Today, I watched a really intriguing Intelligence Squared Debate on the motion of “Smart Technology is Making us Dumb.” For the affirmative, Nicholas Carr and Andrew Keen argued; for the negative, Steven Weinberger and Genevieve Bell. For my part, I agreed the most with Genevieve Bell, whose main point was that there is a lot more to the story than whether it IS making us smart or stupid, mostly because there are a lot of smart technologies and a lot of ways we can use those technologies. I agreed least with Andrew Keen, whose conservative persective seemed to be that if we can find even a few ways “we” are using technology in ways he thinks aren’t substantive (twitter seems his favorite example), then that settles the matter.
But one thing I noticed is that the debate really hinges on what we mean by ‘smart,” “dumb” and for that matter, “intelligence.” Carr seemed to tie these things to short-term memory and attention; Weinberger seemed to argue that all intelligence requires is having access to information.Here is a comment I wrote below the debate that may be interesting to share here. (And, of course, check out the debate to form your own conclusions.)
Warning: since you are reading this on a blog, Keen may accuse you of being stupider for it.
There are two attitudes one can take when a child is not learning at the level we expect: fatalism and optimism. The fatalistic attitude is that which leads us toward giving up and changing direction; perhaps the child is not learning the material because she is not suited for it. The optimistic attitude is that which leads us towards redoubling our efforts; perhaps she is not learning because we are not teaching it correctly, intensely, or thoroughly.
Both attitudes have positives and negatives. If the child is not learning the material because she really is not capable, fatalism may save time and the potentially bad experience of trying to force the proverbial square peg into the round hole by forcing ill-suited information into an unwilling and unable participant. But fatalism is a bad thing if it means that we give up on a child too soon who could have learned if we had persisted.
Conversely, optimism has its benefits and drawbacks. Optimism, by definition, means persistence out of desire for a good outcome. Optimism leads to good results when it leads us not to give up on a child too soon. Of course, the hoped-for scenario of where the child gets the information by our sheer persistence does not always come to pass, in which case we see the downside of optimism: the risk of forcing students to do more than they may be able to do for the sake of hope for a better result.
The reason I point out these good and bad points is that the dilemma teachers often face ove which attitude to adopt is made (dare I say) impossible by our inability to know the future. Asking a teacher whether a child is capable of learning x or not – asking them to adopt a optimistic or fatalistic attitude – is asking them to know what the child is in fact capable of, which entails knowing the future. This is because knowing what a child’s potential is is premised on the idea of knowing what the child would be able to do if educated in the right way, which entails knowing what can’t be known in advance. The best we can do when contemplating a child’s potential is to give our best educated guess, which often isn’t really that educated at all.
To elaborate further on the difficulty of gaguing a student’s capability, I want to point out how essentially unfalsifiable estimates are. Let’s suppose that we believe that Johny is capable of learning Algebra and despite our efforts, he does not show evidence of learning it. Well, we can explain this in two ways: we can suggest that maybe Johny is not equipped to learn algebra, or that we have simply not done everything necessary to teach it to him. (more…)
Jonathan Hawkins, the creator of the PalmPilot and Graffiti handwriting software it uses, has written a book outlining a very interesting theory of what intelligence is. “On Intelligence” takes a non-behavioral (intelligence is not the same as intelligent behavior) and non-computational (intelligence is more than the ability to compute) approach to intelligence. Instead, he views intelligence as the ability to make predictions by taking stored memories and predicting future outcomes based on those memories. Hawkins suggests, uncontroversially, that this ability comes exclusively from the neocortex and, more controversially, that all operations we call intelligent can be reduced to the ability to make and adjust predictions.
Here is my review of the book, which I gave a four out of five stars on amazon.com
Jonathan Hawkins’s concern in “On Intelligence” is to outline a theory of what intelligence is that differs from ones floated around in various artificial intelligence (AI) circles. First, most theories of how to build “intelligent machines” focus exclusively on “intelligent behavior” without focus on the “thought” that must be behind it. (Think about Alan Turing’s test of an intelligent machine: if its behavior seems intelligent to humans, it must be intelligent. Purely behavioral.) Also, Hawkins is concerned that those few AI folks who have given thought to what intelligence is, apart from behavior, see intelligence as “ability to computer” and analogize it to a computer. But, Hawkins rightly notes, what we see as human intelligence -ability to synthesize disparate information, create novel solutions, apply old knowledge to new problems – is much more than computation. (more…)