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Why it's Hard to Make Machines Think Original Thoughts
12-01-2008, 02:06 PM,
#1
Why it's Hard to Make Machines Think Original Thoughts
Quote:Robust artificial creativity systems are an important step towards the ultimate commodity: a mass-producable product that in turn produces solutions and ideas on demand. Think how this could add to our capacity for problem solving. The idea is as exciting as the challenges involved in realizing it. Many questions remain unanswered:

Not only do we lack understanding of our own creative mechanisms, but the basics of computer programs seem to oppose the idea of achieving unbound originality. Here’s a look at that important, fundamental problem when implementing creativity. In easy digest format, no less.
A Brief Introduction to Creativity

A painting done by the computer program AaronCrucial to what follows is pointing out that creativity is ill-defined and people generally have very different ideas of what it is. This can make it difficult to discuss and debate.

Art is typically strongly tied to creativity, and many scientists are focusing on this. The painting on the side was created by the computer program Aaron, which is one of the more famous creative systems. But while creativity exhibits itself very strongly amongst artists and is easily associated with them, that’s nowhere near the whole story. For example, there’s software like Thaler’s neural networks that have invented new, patentable physical materials. This is another type of creative expression.

And to go even further; in Emergence of Creativity, my chapter in the book Intelligent Complex Adaptive Systems, I explain and define creativity and its origins in a way that accounts for even the actions of primitive organisms — not only human abilities.

But for this article’s purposes, all we have to agree on is that creating something new or being original is an essential part of creativity. Given this agreement, we shouldn’t run into a problem with the following explanations. But even so, keep in mind how extremely multifaceted creativity is and that I’m simplifying the concept (to keep this article from becoming a book).
A problem when creating creative systems

To properly explain the problem, how programming seems to oppose creativity, we must understand what computer programs are: instructions. A set of steps the computer executes. Typically, when we create computer programs we specify a certain problem and in turn devise a set of instructions that addresses this problem.

A program that can add numbers is a very simple example of this: we specify that its input are numbers and operators, how it should apply the operators to the numbers and that the output should be the result of the computation. Note here that before we create a program we need to know what we want it to do and what instructions achieve that purpose.

Computer programs are instructions, even when they become more complex.
An example of a creative system

Consider an intelligent agent model. An agent is a system that perceives its environment (input) and acts upon that environment (output), and broadly speaking, an agent’s input can be anything from keystrokes to streaming video (or a combination).

Our agent is a writer, to stay within a creativity setting most are comfortable with (here’s to hoping you think people like Shakespeare are creative). For this particular case, the input is a human’s demanding to hear a story about a particular subject, like a story about detectives or robots. Our agent composes a story, puts it in a file and then acts upon the environment by displaying it on-screen.
Our agent perceives human input from keyboard and displays a story on screen

In between receiving input and presenting output is, of course, a program that maps the input to output. Its brain, loosely speaking. We’ve already stated the agent’s high-level goal: to write a story. It’s the part of the agent that makes decisions on where he puts the plot twist where we learn that his mother, Alice, wasn’t really an actress but a government agent.

But in order to make our agent write something other than gibberish, he must have a dictionary of words and he must know grammar. He must also have common sense to know how the world works or otherwise we’d be getting stories where a bucket drinks from a detective.

In the real world we would have to take our agent’s architecture quite a bit deeper. We would have had to give him some way of choosing plots, paragraphs and words, for example. But we’re going to look past that and just focus on what we already have at this point.
Instructions are limitations

Note now that when we gave our agent a dictionary, a goal, grammar knowledge and common sense, we effectively restricted him: He’s not a painter. He’s not a musical composer. He’s not a programmer, a witch, a lion or a wardrobe. And when we look at it as a creative writer, we begin to see he’s not that creative at all.

A goal limits the objectives of a system and thereby helps us organize how the system will behave1: Our agents should write a story — he’s not about to write a groundbreaking paper about artificial creativity. And what about his stories? He has common sense that dictates no man can fly without the help of machines. We killed our creative agent’s Superman right there.

But these restrictions were also necessary for him to do anything at all. To explain this with a familiar analogy, it’s like writing a cooking recipe: To bake a cake we need certain ingredients. When we bake it the ingredients define what kind of cake it becomes. But we’re baking a cake, not bread. And the cake is sweet, not sour. The ingredients are restricted to define a particular outcome of the baking. Similarly, the instructions we devise are what defines a programs behavior and outcome.

Basically, to make it do what we want it to, we impose restrictions — a confined set of rules out of all the possible rules in the world.
What kind of instructions make limitless systems if instructions themselves are limitations?

