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1. Uncovering the computational mechanisms underlying many-alternative choice

   https://doi.org/10.7554/eLife.57012  

   Thomas, Armin W; Molter, Felix; Krajbich, Ian (April 2021, eLife)

   null (Ed.)

   In our everyday lives, we often have to choose between many different options. When deciding what to order off a menu, for example, or what type of soda to buy in the supermarket, we have a range of possibilities to consider. So how do we decide what to go for? Researchers believe we make such choices by assigning a subjective value to each of the available options. But we can do this in several different ways. We could look at every option in turn, and then choose the best one once we have considered them all. This is a so-called ‘rational’ decision-making approach. But we could also consider each of the options one at a time and stop as soon as we find one that is good enough. This strategy is known as ‘satisficing’. In both approaches, we use our eyes to gather information about the items available. Most scientists have assumed that merely looking at an item – such as a particular brand of soda – does not affect how we feel about that item. But studies in which animals or people choose between much smaller sets of objects – usually up to four – suggest otherwise. The results from these studies indicate that looking at an item makes that item more attractive to the observer, thereby increasing its subjective value. Thomas et al. now show that gaze also plays an active role in the decision-making process when people are spoilt for choice. Healthy volunteers looked at pictures of up to 36 snack foods on a screen and were asked to select the one they would most like to eat. The researchers then recorded the volunteers’ choices and response times, and used eye-tracking technology to follow the direction of their gaze. They then tested which of the various decision-making strategies could best account for all the behaviour. The results showed that the volunteers’ behaviour was best explained by computer models that assumed that looking at an item increases its subjective value. Moreover, the results confirmed that we do not examine all items and then choose the best one. But neither do we use a purely satisficing approach: the volunteers chose the last item they had looked at less than half the time. Instead, we make decisions by comparing individual items against one another, going back and forth between them. The longer we look at an item, the more attractive it becomes, and the more likely we are to choose it. 

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2. The Commonness Fallacy: Commonly Chosen Options Have Less Choice Appeal Than People Think

   https://doi.org/10.1037/pspa0000172  

   Reit, E.; Critcher, C. R. (January 2020, Journal of personality and social psychology)

   In predicting what others are likely to choose (e.g., vanilla ice cream or tiramisu), people can display a commonness fallacy—overestimating how often common (but bland) options (e.g., vanilla ice cream) will be chosen over rarer (but exciting) options (e.g., tiramisu). Given common items are often chosen merely because they are frequently offered, not because they are preferred (tiramisu is rarely offered as a dessert), commonness is not necessarily diagnostic of future choice. Studies 1a and 1b document the commonness fallacy in forecasts of single and repeated choices. Study 2 replicates it in an incentivecompatible choice context. Studies 3 and 4 uncover when and why perceived commonness is relied upon. Perceived commonness is spontaneously used as a guide when forecasting others’ choices (as though people blur what has been chosen with what people will choose), but not when forecasting what others would be pleased to receive. Choice forecasters leaned upon perceived commonness over and above many other cues, including their own choices, the goods’ prices, and even how much others were thought to like each option. Upon conscious reflection, choice forecasters abandon commonness and gravitate toward more normatively defensible input. Studies 5 and 6 used correlational and experimental methods, respectively, to examine antecedents of the commonness fallacy. Study 7 illustrates a literally costly consequence: A 2-part marketplace simulation study found amateur sellers’ reliance on perceived commonness prompted them to systematically misprice goods. 

