[youtube width=”520″ height=”270″]http://www.youtube.com/watch?v=dtNMA46YgX4[/youtube]
Supporters of the Big Data movement argue that data will change everything, but only once we break down the institutional and technological barriers that prevent us from getting at it. In his talk at TEDMED 2012 at the Kennedy Center, Stanford’s Atul Butte argues that the we already have more than enough to do real science, if only we know where to look.
A recurring them on this blog is the need for empowered, engaged patients to understand what they read about science. It’s true when researching treatments for one’s condition, it’s true when considering government policy proposals, it’s true when reading advice based on statistics. If you take any journal article at face value, you may get severely misled; you need to think critically.
Sometimes there’s corruption (e.g. the fraudulent vaccine/autism data reported this month, or “Dr. Reuben regrets this happened“), sometimes articles are retracted due to errors (see the new Retraction Watch blog), sometimes scientists simply can’t reproduce a result that looked good in the early trials.
But an article a month ago in the New Yorker sent a chill down my spine tonight. (I wish I could remember which Twitter friend cited it.) It’ll chill you, too, if you believe the scientific method leads to certainty. This sums it up:
Many results that are rigorously proved and accepted start shrinking in later studies.
This is disturbing. The whole idea of science is that once you’ve established a truth, it stays put: you don’t combine hydrogen and oxygen in a particular way and sometimes you get water, and other times chocolate cake.
Reliable findings are how we’re able to shoot a rocket and have it land on the moon, or step on the gas and make a car move (predictably), or flick a switch and turn on the lights. Things that were true yesterday don’t just become untrue. Right??
Bad news: sometimes the most rigorous published findings erode over time. That’s what the New Yorker article is about.
I won’t try to teach here everything in the article; if you want to understand research and certainty, read it. (It’s longish, but great writing.) I’ll just paste in some quotes. All emphasis is added, and my comments are in [brackets].