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What AI Elements Could Improve the Web?
DavidpFitz asks: "I'm entering my final year of my Artificial Intellgience/Computer Science degree at Birmingham Uni. (UK). The trouble is that I can't decide what to do for my final project. I'd like to do something of practical value delivered over the web (things like an intelligent Slashdot filter spring to mind :-), but I always come up with reasons against everything I think of. Can anybody think of ways they would like a web site to react more intelligently that they currently do. Clever shopping carts? More targeted news? Both of these are rubbish, I think - so more interesting and complex ideas are welcome! The main thing, is that it has to have a strong AI element in it, not just appearing to be clever."
Interesting thought. So if we were to apply more AI to the web, what areas should we target? And I feel this is a valid question even if someone may be using these ideas for their school project. These are still just that: ideas. DavidpFitz will have to finish and implement his final project regardless of anything said in this forum, so why not take his line of reasoning, brainstorm a bit and have some fun with it?
The problems of the web that can have AI-type solutions are generally semiotic in nature. We could have intelligent agents, able to pay our bills and do our shopping for us, if we had a system of symbols that mapped clearly and unambiguously to meanings, or, a non-symbol processing system able to decode the web the way a human does. Most likely, we'll get something midway between them.
:^P
The GOFAI idea that human cognition is a matter of disembodied symbol processing is dead, and good riddance. However, our computers remain most useful as symbol processing engines, not as the more complex kinds of massively parralel connection engines that most people think brains are. We can get computers to emulate that kind of brain functionality, but only on a very limited scale compared to the human mind. Human-equal parralel machines are not just around the corner, so we have to augment the connectionist systems we have with symbol processing facilities.
The kind of project that interests me is a system that uses XML formats to provide clear semantics on the web, and connectionist methods to make judgements about how to act in response to those symbols. A system, for instance, that can scan an XML resource for information about rock concerts or movie listings, and having learned in more connectionist ways the preferences of the user (both in terms of costs, scheduling and personal taste) can inform them of events they might like to see, perhaps even going so far as to make tentative reservations when it's very confident.
The same kind of system could be used to solve library research problems. An XML document structures data semantically enough that a connectionist system can make quick, fairly superficial judgements about the contents and how they relate to the research needs of its users. It can then do more indepth readings of the highest confidence documents, leading to better sources and new documents. In the end, it can provide the documents to users and assist them when there are gaps in their knowledge by pointing them to the document that fills the gap.
The killer ap for AI would be automatic translation. Since that's my field, I don't think it's somewhere you ought to go without a strong knowledge of linguistics, and of the past failures in the field. I have some ideas, but that's what my PhD is going to be about.
There needs to be a real push into getting intelligence in educational software (for kids). Most of what I've seen is drek - while some of it is very slick and good-looking, it lacks real educational content. You either do not learn anything, or you learn it once and then repeat it endlessly.
Here's a challenge for your AI - adaptive educational software. Most software today requires the child to 'log in' so it can keep track of their saved games. Go further. Keep track of what the child does, how successful they are, and tailor the next experience accordingly.
Give rewards for progress. Reduce the rewards for continued success at the same level (gradually). Prod them into more difficult problems / puzzles / challenges. Eventually remove the lower, introductory, levels all together. Give different rewards.
Do all this while keeping it fun, and keeping them coming back for more. Pop quizes to keep them sharp - reward those accordingly. More advanced information (kind of like sidebars), when they are ready for it, can appear as options. Almost a tutor / friend relationship.
Teach the young how to learn - what could be more challenging for an AI project?
Oh. You mean START? Ask it a serious question and will often give you the write answer. It can a few non-serious questions as well ;).