Philosophy 101D

Our final screening will be this Thursday at 7pm in Wohler Hall rm 24. Wohler is directly behind DKH.

We will be watching the documentary Love Machine by Peter Asaro and Doug Matejka. From the press release:

Love Machine considers the social and moral implications of building humanoid robots sophisticated enough to participate in social and emotional roles that are traditionally considered exclusively or even essentially human: friendship, sex and love. The film examines the actual technologies being developed in these directions, and discusses these issues with the people who are pursuing these technologies as well as those who seek to profit from them. It also confronts various social critics, commentators and philosophers of different perspectives in a effort to open a dialogue on what implications these technologies might have for human relationships in the future.

Among those interviewed are:

Roboticists:
Rodney Brooks, Director of the MIT Artificial Intelligence Laboratory
Hans Moravec, Carnegie Mellon University
Gill Pratt, Cynthia Breazeal, and Brian Scassellatti, MIT
Ken Goldberg, University of California, Berkeley.

Philosophers:
Daniel Dennett, Tufts University
Hubert Dreyfus, Univesity of California, Berkeley
Manuel DeLanda, Columbia University and Institute of Advanced Study-Princeton

Sex & Culture Commentators:
Carol Queen, Robert Morgan Lawrence and Lisa Palac
Ernest Green, Editor of Taboo Magazine

Childhood technology-use advocates:
Joan Almon, and Colleen Cordes

and the entrepreneurs building such products as the Sybian and Real Doll and others . . .

I was sent this video by a student I had last semester. Feel free to leave a comment!

Click the link below to see all the videos shown during last week’s movie screening. Comments are appreciated!

Continue Reading »

This whole semester has been building up to a serious philosophical discussion of the internet. People use the internet all the time, but know very little about it. So to get you psyched up for the discussion, you should watch this video:

Here’s a good, though old, Discover Magazine article about self organizing, evolved machines that is worth a read.

Evolving a conscious machine

Strangely, Thompson has been unable to pin down how the chip was accomplishing the task. When he checked to see how many of the 100 cells evolution had recruited for the task, he found no more than 32 in use. The voltage on the other 68 could be held constant without affecting the chip’s performance. A chip designed by a human, says Thompson, would have required 10 to 100 times as many logic elements—or at least access to a clock—to perform the same task. This is why Thompson describes the chip’s configuration as flabbergastingly efficient.

It wasn’t just efficient, the chip’s performance was downright weird. The current through the chip was feeding back and forth through the gates, swirling around, says Thompson, and then moving on. Nothing at all like the ordered path that current might take in a human-designed chip. And of the 32 cells being used, some seemed to be out of the loop. Although they weren’t directly tied to the main circuit, they were affecting the performance of the chip. This is what Thompson calls the crazy thing about it.

Thompson gradually narrowed the possible explanations down to a handful of phenomena. The most likely is known as electromagnetic coupling, which means the cells on the chip are so close to each other that they could, in effect, broadcast radio signals between themselves without sending current down the interconnecting wires. Chip designers, aware of the potential for electromagnetic coupling between adjacent components on their chips, go out of their way to design their circuits so that it won’t affect the performance. In Thompson’s case, evolution seems to have discovered the phenomenon and put it to work.

It was also possible that the cells were communicating through the power-supply wiring. Each cell was hooked independently to the power supply; a rapidly changing voltage in one cell would subtly affect the power supply, which might feed back to another cell. And the cells may have been communicating through the silicon substrate on which the circuit is laid down. The circuit is a very thin layer on top of a thicker piece of silicon, Thompson explains, where the transistors are diffused into just the top surface part. It’s just possible that there’s an interaction through the substrate, if they’re doing something very strange. But the point is, they are doing something really strange, and evolution is using all of it, all these weird effects as part of its system.

In some of Thompson’s creations, evolution even took advantage of the personal computer that’s hooked up to the system to run the genetic algorithm. The circuit somehow picked up on what the computer was doing when it was running the programs. When Thompson changed the program slightly, during a public demonstration, the circuit failed to work.

All the creations were equally idiosyncratic. Change the temperature a few degrees and they wouldn’t work. Download a circuit onto one chip that had evolved on a different, albeit apparently identical chip, and it wouldn’t work. Evolution had created an extraordinarily efficient, utterly enigmatic circuit for solving a problem, but one that would survive only in the environment in which it was born. Thompson describes the problem, or the evolutionary phenomenon, as one of overexploiting the physics of the chips. Because no two environments would ever be exactly alike, no two solutions would be, either.

Cases like this seem to justify Turing’s argument that ‘machines can sometimes surprise me’, though Turing was quite far from thinking along these lines.

Going over the posts, there seem to be a lot of people still of the opinion that machines can only do what they are programmed to do. Maybe this will help to shake that bias. All the machines in this demonstration were evolved using genetic algorithms, which means that their design was not imposed by a human, but are the result of competition for survival by a number of different designs.