Now here’s the core of the problem, finally: We agreed in the beginning of this article that an essential part of creativity is originality and creating something new. But like we’ve discussed above we know beforehand how a program should behave before we make it, including what it should produce.
Diagram depecting a programmer knowing what his program will do

So how can we make a program when we don’t want to know beforehand what it should do, and when we want it to be as limitless as possible? If we must tell the program what to do, can the program ever be original? Can it surprise us? Can it make something novel?

The basics of programming require us to explicitly design mechanisms that produce certain outcomes. By giving these explicit instructions we inadvertently decrease the potential of the program surprising us since clearly it means that we know beforehand how it will behave.

The instructions that define our program (and make it work) are in turn the exact reason it can’t produce surprising, novel and interesting ideas.

But how about a self-organizing program that writes its own code on the fly to overcome its restrictions? Yes, that sounds appealing and is what many scientists working on artificial creativity are trying to do, in one form or the other. And it would be really easy too… if the program wouldn’t have to be creative to write new code!

Edit (Aug. 25th): Due to some comments from readers (thank you) I feel inclined to emphasize what I mentioned in the article: many creative systems have already been made (have a look through the creativity category).

I’ve personally created and worked on systems that present creative behavior. Making them more robust is just a question of time, research and development. The example used here is intentionally simple and raw to flesh out an essential problem that scientists face when developing creative systems—but this is a problem we are overcoming.

http://www.thinkartificial.org/artificialc...thoughts-intro/
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12-06-2008, 01:06 PM, (This post was last modified: 12-06-2008, 01:19 PM by JazzRoc.)
#2
Why it's Hard to Make Machines Think Original Thoughts
My creative processes frequently take place while I sleep. I have to be thoroughly occupied with some intractable problem, and then go to sleep on it.

It isn't a process I control: it is NEVER done to order. Quite often on some long technical project involving weeks of effort, then 70% of the time to deadline has elapsed before there is sufficient "strain" and my thought processes sufficiently intense. Sometimes 90%. Sometimes not at all. Just occasionally it just flows out instantly.

It is almost impossible to be consciously creative. One can, of course, be technically proficient in the interim, while waiting for true creativity to arrive: that helps a lot. But it's in the gaps, say relaxing with a cup of tea, or nodding off in the afternoon, when one is NOT consciously directing ones thoughts, that such a miracle can possibly take place.

Now I suggest that is the normal way creativity occurs with Man, and ask how can that be possible at any time with computers as they are presently configured. Do they lean back and yawn, look out of the window, doze, sleep? No - they're insanely full ON, all of the time (until they're switched off).

They can of course present one very quickly with all the options, but can they select the best, SEE synthesis, etc?

Perhaps there's an analogy with warfare and aircraft... back in the sixties it seemed inevitable that with super-fast and super-accurate missiles, a man in a cockpit didn't stand a chance, no matter what the speed of his aircraft was.

But forty years on, what do we have? A man in a cockpit (maybe pressing buttons for missiles) and his aircraft still has A GUN. All this has been tested by war, the machines may have shifted some parameters, but Man and his creativity STILL wins the "game".

Sorry about going on about wars and all, but wars are the best test of what is practical that Man has discovered. Maybe travel through space and other pioneering could replace war, but until...

I believe that our useless "junk" DNA has a lot to do with our natural creativity.
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12-06-2008, 02:09 PM,
#3
Why it's Hard to Make Machines Think Original Thoughts
Nice reply. Kudos

Do androids dream of electric sheep?

I predict a combination of the artificial with the human psyche at some point
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12-06-2008, 08:17 PM,
#4
Why it's Hard to Make Machines Think Original Thoughts
machines with original thoughts - sounds like edging towards HAL in space odessy
kill all humans
&Alice laughed, &There's no use trying,& she said: &one can't believe impossible things.& &I daresay you haven't had much practice,& said the Queen. &When I was your age I always did it for half-an-hour a day. Why, I've believed as many as six impossible things before breakfast.&
- Lewis Carroll

&Things are seldom as they seem ... Skim milk masquerades as cream.&
- Gilbert and Sullivan (Pinafore)

At NASA, it really is rocket science, and the decision makers really are rocket scientists.
But a body of research that is getting more and more attention points to the ways that smart people working collectively can be dumber than the sum of their parts. .. Irwin Janis? &Groupthink:& is a mode of thinking that people engage in when they are deeply involved in a cohesive in-group, when the members' striving for unanimity override realistic appraisals ? It is the triumph of concurrence over good sense, and authority over expertise.&
-John Schwartz & Matthew L. Wade
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12-12-2008, 12:22 PM,
#5
Why it's Hard to Make Machines Think Original Thoughts
personally i think IA has to be shaped on a ground up point of view. you need to develop a brain. I requires a lot of experiences before a fully functioning being can pop out. like the main stem for a baby up to the fully developed brain of an adult. its the set of experiences that make up the whole.

