MACBETH,
developed by the University of Oklahoma (OU), is the
winner of both the “Best Business Game” and “Best Game Special Emphasis
Adaptive Force Award” (judged by the Office of the Secretary of Defense among
others), two of the seven award categories of the Serious Games Showcase &
Challenge, at I/ITSEC 2013 hold last week in Orlando, Fl.
MACBETH,
which stands for Mitigating Analyst Cognitive Bias by Eliminating Task
Heuristics, is a Serious Game created to train intelligence analysts and
measure their proficiency in recognizing and mitigating the cognitive biases that
affect intelligence analysis.
The objective of the game is to improve accuracy of
credibility assessments, working as a learning system where players must
counteract threats to American interests by using the intelligence data at hand
without allowing their cognitive biases to cloud their judgment.
The game simulates a crime investigation, giving players
a group of suspects and information to help decide who committed the crime. The
player guides agents as they collect information, and then decides whether that
information was affected by certain types of cognitive bias.
Through gameplay, the system will highlight the use
of a bias, then provide the player with information on and opportunities to
practice bias mitigation techniques based on the theoretical model, the
Heuristic-Systematic Model of information processing.
The game is designed to test players for three
kinds of bias: anchoring bias, projection bias and representativeness bias. Anchoring
bias causes the player to rely too heavily on the first piece of information he
or she receives. Projection bias is a case where the player projects his or her
own thought patterns onto another person, assuming they will be the same. A
player operating under representativeness bias might judge an individual person
based on stereotypes about a larger group.
The uniqueness of MACBETH approach can be
experienced at the different challenge levels as players collect information,
review Intel and formulate hypothesis: game goal can only be achieved if
players take cognitive biases out of the equation and make better decisions.
Norah Dunbar, associate professor in the OU
Department of Communication and the Center for Applied Social Research, and the
primary investigator responsible for project oversight, says the team
modeled MACBETH after the game “Clue” because it is familiar
to most people. With MACBETH, players spend less time learning the
game and more time solving the problem. Like Clue, MACBETH
gives player(s) a group of suspects to choose from and clues that help the
player decide who has committed the crime. Mentors guide a player by
providing insight as to what a player did wrong.
The game is already getting interest from several
federal agencies.
Although MACBETH was designed with the
intelligence community in mind, Dunbar said the same model could be used in
other areas. For example, it could be useful for making medical students aware
of their biases when diagnosing patients. “I think it's pretty
broadly applicable,” she added.
Game
Background
The OU team
was one of six teams selected to create a video game for the Air Force Research
Laboratory in support of the Intelligence Advanced Research Projects Activity
(IARPA), the federal agency that funds research and development for the
intelligence field.
The agency
was interested in developing a program that helped mitigate the kinds of
cognitive bias that were most problematic in the intelligence community. After
developing the first version of the game, Dunbar's team tested it on a group of
undergraduates. One group played the game, while another group watched a video
about cognitive bias. A total of 2,000 subjects were tested both at OU and the
University of Arizona.
When
researchers gave the participants a follow-up exam on cognitive bias eight
months later, the students who had played the game had retained the information
better than those who had watched the video.