An Epistemology for Cyborgs

In the next several entries to this blog I want to focus on epistemology and the implications of technology on the question of how and why we know what we know.  These posts will be numbered, not because they are in any kind of sequence, just to help keep them organized.

Recovering the Question:

                Epistemology has fallen out of favor (but not quite as much as its half- brother metaphysics).  It has been kidnapped by analytical philosophers who have starved it to near extinction, making it live off a steady diet of over and under coded sentence fragments.  The grand reach of the original question has been lost in the science of cognition and the rise of artificial intelligence.  Before we concede the field to ever more sophisticated machines and the algorithms that run them, I think we should step back and ask exactly what it means to “know” something in this environment, bordered on the one hand by technology and on the other by increasingly mechanistic notions of what it means to be human.  I think it is important to pause for a moment and sort out what human intelligence is; what are its characteristics, limitations and purposes.

                It’s become too easy frame these questions in disembodied contexts that focus on speed and information in one direction and chemical reactions in another.  The value of thinking epistemologically is that implies an embodiment – a biological, that is to say living, entity – that can’t be reduced to information or chemical reactions.  Epistemology also implies the consciousness of the knower, the awareness of the act of knowing.  Human intelligence may seem limited when compared to the speed and data of a computer, but it also presents an option that artificial (I would prefer to call it machine) intelligence lacks; it is organic.  It is organic in a way that even the most sophisticated algorithm, even ones that produce infinite variable, cannot completely mimic.  I mean no disrespect to the potential and power of machine intelligence.  It has become a valuable tool, maybe we could even day collaborator, in the way we understand our world and our place in it.  I simply want to draw a line between machine intelligence and what it means to know and learn as a human being.  Confusing them only confuses and limits the potential of both.

                When we learn, we are not learning about an objective world that is static.  When we learn, we are first and foremost learning about ourselves, and we are bringing forth a world that we share with others through the act of languaging.  Epistemology is not about absorbing or manipulating knowledge as much as it is creating consciousness.  What gets lost in the technological and materialist notions of learning and knowing is the connection between learning and living well, fully engaged in both the creation of the world we bring forth with others and the responsibility of harmonizing with it.  In other words, epistemologies move and change – they are themselves organic.   To reclaim epistemology is to reclaim the way we ground ourselves in an ongoing dynamic process.

                We live in a country that produces more technical and expert data and information than any culture has ever created.  There are over a billion pages of new scientific data alone published every year.  Yet we also live in a country where the shared understanding and value of that data is limited to a very small sub set of the population and in which many of the most basic findings of science are rejected by large swaths of the population.  We surround science, and every other academic and professional discourse, with barriers meant to limit participation and understanding.  While some people ‘know’ a lot about a particular subject, it doesn’t ‘bring forth a world,’ as Maturana would have it.  It also doesn’t shape the actions and consciousness of most of its practioners.  Only a few scientists really do science; most are mere technicians.  An even smaller number of the people who really do science think that way in the rest of their lives.  The same is true of the rest of the academic and professional worlds.  Separating the things we think from the social, biological, technical and spiritual worlds we inhabit is to engage in what Blake called ‘ single vision.’

                To reclaim the question of epistemology in a world dominated by technological and analytical systems is not going to be easy.  Not reclaiming it will mean that the only real outcome of ‘human intelligence’ will be to build machines that can escape this planet to colonize others.  Only by resituating ourselves in the autopoietic context of our own lives can we learn, again, who we are.