You can read more here:

Virtual Evolved Creatures
Genetic Algorithms (Wikipedia)

I’ve been thinking about the issue whether machines can think. This is my final viewpoint: Thinking consists of the ability to contemplate about the future, past, or even imaginary. A machine is not going to wonder about its death or whether it can get a job in the future. What a machine can do is compute numbers/symbols, that’s why they such machines computers. If they have the ability to drive solo along hundreds of miles of rugged terrain without a roadmap, they are not really thinking about where they are going. All they do is gather information about their environment, crunch some numbers and adjust to what those numbers said. They are programmed to avoid certain obstacles, and during their trip, they cannot learn from their mistakes. If they keep running into steep banks, they aren’t going to know to avoid them later down the road. They can only adjust their settings after the race is finished and the programmer fixes his mistakes in the way he programmed his machine.

After watching The Great Robot Race video, I am a little more convinced that robots can think and make judgments. Although, it took many people to build these complex robots over a long period of time and with a lot of money, in the end it was up to the robot to figure out how to make it through the maze. These robots were equipped with many different lasers, cameras, and GPS systems that told them how to take the information given (about the terrain) and decide what action to take in order to not get stuck or run into something. After the first obstacles at the California Speedway where none of the robots made it very far, I did not think that the robots would be capable to drive through a desert. The robots were given tunnels, terrain changes, obstacles such as cones and hay. When combined it took a very ‘knowledgeable’ and skilled robot to make it to the end. The whole time I was watching this movie, however, I just kept thinking of the ethical implications that having such advanced robots would do to our society. On one hand, it would be a great thing to replace military vehicles with a robot that does not have a person inside who is in danger. This type of contribution would greatly help the military especially in this time of war. However, there are other ethical questions that we need to think about before replacing other common items with a robot. Technological advancement can make it possible to have a robot do many things that humans do everyday. Driving to work, assembling a car, or doing household chores can all be done with a robot, which I then wonder if it is such a good thing to be doing. People lose jobs when robots can do it faster and for less money which can hurt thousands of people and their families. Also, if a job is done by a non-human, the person then is not responsible for it anymore (for example, a robot vacuum) which could either lead to more productive things in the human or more lazy behaviors. It’s hard for me to be completely pro-robot but as with any new technology, there are always complications that eventually people look past.

Over this week we have been discussing about how machines could have intelligence similar to us humans.  At first thought it seems insane that anyone could think that this could be possible.  In fact I couldn’t agree more.  As humans we have the utmost intelligence on this planet.  It is possible for us to make our own decisions when we want to, why we want to, and how we want to.  There is nothing that influences us to make a decision, unless you count peer pressure, bribes, etc.  We live freely with no code programmed into us, forcing us how to live. (You could get technical and say what about the people in the prison system?)

Machines and computers, however, are another story.  These pieces of metal are built for a specific purpose.  A problem arises and several individuals, mainly engineers and programmers, collaborate on how to conquer this problem.  A machine is built and then programmed specifically to dominate this obstacle.  This signifies my point in that machines can’t make their own decisions.  They are not intelligent enough to decide what to do.  Humans must physically program this machine to do what it was assigned to do.  Machines have what is called artificial intelligence and is nothing close to human intelligence because it isn’t true/natural intelligence according to human nature.

I have explained my reasoning of why machine artificial intelligence is nothing close to human intelligence.  Others could argue that machines are just as intelligent as humans because they choose the most logical decision out of many just like we do.  Or that our human intelligence is based on learning which is the same thing as a machine being programmed with instructions.  I leave the opposite side open to discussion/argument.

One thing not covered in any of the arguments about artificial intelligence, is the ethics and need for this technology. While it is interesting to know how far human capabilities go as far as engineering something so complex, does this technology provide anything else for the human race?

First of all, artificial intelligence seems to have stemmed from the questions that have long been discussed about what human intelligence is and how it operates. The quest for figuring out how to program a computer to complete human tasks or mimic human behavior, is just part of exploring how our own intelligence works. When it comes to this though, does exploring wires, energy, programming, and rule-based functions really relate to how the human brain works? We still don’t know for sure what is happening in our brains, so how can we compare our brains with how AI technology works? As brought up in the arguments for God’s existence, the strength of this argument is based on how closely related the two systems are (which in this case is very debatable).

If artificial intelligence stems from the ideas of solving how the human mind works, we know why AI has ever come up and is being pursued. But have we ever thought of the ethics behind the decisions we make in this pursue? After we figure out how to make a computer or robot act exactly like a person, what do we do with this technology? Are we going to use them for maintaining jobs that no one wants to do anymore? This would give us more leisure time, but at the same time people can lose jobs to these robots. If they are not used for that, they might be used for companionship. There are robots being made that can recognize facial expressions, etc. If we have these computers that act just as friends, aren’t they really just restraining us from having normal contact with other humans. Our society is already governed heavily by technological mediums. The Internet (and even cell phones), the most recent medium in keeping people in touch with the ‘world’ and loved ones, just makes us prisoner to our own technology. If artificial companions come from this research in AI, we are motivating people to interact less with other humans around them and more with technology. Not good. These are only a few ethical concerns that I have been thinking about when it comes to advancements in artificial intelligence.

Because of class, I’ve been thinking about this movie lately, so I thought maybe we could talk about it.