If AI will ever take off it need to make a processor that can rebuild itself on the fly sort of a cross between a cpu and flash memory. memories are not calculations or algorithms just answers. yes, no, maybe. those are the main logical paths for AI to really work. but as binary doesn't really equate for a maybe, errors will always happen. logic gates are built to only have definite outcomes. a computer can not pick a random number out of the sky.
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12-12-2008, 03:33 PM,
#6
Why it's Hard to Make Machines Think Original Thoughts
found an interesting thread on it

http://forum.conspiracycentral.net/index.p...20watt&st=0
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12-28-2008, 01:15 PM,
#7
Why it's Hard to Make Machines Think Original Thoughts
Quote:personally i think IA has to be shaped on a ground up point of view. you need to develop a brain. I requires a lot of experiences before a fully functioning being can pop out. like the main stem for a baby up to the fully developed brain of an adult. its the set of experiences that make up the whole.

If AI will ever take off it need to make a processor that can rebuild itself on the fly sort of a cross between a cpu and flash memory. memories are not calculations or algorithms just answers. yes, no, maybe. those are the main logical paths for AI to really work. but as binary doesn't really equate for a maybe, errors will always happen. logic gates are built to only have definite outcomes. a computer can not pick a random number out of the sky.
Yet there is such a thing as FUZZY LOGIC.

The weird droids one finds in Iain M. Banks's "Culture" series are the best pointers to the future I've ever seen... they're funny, rude, idiosyncratic - weird!

Ah, well, one lives in hope....
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02-03-2009, 12:35 PM, (This post was last modified: 02-03-2009, 12:38 PM by rsol.)
#8
Why it's Hard to Make Machines Think Original Thoughts
my nan used to use fuzzy logic:) she called everyone Jill.

Fuzzy logic only works in certain ways and in certain situations. Fingerprint readers use fuzzy logic. These fail miserably because after the database gets too full it starts "guessing" who is putting their finger on the reader.

If you want your robot to focus on a point then fuzzy logic works well. I wouldn't rely on it to make a decision. There is much to say about volume decision. Basically in most processes of thought, we use many factors to decide something. The real decision comes when an overwhelming volume of positive or negative thoughts toward the subject take over. If there is more for than against, then im for.

Then there is the precedent principle. how do you do something you have never done before? Even for humans this can be very taxing. We usually exploit past experiences and incorporate them into the current task/problem. You could use some fuzzy logic there. Although it would take maybe one "bad" experience and you could corrupt the system.

There is also the existentialist argument. What if you ask your robot a question it cant answer? Will it continue to use cpu time on calculating "pi" forever simply because you asked it a maths quiz question? robot? hello? "PLEASE WAIT" god damn it i gotta reboot again!!!
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02-27-2009, 11:22 PM, (This post was last modified: 02-28-2009, 12:12 AM by JazzRoc.)
#9
Why it's Hard to Make Machines Think Original Thoughts
Quote:my nan used to use fuzzy logic:) she called everyone Jill.

Fuzzy logic only works in certain ways and in certain situations. Fingerprint readers use fuzzy logic. These fail miserably because after the database gets too full it starts "guessing" who is putting their finger on the reader.

If you want your robot to focus on a point then fuzzy logic works well. I wouldn't rely on it to make a decision. There is much to say about volume decision. Basically in most processes of thought, we use many factors to decide something. The real decision comes when an overwhelming volume of positive or negative thoughts toward the subject take over. If there is more for than against, then im for.

Then there is the precedent principle. how do you do something you have never done before? Even for humans this can be very taxing. We usually exploit past experiences and incorporate them into the current task/problem. You could use some fuzzy logic there. Although it would take maybe one "bad" experience and you could corrupt the system.

There is also the existentialist argument. What if you ask your robot a question it cant answer? Will it continue to use cpu time on calculating "pi" forever simply because you asked it a maths quiz question? robot? hello? "PLEASE WAIT" god damn it i gotta reboot again!!!
There's a general feeling that each of us considers ourselves to be a single entity, when in fact the neurones in our brains gather together in "crowds", each of which resolves down to a "spokesman", and the crowd of "spokesmen" are resolved as our single identity by a (hopefully) single "census-taker".

Now each neurone, each neurone cluster, each "spokesman", and finally our "census-taker" operate to a set of unique and specific (and different!) programs. How they do that is probably through a combination of hardware design and fuzzy logic.

It's a wonder we come to a decision at all! But of course, we are massively parallel and incredibly interconnected in a way that makes a mockery of our quick-thinking, but stupid, microprocessors.

Existential questions we can easily deal with, using the "Er, I don't know, duh!", followed by scratching a testicle (known as the "Homer", it must have been one of our earliest sub-routines...possibly dating back to the Early Cretaceous Era.)

Cheers, Jill.:)
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