Science Plugs Into Prediction Markets
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Transcript of Science Plugs Into Prediction Markets
Science Plugs into Prediction Markets
Over the weekend, Warner Brothers released a science-fiction thriller serendipitously
timed to feed off public fascination with a real-life scientific breakthrough. Biologist
Craig Venter announced May 20, to equal praise and alarm, that he had inserted
synthetic DNA into a living cell.
Then came Adrien Brody on the big screen in Splice. He gets a little reckless splicing
together animal and human DNA — and this is hardly a spoiler alert — he discovers
he can’t control his creation.
“It was an interesting juxtaposition with science and science-fiction,” said David
Rejeski, who directs the Woodrow Wilson Center’s Science and Technology
Innovation Program. As such, the film’s debut offered the ideal opening experiment
for STIP’s latest endeavor: a prediction market for science and technology questions
that range from near-term bureaucratic events (when will the FDA approve the next
oral antibiotic?) to far-off fantasy (who will make the first breakthrough with real
“artificially intelligent” machines?).
In the spirit of the moment, STIP asked its following of science and tech enthusiasts
last week to place a bet with virtual dollars in an online prediction market posing this
question: “How much money will the film ‘Splice’ gross domestically during its
opening weekend?”
B y the time the market “closed,” the leading prediction among several hundred bets
was $5 million to $10 million.
Alas for Adrien Brody — but to the credit of all the people who bet against him —
Splice made a mere $7.5 million at the box office.
STIP’s prediction market is now turning the experiment to more monumental
questions. Which Millennium Prize math problem will be solved next? When will the
total number of known exoplanets reach 500? And as for that real “artificially
intelligent” machine, will the breakthrough come from the entertainment industry,
toy makers, airlines, a random private inventor, government, the auto industry or
academic teams? (The leading opinion, as of Wednesday: academic teams.)
THE IDEA
LOBBY
Miller-McCune's
Washington
correspondent
Emily Badger
follows the ideas
informing,
explaining and
influencing
government, from
the local think tank
circuit to academic
research that
shapes D.C. policy
from afar.
re ct on mar ets aggregate evo v ng op n on n t e same way t e
stock market does (albeit with virtual currency — to use real money
would constitute gambling). They’ve been used with success to
predict elections and to aid businesses in forecasting future events
like stock volumes and new product sales.
The U.S. government has even attempted to apply prediction markets
before, although the lone foray was mostly a PR disaster. In 2003,
the Pentagon tried to set up a market to predict future terrorist
attacks.
“It basically ended up in the news as ‘Pentagon Plans Online Terror
Bets,’” Rejeski recalled. That project was scrapped, and government
has shied away from the idea ever since.
But no one has ever really applied the model to science and
technology questions before. And if the Woodrow Wilson Center
perfects the technique, currently with the help of a grant from the National Science
Foundation, perhaps these tools could be used one day to inform policymakers.
For now, Rejeski is interested less in the predictions themselves than in how to make
the market work.
“The biggest issue for us, and it’s a cutting-edge issue, is can we get people to play in a
science and technology market?” Rejeski said. “If we can’t get them in there, the rest
of this stuff becomes kind of irrelevant.”
The project is building up to a market that will open later this summer specifically
around synthetic biology, one of STIP’s core interests. The emerging discipline draws
on experts who don’t typically work together, from biologists to engineers to
computer scientists. And so a prediction market may be a good place to corral their
expertise.
The field of synthetic biology also lends itself well to the quantifiable questions
necessary to run a prediction market: How many genes can scientists put together?
Can they create a synthetic organism that will allow us to produce hydrogen fuel?
When will that happen?
While people are mulling those questions, Rejeski is trying to answer many of his
own: Can you get people interested in a prediction market when there’s no real
money on the line? Can you identify the people who seem to be better at this than