Bicentennial Man is about a robot named Andrew that starts to display several human-like qualities and his quest to join humanity.

There are several scenes which illustrate the difference between human thought and computer thought.

In one scene, he carves a horse figurine out of driftwood for the little girl. The father asks where he got the horses design from. Andrew says that he didn’t get the designs from anywhere. He just saw the horse in his head, and chipped away the pieces of wood that wouldn’t be part of the statue. The family takes this as one of the many signs that Andrew is not a typical robot. Creating his own design takes creativity and intentionality.

Most of the comedy in the movie comes from Andrew’s initial lack of understanding jokes and language. When the oldest girl says that the chicken “sucks” or tells him to jump, he takes everything literally. When Andrew tries to tell jokes to the family, he rattles off the sentences without pausing between the set-up and punchline and without pausing for laughter. The semantic use of language and comedic timing are both qualities of the mind that only humans can have. Eventually, Andrew will learn to use both, but that’s only because in this fictional world, there’s “just something different” about him.

Has anyone else seen this movie?

I thought this article was interesting, especially considering our latest topic in class. Apparently Japanese scientists have created a robot that can “taste” food.
Japanese unveil robot wine steward

This reminded me of “The Robot Reply” which is part of the Searle article. The argument is: if we put a computer inside a robot which apparently perceives the world around it (through seeing, doing, tasting, etc.) couldn’t we say that the robot really has the ability to understand? Searle says no, because the robot is still just manipulating symbols and facts.

All right, imagine this…. the total Turing test. Scientist build what they claim is an intelligent robot. It can decently carry on a conversation. It can see using cameras and scanning devices. It can taste with a more evolved version of the technology described in the article above. It can also detect sound, touch, and smell.

So… does this robot have a mind like we do?

My instinct tells me no.

The artificial intelligence tests we’ve discussed the most frequently are chess and using language. I don’t think either one of these is particularly good for comparing a computer to the human mind. Chess is a closed, formal system which the computer can play with probability and calculations. Even language can be sort of calculated, because of the structure that comes with grammar. The computer could pick out key words and arrange appropriate responses according to the Subject- Verb- Object foundation.

I think a better test would be analyzing a painting.

Take the robot I’ve described and tell it to say what it thinks the painting means. The robot sees the picture through the camera lens. It scans the painting from top to bottom, picking up on colors, lines and space. Assuming the picture isn’t abstract, the robot might be able to tell you if the subject is a woman, a building, etc.

The robot also might have certain information about paintings and symbolism programmed in, such as: blue is used in sad paintings, or a + shape might somehow allude to crucifixion; but, I don’t believe a robot could ever give an interpretation on what the painting might symbolize, or for that matter, decide whether or not the painting is beautiful. The thought process is too subjective. These decisions can’t be made with the manipulation of symbols.

I realize I’ve given somewhat of an “X- factor” response, but analyzing art is somewhat different from some of the other X-factors listed by Turing. Some of the examples he gives include: falling in love, caring, enjoying strawberries and cream, and having a sense of humor. I agree with Turing’s critics that the human mind is somewhat needed for these abilities, but they don’t necessarily have anything to do with the kind of intelligence that artificial intelligence tries to replicate. Learning art, however, most definitely requires intelligence…. the kind of intelligence computers simply cannot have.

Thoughts on this?

On page 22 of the course packet, Haugeland says “It might seem that, in principle, simulation must be possible anyway, because rats are made of atoms, and each atom obeys known equations. But such a principle is utterly out to lunch.”

Well, we don’t have simu-rats, but we are getting close. Here’s a link to research being done on this very campus:

Researchers simulate complete structure of virus–on computer

When Boeing and Airbus developed their latest aircraft, the companies’ engineers designed and tested them on a computer long before the planes were built. Biologists are catching on. They’ve just completed the first computer simulation of an entire life form – a virus.
…

A computer program was used to reverse engineer the dynamics of all atoms making up the virus and a small drop of salt water surrounding it. The virus and water contain more than a million atoms altogether.

The necessary calculation was done at Illinois on one of the world’s largest and fastest computers operated by the National Center for Supercomputing Applications.

Respond to this thread by Tuesday’s class to receive participation credit for this week. Also, remember to read Searle’s paper in the course packet for Tuesday!

Prompts and Questions:

• Haugeland suggests that the analogy to computers will solve the Cartesian problem of mind/body dualism. Are you convinced?
• Haugeland lists a number of X-factors that cognitive science may be unable to account for, including consciousness, ‘original’ intentionality, and caring. Do you agree with any of these objections? If so, do you think this introduces a new kind of dualism?
• Explain the difference between analog and digital, or between algorithms and heuristics, as Haugeland describes them. Are these differences fatal to the central thesis of cognitive science?
• Turing’s imitation game is meant to give a behavioristic account of intelligence that avoids the problematic question, ‘Can machines think?’ Do you think the imitation game satisfies this worry? Why or why not?
• Is Lady Lovelace’s objection to the Turing Test fatal? Are Turing’s responses satisfactory?
• Turing’s final suggestion is to build learning machines. Do you think a machine that learns can be genuinely intelligent? Why or why not?