Do humans make good decisions?

Summerfield, Christopher; Tsetsos, Konstantinos

doi:10.1016/j.tics.2014.11.005

Cited by 137 publications

(149 citation statements)

References 57 publications

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“…In our analyses, however, we assumed that such direct and unbounded gain amplification is not plausible because organisms operate within computational and metabolic constraints (33). Due to these constraints, even under conditions of increased vigilance behavioral and neural variability perseveres (34), indicating that a portion of internal noise is virtually irreducible.…”

Section: Discussionmentioning

confidence: 99%

Economic irrationality is optimal during noisy decision making

Tsetsos

Moran

Moreland

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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According to normative theories, reward-maximizing agents should have consistent preferences. Thus, when faced with alternatives A, B, and C, an individual preferring A to B and B to C should prefer A to C. However, it has been widely argued that humans can incur losses by violating this axiom of transitivity, despite strong evolutionary pressure for reward-maximizing choices. Here, adopting a biologically plausible computational framework, we show that intransitive (and thus economically irrational) choices paradoxically improve accuracy (and subsequent economic rewards) when decision formation is corrupted by internal neural noise. Over three experiments, we show that humans accumulate evidence over time using a "selective integration" policy that discards information about alternatives with momentarily lower value. This policy predicts violations of the axiom of transitivity when three equally valued alternatives differ circularly in their number of winning samples. We confirm this prediction in a fourth experiment reporting significant violations of weak stochastic transitivity in human observers. Crucially, we show that relying on selective integration protects choices against "late" noise that otherwise corrupts decision formation beyond the sensory stage. Indeed, we report that individuals with higher late noise relied more strongly on selective integration. These findings suggest that violations of rational choice theory reflect adaptive computations that have evolved in response to irreducible noise during neural information processing.decision making | irrationality | choice optimality | selective integration | evidence accumulation D aily decisions, such as choosing a holiday destination or accepting a job offer, involve comparing alternatives that are characterized by different attributes (1, 2). Understanding how the brain combines information from different attributes into unitary decision values is a key challenge in psychology and the neurosciences (3, 4). From a normative perspective, the value of an alternative should be independent of factors, such as the attractiveness of competing alternatives or the context in which preferences are elicited (5). Thus, the preference relationship between two alternatives ought to remain stable, regardless of changes to the choice set, incurred for example by the addition or removal of other choice alternatives (6).However, human preferences are often driven by irrelevant factors (7,8). For instance, an initial preference for one holiday destination (e.g., Bali) over another (e.g., Berlin) can reverse when an inferior alternative (e.g., Dresden) is added to the choice set, even if this "decoy" alternative is never chosen (9, 10). Similarly, an individual preferring a holiday in Bali to Berlin, and Berlin to Boston, will sometimes show a systematic "intransitive" (or inconsistent) preference for Boston over Bali (11). A canonical argument states that such violations of decision theory (hereafter "economic" or "choice irrationality") disclose fundamental limita...

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Section: Discussionmentioning

confidence: 99%

Economic irrationality is optimal during noisy decision making

Tsetsos

Moran

Moreland

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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133

186

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“…We chose the stochastic normalized utility function defined in Equation 16 because of its neuroscientific underpinnings and its ability to explain context-sensitive preferences in valuebased decision-making (Summerfield & Tsetsos, 2015). Concretely, UWS combined with a context-insensitive utility function, such as a simple linear function of the outcome, or the concave utility function of prospect theory, would be unable to explain why people's preference for the risky gamble +40/0 over the safe option +20 is lower in Experiment 3 than in Experiment 1 even though the choices are exactly the same.…”

Section: Overweighting Of Extreme Events In Decisions From Experiencementioning

confidence: 99%

“…We chose it because it is the simplest instantiation of the efficient coding theory proposed by Summerfield and Tsetsos (2015) that captures our findings. It thus remains to be validated independently.…”

Section: Limitations and Future Workmentioning

confidence: 99%

“…To do so, we interpret an outcome's utility as the subjective value that the decision-maker's brain assigns to OVER-REPRESENTATION OF EXTREME EVENTS 10 it in the choice context. Concretely, we follow the proposal of Summerfield and Tsetsos (2015) that the brain represents value in an efficient neural code. This proposal is based on psychophysical and neural data (Louie, Grattan, & Glimcher, 2011;Louie, Khaw, & Glimcher, 2013;Mullett & Tunney, 2013) …”

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confidence: 99%

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Over-representation of extreme events in decision-making reflects rational use of cognitive resources

