I’m currently reading a draft of my wife’s PhD thesis. The thesis uses metaphor to examine the concepts that underpin research within the Information Systems discipline. It finds that research within the discipline appears to have a very heavy emphasis on techno-rational type conceptions of organisations, individuals and artifacts. There are various connections between this work and that of learning analytics and some of the assumptions behind the semantic web. This is an initial attempt to make some of these connections. Given limited time (I have to get back to commenting on the thesis), this has become more a place-holder of thoughts and ideas I need to explore more fully.
This post was prompted by this quote by Merlin Donald that is included in the thesis (emphasis added)
It is far more useful to view computational science as part of the problem, rather than the solution. The problem is understanding how humans can have invented explicit, algorithmically driven machines when our brains do not operate this way. The solution, if it ever comes, will be found by looking inside ourselves.
This captures some of my concerns when I start hearing computer scientists talk about intelligent tutors, the semantic web and other “big” applications of artificial intelligence. I don’t doubt the usefulness of these techniques in their appropriate place, however, I think it increasingly unlikely that they can effectively replace/mirror/simulate a human being outside of those limited places.
Another interesting quote from Merlin Donald’s home page
His central thesis is that human beings have evolved a completely novel cognitive strategy: brain-culture symbiosis. As a consequence, the human brain cannot realize its design potential unless it is immersed in a distributed communication network, that is, a culture, during its development. The human brain is, quite literally, specifically adapted for functioning in a complex symbolic culture.
The first Donald quote mentioned above comes from the book The way we think: Conceptual blending and the mind’s hidden complexities (Fauconnier & Turner, 2003). A book that argues that conceptual blending is at the core of human thinking, or at least what makes us distinctive.
Lot’s more to read and ponder. For now, some questions
- Is there a fit here with connectivism and/or distributed cognition (or similar)?
- What implications do these ideas have for analytics and how it can make a difference?
- What critiques are there of these ideas?
Donald, M. The slow process: A hypothetical cognitive adaptation for distributed cognitive networks. Journal of Physiology (Paris), 2007, 101:214-222.
Fauconnier, G. & Turner M. (2003). The way we think: Conceptual blending and the mind’s hidden complexities. New York, NY: Basic Books