us fast and loose data points but typically not much more before it is time to move on to the next topic. Lacking time consuming IRL-experiences, it is easy to fall back on fantasies and stereotypes.
Digital tools have increasingly become our senses, our eyes and ears. Digitalization has given us amazing access to the world. But there are things it does not capture. The more people have superficial information about the world, the less they actually put themselves in the shoes of others. The psychological problem is that when we don’t know the history and the context behind something, we project those ourselves.
When the context is stripped away, we add it back.
We fill in the gaps in information when they are not there. It is so easy for us to comment very negatively on (Twitter) posts without any understanding of the context of the discussion. We don’t know much about the refugee crises, but we think we know, as we project our beliefs, fears and worries onto what is going on.
But the new social technologies can also be used to solve these problems.
The concept of social skills often means that people are good at telling stories or accomplished at party talk, but there are social capabilities of a very serious sort. The social capacity of cooperation is more the foundation of human intelligence than differential equations are.
The next digital tools dealing with intelligence need to be more “dialogic”. The concept of dialogue has a very precise meaning. It is a discussion which does not resolve itself by finding common ground. Though no shared agreements are reached, people often become more aware of their own views and learn through expanding their understanding of one another and the different contexts of different people. We become more intelligent if the paradoxes are kept alive.
Cultural homogenization is a theme of our time. It is apparent in fashion, food, music, and many services with a unified user experience. Everything is made to be basically the same everywhere. According to some psychologists, the desire for this sameness arises from anxiety about differences. This is one of the reasons why Gregory Bateson argued that the history of our time can be perceived as the history of malfunctioning relationships. More homogenization leads to more anxiety (when experiencing differences) which leads to more homogenization and the “differences that make a difference”, as Bateson put it, are lost.
Unless you genuinely value the perspectives of others, and not just the ones that conform to your own, you are not going to understand them. Truly intelligent thinking is not just a means to an end: it has to be rooted in what we see as ends in themselves, the values by which we live.
More on mono-cultures.
