What Determines Visual Statistical Learning Performance? Insights From Information Theory

In order to extract the regularities underlying a continuous sensory input, the individual elements constituting the stream have to be encoded and their transitional probabilities (TPs) should be learned. This suggests that variance in statistical learning (SL) performance reflects efficiency in encoding representations as well as efficiency in detecting their statistical properties. These processes have been taken to be independent and temporally modular, where first, elements in the stream are encoded into internal representations, and then the co‐occurrences between them are computed and registered. Here, we entertain a novel hypothesis that one unifying construct—the rate of information in the sensory input—explains learning performance. This theoretical approach merges processes related to encoding of events and those related to learning their regularities into a single computational principle. We present data from two large‐scale experiments with over 800 participants tested in support for this hypothesis, showing that rate of information in a visual stream clearly predicts SL performance, and that similar rate of information values leads to similar SL performance. We discuss the implications for SL theory and its relation to regularity learning.     

Diagnosticity,confidence, and the need for information

Recent research has suggested that people prefer to use the most diagnostic available information as the basis for their choices and decisions, and are most confident in those decisions when information is highly diagnostic. However, the effect of information diagnosticity on the need for additional information has yet to be investigated; that is, in an optional stopping task, will the amount of information requested depend upon information diagnosticity? Three models of the role of diagnosticity in information use were examined; expected value, a confidence criterion, and information cost. Subjects attempted to categorize stimuli with the aid of information of varying costs and diagnosticity levels. They requested more information when it was obtained at a low cost. More importantly, across cost conditions, subjects consistently requested greater amounts of information when that information was of a low diagnosticity. These data seem most consistent with use of a confidence criterion that is adjusted for information costs.     

A call for a statement of expectations for the global information infrastructure

This paper considers the relationship between ethics, technology and law, and the roles and limitations each has in this relationship. It argues that ethics has the key role in establishing a resilient, comprehensive and sensitive information infrastructure. It puts forward a Bill of Rights and Responsibilities for the electronic community.

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