Information seems to be the hot word today. It’s one of those slippery concepts that exists in a somewhat definable way in mathematics and science – particularly in information theory – but it is a hot item with or without a precise way to define it. Just look at finance, media, or a zillion other things hitting your inbox daily.
Here, in New York City, Mayor Bloomberg has gotten the bureaucratic machinery to move in the direction of building a campus in New York for the purposes of dealing with information. It’s great to have someone managing a city who understands these imprecise concepts, while recognizing their importance. Furthermore, it’s nice to have someone who knows how to spin their effects into the precise things that voters – and consequently politicians – care about: jobs, jobs and jobs (read: “taxes, taxes and taxes”).
Not only is information turning municipal machinery, but it is also warranting retrospectives on how we got to this state of information-ness. The latest prodigious attempt at this is James Gleick’s The Information: A History, A Theory, A Flood. This book is hitting all the bases for me thus far (it’s a long read – so don’t expect to finish it on a puddle-jumper flight. Treat it instead like an HBO series that you digest in installments). In Gleick’s book, you get the historical – and right up to the present – explanation about how computing machines came about, and you get a little more of descriptive precision on this thing people call “information.”
For us in biomedical sciences, none of this should be surprising, neither the New York municipal support for the study of information or an historical account of it are surprising facts. Well, maybe just in the regard that for once a majority of people are in concordance with scientific experts (counterexamples: global warming, HPV and a few other things down the years). Because isn’t this what biomedical sciences are increasingly about?
We’re done cataloguing where bones and organs are, and how many different species of nematode there are. Now we’re trying to figure out how this mess works. And for those physicists-turned-biologists (such as myself), we’re doing our darned best to make the picture a little bit neater. This is perhaps why so many of us have fallen into the arms of the information temptress: we love her simplicity, and her ability to beget complexity.
This might be the reason why it seems most theoretical neuroscience conferences I’ve attend are like Alcoholics Anonymous meetings for physicists: “Yes, it’s been 5 years since my last physics equation. But I’ve been doing neuroscience since then without any relapses.” Let’s just call information our form of “going to meetings.” Take a poll the next time you barge into one of these meetings by accident. Hey, it’s not like they have anything to do in physics these days (give or take a few faster-than-light neutrinos).