Here's the press release: Robot scientist becomes first machine to discover new scientific knowledge
In an earlier posting, I discussed the idea of computers participating in the reasoning process of the scientific method. There are, as far as I can see, two fields that are applicable to this. One is machine learning, where a computer studies a body of data to find patterns in it. When done with statistical methods, this is called data mining. The other is automated reasoning such as is done with semantic web technology.
So I was quite interested to see the news story linked above. Researchers in the UK have connected a computer to some lab robotics and developed a system that was able to generate new scientific hypotheses about yeast metabolism, and then design and perform experiments to confirm the hypotheses.
This is important because there will always be limits to what human science can accomplish. Humans are limited in their ability to do research, requiring breaks, sleep, and vacations. Humans are limited in their ability to collaborate, because of personality conflicts, politics, and conflicting financial interests. Human talent and intelligence are limited; the Earth is not crawling with Einsteins and Feynmans.
That's obviously not to say that computers would have an unlimited capacity to do science. But their limits would be different, and their areas of strength would be different, and science as a combined effort between humans and computers would be richer and more fruitful than either alone.
I still think it's important to establish specifications for distributing this effort geographically. I would imagine it makes sense to build this stuff on top of semantic web protocols.
I like the idea that with computer assistance, scientific and medical progress might greatly accelerate, curing diseases (hopefully including aging) and offering solutions to perennial social problems like boom-and-bust economic cycles. Then we could all live in a sci-fi paradise.
No comments:
Post a Comment