“We have shown that by applying tools from neuroscience to the public-goods problem, we can get solutions that are significantly better than those that can be obtained without brain data,” says Antonio Rangel, associate professor of economics at Caltech and the paper’s principal investigator.

Here is the paper.  You should read it.  It is forthcoming in Science. Zuchetto Zip goes to Economists’ View.

The public goods aspect of the problem is not important for understanding the main result here, so here is a simplified way to think about it.  You are secretly told a number (in the public goods game this number is your willingness to pay) and you are asked to report your number.  You have a monetary incentive to lie and report a number that is lower than the one you were told. But now you are placed in a brain scanner and told that the brain scanner will collect information that will be fed into an algorithm that will try to guess your number.  And if your report is different from the guess, you will be penalized.

The result is that subjects told the truth about their number.  This is a big deal but it is important to know exactly what the contribution is here.

  1. The researchers have not found a way to read your mind and find out your number.  Indeed, even under the highly controlled experimental conditions where the algorithm knows that your number is one of two possible numbers and after doing 50 treatments per subject and running regressions to improve the algorithm, the prediction made by the algorithm is scarcely better than a random guess.  (See table S3)
  2. In that sense “brain data” is not playing any real role in getting subjects to tell the truth.  Instead, it is the subjects’ belief that the scanner and algorithm will accurately predict their value which induces them to tell the truth.  Indeed after conducting the experiment the researchers could have thrown away all of their brain data and just randomly given out payments and this would not have changed the result as long as the subjects were expecting the brain data to be used.
  3. The subjects were clearly mistaken about how good the algorithm would be at predicting their values.
  4. Therefore, brain scans as incentive mechanisms will have to wait until neuroscientists really come up with a way of reading numbers from your brain.
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