Minds & Machines: Week 1 – Minds and Computers

This week I started a new online MOOC through MITx called Minds and Machines. This course is an introduction to philosophy of the mind. Some of the questions we will be thinking about in this course are:

  • Are you an “immaterial soul” , distinct from your brain and body?
  • Alternatively, are you simply a material or physical animal, living in an entirely physical world?
  • Do we see ordinary physical objects like lemons and iPhones?  And assuming that we do see them at all, do we see them as they really are?
  • Can consciousness be given a scientific explanation?
  • Can machines think?

The class is divided into 5 parts.

  1. Minds and computers
  2. From dualism to functionalism—a survey of theories of mind
  3. Minds and brains
  4. Perception
  5. Consciousness and the mind-body problem

The class consists of online lectures, readings, problems and assessments. The course leader is Alex Byrne, chair of philosophy at MIT.

In week 1 we had an introduction to the course before moving onto the first proper lecture. We started by learning more about what philosophy is. Philosophy is working out the right way to think about things, in the broadest possible sense. The best way to learn about philosophy is to do philosophy. There are 3 main branches.

  • Metaphysics – what is there?
  • Epistemology – what do we know and how do we know it?
  • Ethics – what should we do?

In explaining the value of philosophy Alex used a quote from Bertrand Russell from 1912. Russell says that the value of philosophy comes from its uncertainty. When we engage with ideas and problems on a philosophical level we are able to suggest many solutions that enlarge our thoughts. He also said that when we philosophise we wonder, we ponder and we break free from the norm. Philosophy shows familiar things in an unfamiliar way.

Philosophy of the mind is one of the many sub-brachches of philosophy. It aims to solve the problem of what does it mean to have a mental life? How does our mental life relate to the world? This relates back to the branch of epistemology.

Can we build a computer that thinks? It seems like the answer to this question is yes, take the IBM Watson computer for example, this machine won a quiz against humans. Surely this machine can think?

ibm-watson-2
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According to John Searle, professor of philosophy at the University of California at Berkeley, Watson is not a thinking machine. He says a computer is a device that manipulates formal symbols, such as 0’s and 1’s. Watson can process data very, very quickly, faster than humans, but that doesn’t mean it has a superior intellect. He goes on to say that Watson did not understand the questions, nor its answers. Watson didn’t understand why some of its answers were right or wrong. It didn’t even understand it won the quiz or that it was playing. This is because computers don’t understand anything. Basically, Watson faked it!

Screen Shot 2017-10-06 at 11.34.49 am.png

IBM’s computer was not and could not have been designed to understand. Rather, it was designed to simulate understanding, to act as if it understood. It is an evasion to say, as some commentators have put it, that computer understanding is different from human understanding. Literally speaking, there is no such thing as computer understanding. There is only simulation.

Searle, J 2011Watson Doesn’t Know It Won on ‘Jeopardy!’WSJ, accessed 6 October 2017, <https://www.wsj.com/articles/SB10001424052748703407304576154313126987674>.

Alex challenged us by holding up a tomato and asking is the tomato really there? Isn’t a tomato just a collection of colourless particles? Where does the red colour come from? Colour is not in the tomato, it is in the mind. Is colour an illusion? Is anything really the way we perceive it to be? Lots of interesting and challenging questions to think about. I liked Alex’s quote from Chris Frith from his book ‘Making up the Mind, “My perception is not of the world, but of my brain’s model of the world.”

Alex continued by discussing the differences between Strong AI and Weak AI.

  • Weak AI – a computer is a very powerful tool. For example, it enables us to simulate various kinds of mental processes, such as simulating weather patterns and storms
  • Strong AI – says that a computer literally has mental states (cognitive states in particular). Meaning computers would actually know things and believe things. An example would be the computer literally has meteorological states – it can drop 2 feet of snow on Cambridge

Searle says that weak AI is correct but strong AI is false.

Alex then talked about computer programs in more detail. A computer program is an algorithm, a mechanical recipe, for transforming symbols into symbols. You start with symbols, apply the recipe to get the output symbols. He said computers can be made out of anything. John Searle gives an example called the Chine Room.

Chinese room experiment
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This thought experiment explains how a computer can fake understanding by following a rule book. Searle is in the room processing Chinese symbols as a native speaker would and he is producing the correct output. But he does not understand Chinese. However, Searle is not the computer, he is only part of the computer. As Alex said, it is a bit like taking a neuron from your temporal lobe and saying that doesn’t understand English.

This was a great start to the course and looking forward to week 2 already.

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