Model-Based Wisdom of the Crowd for Sequential Decision-Making Tasks

We study the wisdom of the crowd in three sequential decision-making tasks: the Balloon Analogue Risk Task (BART), optimal stopping problems, and bandit problems. We consider a behavior-based approach, using majority decisions to determine crowd behavior and show that this approach performs poorly in the BART and bandit tasks. The key problem is that the crowd becomes progressively more extreme as the decision sequence progresses, because the diversity of opinion that underlies the wisdom of the crowd is lost. We also consider model-based approaches to each task. This involves inferring cognitive models for each individual based on their observed behavior, and using these models to predict what each individual would do in any possible task situation. We show that this approach performs robustly well for all three tasks and has the additional advantage of being able to generalize to new problems for which there are no behavioral data. We discuss potential applications of the model-based approach to real-world sequential decision problems and discuss how our approach contributes to the understanding of collective intelligence.     

How Attention Partitions Itself During Simultaneous Message Presentations

Television producers, across all types of programming, assume young viewers can parallel process simultaneously presented messages. For instance, television news producers appear to believe that young viewers can attend to weather icons, lexical news crawls, and sports scores while they also attend to news anchors who present the news. Nonetheless, attention theory suggests parallel processing on this scale cannot be executed efficiently. Given the format's popularity, perhaps those messages take advantage of perceptual grouping, as described by Treisman, Kahneman, and Burkell (1983). Perceptual grouping describes a process where separate but semantically related messages are attended to simultaneously with minimal effort. Using secondary task methodology, we measured participants' attentional capacity while they watched an example of this format: CNN's Headline News. In addition to this visually complex condition, we created a visually simple condition by deleting graphics and news crawls. Participants in this latter condition attended to both the auditory and visual channels, thus retaining story facts conveyed by both channels. Participants in the complex condition, however, shifted attention to the auditory channel. Ten percent of the factual information contained in news stories was lost to participants. It appears that this multimessage format exceeded viewers' attentional capacity. In conclusion, we discuss the implications for attention theory.