Government Computer News has a brief article about the ACE program. It focuses mainly on Applied Research Associates' Forecasting Ace, but it still gives a good overview of what the program is trying to achieve.

Johns Hopkins neuroscientist David Linden explains "the brain science behind gambling with the debt ceiling" on Reuters' Great Debate blog. It draws on, among other things, Barbara Mellers' work investigating how circumstances affect how people assess financial gains and losses.

The debt ceiling debate is raging in Washington. But what’s going on in the minds of the politicians working on the seemingly intractable problem? Barack Obama, Mitch McConnell, John Boehner and Eric Cantor are all taking calculated risks — bets — that they can win the standoff and get more out of the deal than the other side can. Their strategies are rooted in their political beliefs and theories on how government should operate, but their tactics come from the part of the brain that covets social acceptance and individual rewards.

Hans Breiter and his coworkers addressed these issues in some clever in human brain scanning experiments. Initially each subject received an account containing $50 worth of credit. They were instructed that they were working with real money and that they would be paid the balance of their account in cash at the end of the experiment. In the brain scanner, they watched a video screen that showed one of three wheels, each of which was divided into three pie-shaped segments labeled with a monetary outcome. The “bad” wheel had only negative or neutral outcomes (-$6.00, -$1.50, or $0), an “intermediate” one had mixed results (+$2.50, -$1.50, $0), and a final “good” wheel primarily had rewards (+$10.00, +$2.50, $0). After a particular wheel type was presented on the screen, the subject would push a button that would initiate rotation of an animated pointer. The pointer would spin for about five seconds and then come to rest, seemingly randomly, on one of the three possible outcomes, where it would remain for five more seconds.

The design of this experiment makes it possible to measure brain activation during both an anticipation phase (while the pointer is spinning) and an outcome phase (after the pointer has stopped). Of course, the software running the pointer is controlled by the experimenters so that it can deliver all of the possible monetary outcomes in a balanced manner.

The main finding was that key regions of the brain’s pleasure circuit were activated during both the anticipation phase and the outcome phase, when the outcomes were positive. The anticipation phase responses were graded according to the possible outcome: There was greater activity while the “good” wheel’s pointer was spinning than when that of the “intermediate” or “bad” wheel. And finally, during the outcome phase with the “good” wheel, greatest activation was seen for the largest monetary rewards. Thus even anticipation and experience of an abstract reward, like money, can activate the human pleasure circuit—we’re hardwired to catch a buzz of gambling and to catch the biggest buzz when the most is at stake.

This experiment was also designed to test another hypothesis about monetary reward in gambling. Using a related task, Barbara Mellers and coworkers demonstrated that people regard a $0 outcome on the “good” wheel as a loss but a $0 outcome on the “bad” wheel as a win. If our minds were completely rational, we would value these outcomes the same way, but we don’t. We are influenced by the counterfactual possibility of “what might have been.” Was this irrational belief reflected in brain activation? The response strength to the $0 outcome on the “good” wheel was lower than that for the “bad” wheel. However, the responses to the $0 outcome on the “intermediate” wheel did not fall between the levels for the good and the bad $0 responses, as would be predicted. The theory that counterfactual comparison modulates brain pleasure circuit activation is therefore possible, but remains unproven.

Jon Baron points out a new article on widening subjective confidence intervals:

Subjective probabilistic judgments are inevitable in many real life domains. A common way to obtain such judgments is to assess fractiles or confidence intervals. However, such judgments tend to be systematically overconfident. For example, 90% confidence intervals for future uncertain quantities (e.g., future stock prices) are likely to capture only 50-60% of the actual realizations. Furthermore, it has proved particularly difficult to de-bias forecasts and improve the calibration of expressed subjective uncertainty. This paper proposes a simple process that systematically leads to wider assessed confidence intervals than is normally the case, thus potentially improving calibration and hence reducing overconfidence. Using a series of lab and field experiments with professionals forecasting in their domain of expertise, we show that unpacking the distal future into intermediate more proximal futures has a substantial effect on subjective forecasts. For example, simply making it salient that between now and three months from now there is one month from now and two months from now increases the uncertainty assessors have in their three month forecasts, which helps mitigate the overconfidence in those forecasts. We refer to this phenomenon as the time unpacking effect and find that it is robust to different elicitation formats. We also address the possible reasons for the time unpacking effect and propose future research directions.