MACBETH

Organization:

University of Oklahoma

Dev Category:

Academic

Release Year:

2013

MACBETH w as designed to train intelligence analysts to avoid three cognitive biases that undermine accurate collection, interpretation and fusion of intelligence: fundamental attribution error (FAE), confirmation bias (CB) and bias blind spot (BBS). Players are presented with a fictional scenario of an impending attack. The players must figure out the suspect, location, and the weapon that may be used in the attack while gathering information from multiple sources and forming hypotheses. Throughout the game, players learn about the cognitive biases and receive feedback about their decision making and make them aw are that they are susceptible to biased decision making.

Game Overview

MACBETH w as designed to teach players about three types of cognitive biases: fundamental attribution error (FAE), confirmation bias (CB) and bias blind spot (BBS). Mitigation strategies are built into the game mechanics and feedback to train player on avoiding the three types of cognitive biases in decision making.

The primary goal of MACBETH is to mitigate the cognitive biases of the player. While playing MACBETH, players must formulate and revise hypotheses about a fictional attack. Through the process, the players are challenged with gathering intelligence, comparing multiple information sources to formulate hypotheses about the attack, and avoid cognitive biases that may affect their judgments.

Intelligence Analysts.

Financial performance data is generated for each turn, and players are graded on quality and timeliness for every contract fulfilled for every client. In addition, critical thinking questions are presented to players every turn.

MACBETH

Game Overview

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