Colin,
>From a quick read, the gist of what your are saying seems to be that AGI is just "engineering", i.e., the study of what man can make and the properties thereof, whereas "science" relates to the eternal verities of reality. But the brain is not part of an eternal verity. It is the result of the engineering of evolution. At the other end of things, physicists are increasingly viewing physical reality as a computation, and thus the science of computation (and communication which is a part of it), such as information theory, have begun to play an increasingly important role in the most basic of all sciences. And to the extent that the study of the human mind is a "science", then the study of the types of computation that are done in the mind is part of that science, and AGI is the study of many of the same functions. So your post might explain the reason for a current cultural divide, but it does not really provide a justification for it. In addition, if you attend events at either MIT's brain study center or its AI center, you will find many of the people who are there are from the other of these two centers, and that there is a considerable degree of cross-fertilization there that I have heard people at such event describe the benefits of. Ed Porter -----Original Message----- From: Colin Hales [mailto:c.ha...@pgrad.unimelb.edu.au] Sent: Monday, December 22, 2008 6:19 PM To: agi@v2.listbox.com Subject: Re: [agi] SyNAPSE might not be a joke ---- was ---- Building a machine that can learn from experience Ben Goertzel wrote: On Mon, Dec 22, 2008 at 11:05 AM, Ed Porter <ewpor...@msn.com> wrote: Ben, Thanks for the reply. It is a shame the brain science people aren't more interested in AGI. It seems to me there is a lot of potential for cross-fertilization. I don't think many of these folks have a principled or deep-seated **aversion** to AGI work or anything like that -- it's just that they're busy people and need to prioritize, like all working scientists There's a more fundamental reason: Software engineering is not 'science' in the sense understood in the basic physical sciences. Science works to acquire models of empirically provable critical dependencies (apparent causal necessities). Software engineering never delivers this. The result of the work, however interesting and powerful, is a model that is, at best, merely a correlate of some a-priori 'designed' behaviour. Testing to your own specification is a normal behaviour in computer science. This is not the testing done in the basic physical science - they 'test' (empirically examine) whatever is naturally there - which is, by definition, a-priori unknown. No matter how interesting it may be, software tells us nothing about the actual causal dependencies. The computer's physical hardware (semiconductor charge manipulation), configured as per the software, is the actual and ultimate causal necessitator of all the natural behaviour of hot rocks inside your computer. Software is MANY:1 redundantly/degenerately related to the physical (natural world) outcomes. The brilliantly useful 'hardware-independence' achieved by software engineering and essentially analogue electrical machines behaving 'as-if' they were digital - so powerful and elegant - actually places the status of the software activities outside the realm of any claims as causal. This is the fundamental problem that the basic physical sciences have with computer 'science'. It's not, in a formal sense a 'science'. That doesn't mean CS is bad or irrelevant - it just means that it's value as a revealer of the properties of the natural world must be accepted with appropriate caution. I've spent 10's of thousands of hours testing software that drove all manner of physical world equipment - some of it the size of a 10 storey building. I was testing to my own/others specification. Throughout all of it I knew I was not doing science in the sense that scientists know it to be. The mantra is "correlation is not causation" and it's beaten into scientist pups from an early age. Software is a correlate only - it 'causes' nothing. In critical argument revolving around claims in respect of software as causality - it would be defeated in review every time. A scientist, standing there with an algorithm/model of a natural world behaviour, knows that the model does not cause the behaviour. However, the scientist's model represents a route to predictive efficacy in respect of a unique natural phenomenon. Computer software does not predict the causal origination of the natural world behaviours driven by it. 10 compilers could produce 10 different causalities on the same computer. 10 different computers running the same software would produce 10 different lots of causality. That's my take on why the basic physical sciences may be under-motivated to use AGI as a route to the outcomes demanded of their field of interest = 'Laws/regularities of Nature'. It may be that computer 'science' generally needs to train people better in their understanding of science. As an engineer with a foot in both camps it's not so hard for me to see this. Randalf Beer called software "tautologous" as a law of nature... I think it was here: Beer, R. D. (1995). A Dynamical-Systems Perspective on Agent Environment Interaction. Artificial Intelligence, 72(1-2), 173-215. I have a .PDF if anyone's interested...it's 3.6MB though. cheers colin hales _____ agi | <https://www.listbox.com/member/archive/303/=now> Archives <https://www.listbox.com/member/archive/rss/303/> | <https://www.listbox.com/member/?&; 5> Modify Your Subscription <http://www.listbox.com> ------------------------------------------- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244&id_secret=123753653-47f84b Powered by Listbox: http://www.listbox.com
