Path: utzoo!attcan!uunet!samsung!zaphod.mps.ohio-state.edu!sunybcs!boulder!bill From: bill@boulder.Colorado.EDU Newsgroups: comp.ai.neural-nets Subject: Re: the baby bootstrap (determining input...) Message-ID: <18578@boulder.Colorado.EDU> Date: 19 Mar 90 17:29:43 GMT References: <725@berlioz.nsc.com> <720@berlioz.nsc.com> <6603@hydra.gatech.EDU> <5061@ccncsu.ColoState.EDU> <5130@ccncsu.ColoState.EDU> <4972@newton.praxis.co.uk> <34955@ucbvax.BERKELEY.EDU> Sender: news@boulder.Colorado.EDU Reply-To: bill@synapse.Colorado.EDU (Bill Skaggs) Organization: University of Colorado, Boulder Lines: 37 Let me point out that this is an issue philosophers have been arguing about for centuries. Locke believed that a baby is a "tabula rasa", with no prespecified cognitive structure. On the other hand, Kant, stimulated by Hume, decided that the ability to organize experience requires "synthetic a priori" concepts, which are not derivable from experience, but are not logical truths either; "space" is a prototypical example, "causality" is another. Also, there is increasing evidence that babies are "prepared" to learn certain kinds of things but not others. One of the most compelling examples, in my opinion, is phoneme learning. Each language uses a set of some thirty-odd phonemes (i.e., vowels and consonants, roughly speaking), and creates words by stringing them together. Different languages use different sets of phonemes. A baby, in order to understand language, must learn to analyze the stream of sound coming into its ears well enough to distinguish the phonemes of its language. This is a task so difficult that the best of modern computer technology does it very poorly; yet it is done almost automatically by virtually mindless three- year olds. If you were to show these same three-year olds pictures of the spectrograms of the sound (which contain the same information), you could show them pictures forever and they would never begin to be able to distinguish phonemes. (Adult experts can't do it.) The clearest examples of prepared learning, though, are seen in non-human species. Rats, for example, can easily learn to associate a novel taste with a later feeling of sickness, even when the sickness comes several hours later; and they can easily learn that a flashing light signals that they will be shocked unless they move away; but it is almost impossible to teach them to associate taste with shock, or a flashing light with a feeling of sickness. It seems that the nervous system has evolved to make strong assumptions about what sorts of things are likely to be causally connected, and connections that violate the assumptions are very difficult to learn. If this is true for rats, it is likely to be true for humans as well. -- Bill Skaggs