By Gert Jan Hofstede, 2021 04 10
Why sociality matters
System failures: Erratic human behaviour gets the blame
“When a socio-ecological system fails, humans are to blame”. I hear this often. Sometimes the same individual goes on by saying something like “Human behaviour cannot be predicted”. The disheartening inference that follows logically is that it is no use trying to control socio-ecological systems. I disagree.
GAIA: a socio-ecological system
The earth, conceived as GAIA, is a huge socio-ecological system, consisting of innumerable subsystems. We humans are affecting this system like never before in the earth’s history, by our numbers and our voracity. If we accept that we cannot control the system, then our accelerating bandwagon will soon reach a climatic cliff and fall off it.
The urgent task: get a grip on sociality
It is thus urgent that we get a better handle on our collective behaviour on this planet. What are all the social sciences and humanities for, anyway? Over just a few millennia, we have conquered natural hazards; we have multiplied and multiplied; we have self-domesticated; but we have not yet managed to be good stewards for the earth.
It’s not the science…
If we cannot effectively fight climate change and other worldwide challenges, this is not because we have no clue. Climatologists and other scientists know enough for us to take action. We are lame ducks because we are distracted by emotions and feelings, differing across groups. We spend our time bickering and conjuring fiction.
It’s the sociality
Actually, there is pattern to human affairs. Social sciences and humanities did find out a great many useful things. Readers of this blog are probably users of some theories that work for making sense of aspects of human behaviour. What’s lacking is a grand, unifying story that makes evolutionary sense. A story that explains our path through the past will help us in the hard times to come. This is the story, essentially biological, of human sociality.
What is sociality?
We can define sociality as “the way in which we form cooperative societies”. Readers of this blog will be familiar with my ideas on sociality; see e.g. BOSS blog 10 on status-power relational sociology. The differences in the unwritten rules of status, power and group life that exist between peoples are the stuff of culture. We need long childhood to learn our culture, and it settles in us as shared systems of values and norms. A propensity to value our own group, whatever that may be, above all others, is part of our sociality.
Why artificial sociality?
More and more, policies of countries and of world-wide affairs are being supported by models of a “what if?” kind. These models include possible action by humans and their societies. Typically, the non-human side of models is much better catered for than the human side: these models lack artificial sociality. This gives them some blind spots. When things go wrong, human behaviour gets the blame – why were these behaviours not in the models?
How to do artificial sociality?
In the “ivory archipelago” of science, where can we find solid ground for artificial sociality? There are many navigable routes. Let me sketch you my own approach route.
Simulation gaming
In the mid-nineties, the World Wide Web hit our world. It let to ideas about an impending “Global Village” that would obliterate cultural differences across the world. I doubted this. But how to make others see this? I created a simulation game “The Windmills of our Minds” about a multinational enterprise that had to design a communication architecture. It included the concept of scripted “Synthetic Cultures”. The game was a great eye-opener for participants, and led to an article and the book Exploring Culture.
Deep culture vs organizational culture
This game, and many others I created for groups of people since then, gave all their participants two cultures: their own deep culture, and the Synthetic Culture scripts. The many game runs gave me lots of first-hand evidence me that, whatever the task, the real cultural configuration of participants was much more important than the Synthetic Culture scripts in determining what happened. The Synthetic Cultures were acting as a kind of superficial organizational culture. They were important on the surface, but deep culture ruled the process dynamics. You can read aggregate knowledge about these things in another article and the book Why do games work? .
Agent-base modelling
Early in this millennium, one of my PhD students decided to model a game using computational agent-based modelling. This technique, still in its infancy then, works with virtual people known as “agents”. It requires the modeller to give the virtual people behavioural rules. In particular, we gave them culture and let them negotiate. The work let to a series of articles and a PhD. (the last article)
Culture builds on GRASP sociality
My big take-away from that work was that you can only give agents culture for a very narrowly specified task, unless they have an underlying, general purpose sociality. That brought me on the track of work on status-power dynamics in groups; see BOSS blog 10. I was forced to acknowledge that culture, which I found so important, is really no more than the ripples on the ocean of human sociality. I captured my summary of sociality in the acronym GRASP (Groups, Ritual, Affiliation, Status, Power).
The Artificial Sociality Manifesto
In recent years, I found some academic friends who also try to impart broad, general-purpose sociality to agents. Each of us uses slightly different social scientific theories, but with considerable overlap. Together, we wrote the Artificial Sociality Manifesto. It is a long document, with many references that I omitted here.
To-do
We hope that our work will be an inspiration for many, and that artificial sociality will help build better models of policy-relevant systems. These will be models for understanding, not for prediction. The kind of questions such models could tackle are, for instance, “what are the chances that policy X will fail for social reasons?” Of course, decisions remain a political matter; but models with sociality could also investigate political processes.
It will still be a long road, requiring efforts from many people!
P.S. Useful for cross-culturalists: Culture’s Causes
For you cross-culturalists reading this blog, the idea of artificial sociality is valuable. You normally work with real people. You do not need to teach them sociality. But by thinking about what it takes to give sociality to computational agents, you can reflect on the sociality that underlies the cultures of your trainees: Culture’s Causes. This helps in particular to make the step from the group-level insights of culture to the individual-level, situated advice you provide for trainees. An article referring to this is Culture's Causes.