Peter M. Todd

Can there ever be too many options? A meta-analytic review of choice overload

The choice overload hypothesis states that an increase in the number of options to choose from may lead to adverse consequences such as a decrease in the motivation to choose or the satisfaction with the finally chosen option. A number of studies found strong instances of choice overload in the lab and in the field, but others found no such effects or found that more choices may instead facilitate choice and increase satisfaction. In a meta‐analysis of 63 conditions from 50 published and unpublished experiments (N = 5,036), we found a mean effect size of virtually zero but considerable variance between studies. While further analyses indicated several potentially important preconditions for choice overload, no sufficient conditions could be identified. However, some idiosyncratic moderators proposed in single studies may still explain when and why choice overload reliably occurs; we review these studies and identify possible directions for future research.

Précis of simple heuristics that make us smart.

How can anyone be rational in a world where knowledge is limited, time is pressing, and deep thought is often an unattainable luxury? Traditional models of unbounded rationality and optimization in cognitive science, economics, and animal behavior have tended to view decision-makers as possessing supernatural powers of reason, limitless knowledge, and endless time. But understanding decisions in the real world requires a more psychologically plausible notion of bounded rationality. In Simple heuristics that make us smart (Gigerenzer et al. 1999), we explore fast and frugal heuristics--simple rules in the minds adaptive toolbox for making decisions with realistic mental resources. These heuristics can enable both living organisms and artificial systems to make smart choices quickly and with a minimum of information by exploiting the way that information is structured in particular environments. In this précis, we show how simple building blocks that control information search, stop search, and make decisions can be put together to form classes of heuristics, including: ignorance-based and one-reason decision making for choice, elimination models for categorization, and satisficing heuristics for sequential search. These simple heuristics perform comparably to more complex algorithms, particularly when generalizing to new data--that is, simplicity leads to robustness. We present evidence regarding when people use simple heuristics and describe the challenges to be addressed by this research program.

Bounding rationality to the world

Simon proposed that human rationality is bounded by both internal (mental) and external (environmental) constraints. Traditionally, these constraints have been seen as independent, leading to a notion of bounded rationality that is either the attempt to do as well as possible given the demands of the world – the notion of optimization under constraints – or as the suboptimal outcome of the limited cognitive system – the realm of cognitive illusions. But there is a third possibility, following Simons original conception: rather than being unrelated, the two sets of bounds may fit together like the blades in a pair of scissors. The mind can take advantage of this fit to make good decisions, by using mental mechanisms whose internal structure exploits the external information structures available in the environment. In this paper we lay out a research program for studying simple decision heuristics of this sort that expands on Simons own search for mechanisms of bounded rationality. We then illustrate how these heuristics can make accurate decisions in appropriate environments, and present detailed examples of two heuristics inspired by Simons ideas on recognition-based processing and satisficing in sequential search. 2003 Elsevier Science B.V. All rights reserved.

Environments That Make Us Smart Ecological Rationality

Traditional views of rationality posit general-purpose decision mechanisms based on logic or optimization. The study of ecological rationality focuses on uncovering the “adaptive toolbox” of domain-specific simple heuristics that real, computationally bounded minds employ, and explaining how these heuristics produce accurate decisions by exploiting the structures of information in the environments in which they are applied. Knowing when and how people use particular heuristics can facilitate the shaping of environments to engender better decisions.

Optimal foraging in semantic memory

Do humans search in memory using dynamic local-to-global search strategies similar to those that animals use to forage between patches in space? If so, do their dynamic memory search policies correspond to optimal foraging strategies seen for spatial foraging? Results from a number of fields suggest these possibilities, including the shared structure of the search problems-searching in patchy environments-and recent evidence supporting a domain-general cognitive search process. To investigate these questions directly, we asked participants to recover from memory as many animal names as they could in 3 min. Memory search was modeled over a representation of the semantic search space generated from the BEAGLE memory model of Jones and Mewhort (2007), via a search process similar to models of associative memory search (e.g., Raaijmakers & Shiffrin, 1981). We found evidence for local structure (i.e., patches) in memory search and patch depletion preceding dynamic local-to-global transitions between patches. Dynamic models also significantly outperformed nondynamic models. The timing of dynamic local-to-global transitions was consistent with optimal search policies in space, specifically the marginal value theorem (Charnov, 1976), and participants who were more consistent with this policy recalled more items.

Fast and frugal food choices: Uncovering individual decision heuristics

Research on food decision making is often based on the assumption that people take many different aspects into account and weight and add them according to their personally assessed importance. Yet there is a growing body of research suggesting that people’s decisions can often be better described by simple heuristics—rules of thumb that people use to make choices based on only a few important pieces of information. To test empirically whether a simple heuristic is able to account for individual food decisions, we ran a computerized experiment in which participants (N ¼ 50) repeatedly chose between pairs of 20 lunch dishes that were sampled from a local food court. A questionnaire assessed individual importance weights as well as evaluation ratings of each lunch dish on nine different factors. Our results show that a simple lexicographic heuristic that only considers each participant’s most important factors is as good at predicting participants’ food choices as a weighted additive model that takes all factors into account. This result questions the adequacy of weighted additive models as sole descriptions of human decision making in the food domain and provides evidence that food choices may instead be based on simple heuristics. r 2007 Elsevier Ltd. All rights reserved.

