The presence of irrelevant alternatives paradoxically increases confidence in perceptual decisions

Confidence in perceptual decisions often reflects the probability of being correct. Hence, we predicted that confidence should be unaffected or be minimally decreased by the presence of irrelevant alternatives. To test this prediction, we designed three experiments. In Experiment 1, participants had to identify the largest geometrical shape among two or three alternatives. In the three-alternative condition, one of the shapes was much smaller than the other two, being a clearly incorrect choice. Counter-intuitively, all else being equal, confidence was higher when the irrelevant alternative was present. We accounted for this effect with a computational model where confidence increases monotonically with the number of irrelevant alternatives, a prediction we confirmed in Experiment 2. In Experiment 3, we evaluated whether this effect replicated in a categorical task, but we did not find supporting evidence. Our findings stimulate the use of multi-alternative decision-making tasks to build a thorough understanding of confidence.

Underweighting of rare events in social interactions and its implications to the design of voluntary health applications

Research on small decisions from experience suggests that people often behave as if they underweight rare events and choose the options that are frequently better. In a pandemic, this tendency implies complacency and reckless behavior. Furthermore, behavioral contagion exacerbates this problem. In two pre-registered experiments (Ntotal = 312), we validate these predictions and highlight a potential solution. Groups of participants played a repeated social game in one of two versions. In the basic version, people clearly preferred the dangerous reckless behavior that was better most of the time over the safer responsible behavior. In the augmented version, we gave participants an additional alternative abstracting the use of an application that frequently saves time but can sometimes have high costs. This alternative was stochastically dominated by the option abstracting the responsible choice and was thus normatively “irrelevant” to the decision participants made. Nevertheless, most people chose the new (“irrelevant”) alternative, providing the first clear demonstration of underweighting of rare events in fully described social games. We discuss public policies that can make the responsible use of health applications better most of the time, thus helping them get traction despite being voluntary. In one field demonstration of this idea amid the COVID-19 pandemic, usage rates of a contact tracing application among nursing home employees more than tripled when using the app also started saving them little time on a daily basis, and the high usage rates sustained over at least four weeks.

Optimal policy for multi-alternative decisions

Every-day decisions frequently require choosing among multiple alternatives. Yet, the optimal policy for such decisions is unknown. Here we derive the normative policy for general multi-alternative decisions. This strategy requires evidence accumulation to nonlinear, time-dependent bounds, that trigger choices. A geometric symmetry in those boundaries allows the optimal strategy to be implemented by a simple neural circuit involving a normalization with fixed decision bounds and an urgency signal. The model captures several key features of the response of decision-making neurons as well as the increase in reaction time as a function of the number of alternatives, known as Hick’s law. In addition, we show that, in the presence of divisive normalization and internal variability, our model can account for several so called ‘irrational’ behaviors such as the similarity effect as well as the violation of both the independent irrelevant alternative principle and the regularity principle.

INDEPENDENCE OF IRRELEVANT ALTERNATIVES AND FUZZY ARROW'S THEOREM

The literature involving fuzzy Arrow results uses the same independence of irrelevant alternatives condition. We introduce three other types of independence of irrelevant alternative conditions and show that they can be profitably used in the examination of Arrow's theorem. We also generalize some known nondictatorship results. One known fuzzy aggregation rule that is nondictatorial is the average of the individual preferences. We show that a weighted average is also nondictatorial. Moreover, it is not an automorphic image of the ordinary average, which demonstrates that we have proposed a framework unique from the present known results.

A Review On Some Alternative Specifications Of The Logit Model

The logit model, perhaps the simplest and the best possible probabilistic choice model in the discrete choice modeling literature. As a matter of fact, it has been extensively used in many statistical and economic applications. Unfortunately, a very unattractive property of this model in its multinomial situation is independence of irrelevant alternative (IIA) property. Due to such limitation, a number of alternative possible specifications have been proposed in the literature. This paper investigates some of the important alternative specifications of the logit model along with their merits, demerits, estimation techniques, testing procedures and attempts to advocate about the superiority of the existing specifications for the users. Interestingly, we found no such absolutely superior model to be used as an alternative to the logit model. However, generalized extreme value (GEV) model and multinomial probit model have been found to be very promising and much better than other models.