Evidence accumulation is biased by motivation: A computational account

Abstract

To make good judgments people gather information. An important problem an agent needs to solve is when to continue sampling data and when to stop gathering evidence. We examine whether and how the desire to hold a certain belief influences the amount of information participants require to form that belief. Participants completed a sequential sampling task in which they were incentivized to accurately judge whether they were in a desirable state, which was associated with greater rewards than losses, or an undesirable state, which was associated with greater losses than rewards. While one state was better than the other, participants had no control over which they were in, and to maximize rewards they had to maximize accuracy. Results show that participants’ judgments were biased towards believing they were in the desirable state. They required a smaller proportion of supporting evidence to reach that conclusion and ceased gathering samples earlier when reaching the desirable conclusion. The findings were replicated in an additional sample of participants. To examine how this behavior was generated we modeled the data using a drift-diffusion model. This enabled us to assess two potential mechanisms which could be underlying the behavior: (i) a valence-dependent response bias and/or (ii) a valence-dependent process bias. We found that a valence-dependent model, with both a response bias and a process bias, fit the data better than a range of other alternatives, including valence-independent models and models with only a response or process bias. Moreover, the valence-dependent model provided better out-of-sample prediction accuracy than the valence-independent model. Our results provide an account for how the motivation to hold a certain belief decreases the need for supporting evidence. The findings also highlight the advantage of incorporating valence into evidence accumulation models to better explain and predict behavior.

Dynamic Representation of the Subjective Value of Information

“…This prediction might be somewhat counterintuitive, as the motivation for information seeking is expected to be higher when the current evidence favors the less desirable state (the low-reward jar). However, it is consistent with the widespread notion of confirmation bias that an agent needs less evidence to bet on a desirable state than an undesirable state (e.g., Gesiarz et al, 2019). More generally, the prediction echoes the general assumption that information seeking should be driven not by the motivation to predict the state (which jar is the true jar?)…”

“…Our theoretical and behavioral findings may provide some insight into confirmation biases observed across domains. Confirmation bias is commonly framed as biases in updating processes and/or decision criteria due to reward asymmetry or other factors such as pre-commitment (Gesiarz et al, 2019; Leong et al, 2019; Luu & Stocker, 2018; Talluri et al, 2018). We showed that, even without biases in updating or decision criteria, information seeking should be biased by reward asymmetry.…”

Dogmatism manifests in lowered information search under uncertainty

“…This research indicates that people prefer to seek information that confirms their beliefs and has positive valence, as when we read an additional news story about the victory of a favored political party. This type of motivated search is evident both in laboratory experiments ( 9 – 11 ) and in real-world data ( 12 – 14 ).…”

Children perform extensive information gathering when it is not costly

“…In recent years, cognitive neuroscience has started to reveal the mechanisms underlying information gathering and how healthy adults solve this challenge. A key finding is that humans dynamically adjust their decision criteria depending on how long they have been sampling, and not necessarily based on explicit objective sampling costs ( Bogacz, Wagenmakers, Forstmann, & Nieuwenhuis, 2010 ; Gesiarz, Cahill, & Sharot, 2019 ; Hauser, Moutoussis, Iannaccone, et al, 2017 ; Ma, Sanfey, & Ma, 2019 ; Malhotra, Leslie, Ludwig, & Bogacz, 2017 ; Thura, Cos, Trung, & Cisek, 2014 ). This behaviour is evidence for subjective sampling costs that increase as more information is gathered, rendering a long information sampling process unattractive.…”