Made to Measure: Ecological Rationality in Structured Environments

A working assumption that processes of natural and cultural evolution have tailored the mind to fit the demands and structure of its environment begs the question: how are we to characterize the structure of cognitive environments? Decision problems faced by real organisms are not like simple multiple-choice examination papers. For example, some individual problems may occur much more frequently than others, whilst some may carry much more weight than others. Such considerations are not taken into account when (i) the performance of candidate cognitive mechanisms is assessed by employing a simple accuracy metric that is insensitive to the structure of the decision-makers environment, and (ii) reason is defined as the adherence to internalist prescriptions of classical rationality. Here we explore the impact of frequency and significance structure on the performance of a range of candidate decision-making mechanisms. We show that the character of this impact is complex, since structured environments demand that decision-makers trade off general performance against performance on important subsets of test items. As a result, environment structure obviates internalist criteria of rationality. Failing to appreciate the role of environment structure in shaping cognition can lead to mischaracterising adaptive behavior as irrational.

Escaping the tyranny of choice: when fewer attributes make choice easier

In the age of the Internet and easy access to almost infinite information, the problem of information overload among consumers is bound to become of great importance to marketers. By means of simulations we show that this ‘tyranny of choice’ is avoidable. Consumers can neglect most product information and yet make good choices, so long as either there is no conflict among the product attributes or the attributes are unequally important. In these conditions, only one attribute is enough to select a good option - one within ten percent of the highest value possible. We conclude with marketing implications of these findings.

Exploration versus exploitation in space, mind, and society

Search is a ubiquitous property of life. Although diverse domains have worked on search problems largely in isolation, recent trends across disciplines indicate that the formal properties of these problems share similar structures and, often, similar solutions. Moreover, internal search (e.g., memory search) shows similar characteristics to external search (e.g., spatial foraging), including shared neural mechanisms consistent with a common evolutionary origin across species. Search problems and their solutions also scale from individuals to societies, underlying and constraining problem solving, memory, information search, and scientific and cultural innovation. In summary, search represents a core feature of cognition, with a vast influence on its evolution and processes across contexts and requiring input from multiple domains to understand its implications and scope.

Modeling the Perception of Tonal Structure with Neural Nets

ly summarized by the circle of fifths. Analogously, a net exposed to Indian ragas fills in expected tones when presented with subsets of the raga tones. An auto-associative net trained on the scales of one culture can be tested with the scales of another, making predictions about tonal implications 46 Computer Music Journal This content downloaded from 157.55.39.231 on Thu, 06 Oct 2016 04:43:25 UTC All use subject to http://about.jstor.org/terms generated in the minds of listeners hearing an unfamiliar form of music. A net trained on the Western major and minor scales seems to assimilate some Indian ragas to the Western scales, sometimes shifting the tonic (Bharucha and Olney 1989). Learning Hierarchical Representations Through Self-Organization Hierarchical relationships, such as between tones, chords, and keys, can be learned passively by algorithms for self-organization (Kohonen 1984; Linsker 1986; Rumelhart and McClelland 1986; Carpenter and Grossberg 1987). Most self-organization mechanisms assume the prior existence of abstract units into which the input units feed. These abstract units initially have no specialization, since the links from the input units are initially random. However, repeated exposure to commonly occurring patterns causes some of these abstract units to tune their responses to these patterns. One of the more straightforward, self-organization algorithms, called competitive learning (Rumelhart and McClelland 1986) accomplishes this as follows. For any given pattern some arbitrary abstract unit will respond more strongly than any other, simply because the weights are initially random. Of the links that feed into this unit, those that contributed to its activation are strengthened and the others are weakened. This units response will subsequently be even stronger in the presence of this pattern and weaker in the presence of other, dissimilar patterns. In similar fashion, other abstract units learn to specialize to other patterns. This process can be continued to even more abstract layers, at which units become tuned to patterns that commonly occur in the lower layer. The overwhelming preponderance of major and minor chords in the popular Western musical environment would drive such a net to form units that respond accordingly. Furthermore, the typical combinations in which these chords are used would drive units at a more abstract layer to register larger organizational units such as keys. The notion that individual neurons specialize to respond to complex auditory patterns has some preliminary empirical support from single-cell recording studies on animals (Weinberger and McKenna 1988). Once these chord and key units have organized themselves, the net models the implication of tones, chords, and keys given a set of tones. A hierarchical constraint satisfaction net built on this organization has been reported in earlier work (Bharucha 1987a; 1987b). In this net, called MUSACT, activation spreads from tone units to chord and key units and reverberates phasically through the net until a state of equilibrium is achieved. At equilibrium, all constraints inherent in the net have been satisfied. Given a key-instantiating context, the unit representing the tonic becomes the most highly activated. The other chord units are activated to lesser degrees the further they are from the tonic along the circle of fifths. Two behaviors of the net illustrate its emergent properties. First, the above activation pattern does not require the tonic chord to be played at all. An F major chord followed by a G major chord will cause the C major chord unit to be the most highly activated. Second, the circle of fifths implicit in the activation pattern cannot be accounted for on the basis of shared tones alone. If a C major context chord is played, the D major chord unit is more highly activated than the A major chord unit, even though the latter shares one tone with the sounded chord (C major) and the former shares none at all. A careful tracking of the nets behavior as activation reverberates and before it converges to an equilibrium state reveals a lower initial activiation of D major over A major, reflecting an initial bottom-up influence of shared tones. As activation has a chance to reverberate back from the key units (a top-down influence), this advantage is lost, and D major overtakes A major. So the circle of fifths is truly an emergent property of the simultaneous satisfaction of elementary associations between tones and clusters of tones. See Bharucha (1987a; 1987b) for details. Learning With Sequential Nets Some of the schematic expectancies that are essentially sequential, as in chord progressions, can be modeled with sequential nets. The architecture