Lieder¹,

Griffiths²,

Hsu³

2016

Preprint

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People's decisions and judgments are disproportionately swayed by improbable but extreme eventualities, such as terrorism, that come to mind easily. This article explores whether such availability biases can be reconciled with rational information processing by taking into account the fact that decisionmakers value their time and have limited cognitive resources. Our analysis suggests that to make optimal use of their finite time decision-makers should over-represent the most important potential consequences relative to less important, put potentially more probable, outcomes. To evaluate this account we derive and test a model we call utility-weighted sampling. Utility-weighted sampling estimates the expected utility of potential actions by simulating their outcomes. Critically, outcomes with more extreme utilities have a higher probability of being simulated. We demonstrate that this model can explain not only people's availability bias in judging the frequency of extreme events but also a wide range of cognitive biases in decisions from experience, decisions from description, and memory recall. Keywords: judgment and decision-making; bounded rationality; cognitive biases; heuristics; probabilistic models of cognition Human judgment and decision making have been found to systematically violate the axioms of logic, probability theory, and expected utility theory (Tversky & Kahneman, 1974). These violations are known as cognitive biases and are assumed to result from people's use of heuristics -simple and efficient cognitive strategies that work well for certain A preliminary version of our simulations of decisions from description was presented at the 36th Annual Meeting of the Cognitive Science Society and appeared in the conference proceedings. This work has been updated and extended for inclusion in the current manuscript.We are grateful to Sam Gershman, Elliot Ludvig, Christopher Madan, Marta Kryven, Ido Erev, Nisheeth Srivastava, Thomas Icard, and Phoebe Lin for their helpful pointers, discussion, and assistance.OVER-REPRESENTATION OF EXTREME EVENTS 2 problems but fail on others. While some have interpreted the abundance of cognitive biases as a sign that people are fundamentally irrational (Ariely, 2009;Marcus, 2009;Sutherland, 1992;McRaney, 2011) others have argued that people appear irrational only because their reasoning has been evaluated against the wrong normative standards (Oaksford & Chater, 2007), that the heuristics giving rise to these biases are rational given the structure of the environment (Simon, 1956;Todd & Gigerenzer, 2012), or that the mind makes rational use of limited cognitive resources (Simon, 1956;Griffiths, Lieder, & Goodman, 2015;Wiederholt, 2010;Dickhaut, Rustichini, & Smith, 2009).One of the first biases interpreted as evidence against human rationality is the availability bias (Tversky & Kahneman, 1973): people overestimate the probability of events that come to mind easily. This bias violates the axioms of probability theory. It leads people to overestimate the frequen...

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“…Similarly, perceptual decisions are prone to deviate from the veridical as seen in phenomena such as sensory illusions (7,25). Recent theoretical work has suggested that these "biases" reflect humans' ability to deal with the uncertainties in the world using the probabilistic structure of the environment (26,27). Therefore, seemingly erroneous judgments are not only very common in the course of evolution (28) but are also optimal and rational (29)(30)(31).…”

Section: Fig 2 (A)mentioning

confidence: 99%

Receipt of reward leads to altered estimation of effort

Pooresmaeili

Wannig²,

Dolan

2015

Proc. Natl. Acad. Sci. U.S.A.

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Effort and reward jointly shape many human decisions. Errors in predicting the required effort needed for a task can lead to suboptimal behavior. Here, we show that effort estimations can be biased when retrospectively reestimated following receipt of a rewarding outcome. These biases depend on the contingency between reward and task difficulty and are stronger for highly contingent rewards. Strikingly, the observed pattern accords with predictions from Bayesian cue integration, indicating humans deploy an adaptive and rational strategy to deal with inconsistencies between the efforts they expend and the ensuing rewards.Aye, and I saw Sisyphus in violent torment, seeking to raise a monstrous stone with both his hands.Homer, Book XI of The Odyssey T he adage "it was well worth the effort" highlights an assumed interdependency between attainment of reward and retrospective effort assignment. Despite its ubiquity we know little about the nature of these retrospective effort estimations. Previous studies have focused on the interaction of effort and reward as costs and benefits when a choice is to be made (1-5). Whether receipt of reward influences a retrospective estimation of effort is not known. Intuitively, we assume to have immediate and unbiased access to internal representations of how much "effort" we expended in an endeavor. Here, we demonstrate that retrospective estimation of effort is strongly affected by the amount of monetary reward attained and, as such, is profoundly biased. This bias adheres to established principles of Bayesian cue integration (6-8) and, on this basis, is not irrational.In a behavioral experiment, participants pressed two buttons on a keyboard to push a ball up a virtual ramp and rated their experienced physical effort in each trial ( Fig. 1; see also SI Materials and Methods for additional information regarding the task). The ball rolled back by a constant amount on each frame of the display, hence simulating a gravity force that varied so as to manipulate task difficulty (n = 6 difficulty levels, adjusted individually for each participant). Successful trials where participants managed to push the ball all of the way up the ramp were rewarded. Reward was contingent upon task difficulty (with values drawn from six Gaussian distributions with means from 1.5 to 6.5 cents) and the strength of this contingency varied across different blocks of the experiment (SDs of 1.2 or 2.5 cents). Additionally, we included a control experiment in which reward receipt was unrelated to task difficulty (SD = ∞).The reward information was presented either before or after the rating of effort (in 90% and 10% of trials, respectively). Trials in which reward was shown after the estimation of effort served as a reference, because here subjects are not influenced by preceding reward information. Participants were instructed to pay attention to all information presented in a trial, including a brief color change of the ball (50% of the trials), which they needed to detect on each trial. This manipulation was...

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Do humans make good decisions?

Cited by 137 publications

References 57 publications

Economic irrationality is optimal during noisy decision making

Economic irrationality is optimal during noisy decision making

Over-representation of extreme events in decision-making reflects rational use of cognitive resources

Receipt of reward leads to altered estimation of effort

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