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3. Valuations of target items are drawn towards unavailable decoy items due to prior expectations

   https://doi.org/10.1093/pnasnexus/pgae232  

   Izakson, Liz; Yoo, Minhee; Hakim, Adam; Krajbich, Ian; Webb, Ryan; Levy, Dino_J; Tserenjigmid, ed., Gerelt (June 2024, PNAS Nexus)

   Abstract When people make choices, the items they consider are often embedded in a context (of other items). How this context affects the valuation of the specific item is an important question. High-value context might make items appear less attractive because of contrast—the tendency to normalize perception of an object relative to its background—or more attractive because of assimilation—the tendency to group objects together. Alternatively, a high-value context might increase prior expectations about the item's value. Here, we investigated these possibilities. We examined how unavailable context items affect choices between two target items, as well as the willingness-to-pay for single targets. Participants viewed sets of three items for several seconds before the target(s) were highlighted. In both tasks, we found a significant assimilation-like effect where participants were more likely to choose or place a higher value on a target when it was surrounded by higher-value context. However, these context effects were only significant for participants’ fastest choices. Using variants of a drift-diffusion model, we established that the unavailable context shifted participants’ prior expectations towards the average values of the sets but had an inconclusive effect on their evaluations of the targets during the decision (i.e. drift rates). In summary, we find that people use context to inform their initial valuations. This can improve efficiency by allowing people to get a head start on their decision. However, it also means that the valuation of an item can change depending on the context. 

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4. Wardrobe Model for Long Term Re-identification and Appearance Prediction

   https://doi.org/10.1109/AVSS.2018.8639157  

   Lee, Kyung Won; Sankaran, Nishant; Setlur, Srirangaraj; Napp, Nils; Govindaraju, Venu (November 2018, 2018 15th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS))

   Long-term surveillance applications often involve having to re-identify individuals over several days or weeks. The task is made even more challenging with the lack of sufficient visibility of the subjects faces. We address this problem by modeling the wardrobe of individuals using discriminative features and labels extracted from their clothing information from video sequences. In contrast to previous person re-id works, we exploit that people typically own a limited amount of clothing and that knowing a person's wardrobe can be used as a soft-biometric to distinguish identities. We a) present a new dataset consisting of more than 70,000 images recorded over 30 days of 25 identities; b) model clothing features using CNNs that minimize intra-garments variations while maximizing inter-garments differences; and c) build a reference wardrobe model that captures each persons set of clothes that can be used for re-id. We show that these models open new perspectives to long-term person re-id problem using clothing information. 

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5. Assessment of two brands of fentanyl test strips with 251 synthetic opioids reveals “blind spots” in detection capabilities

   https://doi.org/10.1186/s12954-023-00911-w  

   Hayes, Kathleen L.; Lieberman, Marya (December 2023, Harm Reduction Journal)

   Abstract BackgroundFentanyl test strips (FTS) are a commonly deployed tool in drug checking, used to test for the presence of fentanyl in street drug samples prior to consumption. Previous reports indicate that in addition to fentanyl, FTS can also detect fentanyl analogs like acetyl fentanyl and butyryl fentanyl, with conflicting reports on their ability to detect fentanyl analogs like Carfentanil and furanyl fentanyl. Yet with hundreds of known fentanyl analogs, there has been no large-scale study rationalizing FTS reactivity to different fentanyl analogs. MethodsIn this study, 251 synthetic opioids—including 214 fentanyl analogs—were screened on two brands of fentanyl test strips to (1) assess the differences in the ability of two brands of fentanyl test strips to detect fentanyl-related compounds and (2) determine which moieties in fentanyl analog chemical structures are most crucial for FTS detection. Two FTS brands were assessed in this study: BTNX Rapid Response and WHPM DanceSafe. ResultsOf 251 screened compounds assessed, 121 compounds were detectable at or below 20,000 ng/mL by both BTNX and DanceSafe FTS, 50 were not detectable by either brand, and 80 were detectable by one brand but not the other (n = 52 BTNX,n = 28 DanceSafe). A structural analysis of fentanyl analogs screened revealed that in general, bulky modifications to the phenethyl moiety inhibit detection by BTNX FTS while bulky modifications to the carbonyl moiety inhibit detection by DanceSafe FTS. ConclusionsThe different “blind spots” are caused by different haptens used to elicit the antibodies for these different strips. By utilizing both brands of FTS in routine drug checking, users could increase the chances of detecting fentanyl analogs in the “blind spot” of one brand. 

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