A commonsense distinction is often made between natural and artificial intelligence. Natural intelligence is moored to our species innate biological makeup and unique capacity for creativity and meaning-making. The meanings we make are embodied in individual personhood and form the basis of community identities. As social beings that create order, we've built infrastructures for the production and ownership of these knowledge systems that frame what we know, how we know, and in a recursive sense what our individual and collective right to it.
Artificial intelligence, on the other hand, is often seen to be pre-determined by a mechanical nature. It is a product of our species but at the same time something very different – its own kind of “living thing” humming away in the grey-blue light of server farms, our post-industrial version of the factory. In this distinction, machines, technologies, and algorithms become disembodied players in collecting, producing, and owning human knowledge. And when they do, we sometimes allow artificial intelligence to operate under different social rules – the very same rules we established for creators of knowledge to protect their moral, political, and economic rights. However, this physical distance belies a dependence up human, embodied intelligence. Artificial intelligence is only as smart the human meaning it has recorded and recalculated by the processes of “machine learning.”
At the Nineteenth International Conference on Technology, Knowledge and Society we want to pause at a philosophical crossroads to ask:
How might the disembodied thinking machine demand we reframe master categories: “old” and new “materialisms; human and the non/post-human?
What is revealed in a new political economy of disembodied thinking machines? Could it mark a final transition from late capitalism to some newly forming nebula?
And how do disembodied thinking machines shape understanding of productive and non-productive in domains of knowledge work?
What will be the rules to regulate these disembodied thinking machines and the relations of these machines to humans via processes of machine learning? To what extent in in what ways does artificial intelligence leverage and extend embodied human intelligence?
We are not just interested in considering these questions theoretically, we invite papers and case studies from those who also are on new approaches to action and intervention for an age of thinking machines.