Getting Over Past Mistakes: Prospective and Retrospective Regret in Older Adults.

OBJECTIVE: A considerable number of older people who hold powerful positions in governments and corporate are actively engaged in making decisions that have a far-reaching impact on the community. Some of them have to make decisions on behalf of others, and sometimes, the outcomes of their decisions for others are unfavorable. We experience retrospective regret when the obtained outcome turns out to be less attractive than the counterfactual one. We also actively make choices to avoid regretful outcomes if we prospectively anticipate the regret. In the current study, we investigated how older adults experience regret and how they make choices to avoid potential regret, in the context of making decisions for themselves and on behalf of others. METHOD: Sixty younger and 60 older participants performed a gambling task in which two types of regret were independently measured: prospective (planning to avoid regret during decision making) and retrospective (feeling of regret following the comparison of alternative outcomes). RESULTS: Our results showed that compared to younger adults, the older adults were less sensitive to regret-inducing outcomes, whereas they demonstrated comparable ability in using prospective regret to guide decisions, regardless of whether they made decisions for themselves or on behalf of others. DISCUSSION: Our findings indicate that although older adults experience blunted regret, their ability to avoid future regret to guide subsequent choices remains unimpaired. Our research has implications for understanding how older adults cope with regret.

Sparse Extended Redundancy Analysis: Variable Selection via the Exclusive LASSO.

Extended Redundancy Analysis is a statistical tool for exploring the directional relationships of multiple sets of exogenous variables on a set of endogenous variables. This approach posits that the endogenous and exogenous variables are related via latent components, each of which is extracted from a set of exogenous variables, that account for the maximum variation of the endogenous variables. However, it is often difficult to distinguish between the true variables that form the latent components and the false variables that do not, especially when the association between the true variables and the exogenous set is weak. To overcome this limitation, we propose a Sparse Extended Redundancy Analysis via the Exclusive LASSO that performs variable selection while maintaining model specification. We validate the performance of the proposed approach in a simulation study. Finally, the empirical utility of this approach is demonstrated through two examples-one on a study of youth academic achievement and the other on a text analysis of newspaper data.

Trust in Robots: Challenges and Opportunities.

PURPOSE OF REVIEW: To assess the state-of-the-art in research on trust in robots and to examine if recent methodological advances can aid in the development of trustworthy robots. RECENT FINDINGS: While traditional work in trustworthy robotics has focused on studying the antecedents and consequences of trust in robots, recent work has gravitated towards the development of strategies for robots to actively gain, calibrate, and maintain the human user's trust. Among these works, there is emphasis on endowing robotic agents with reasoning capabilities (e.g., via probabilistic modeling). SUMMARY: The state-of-the-art in trust research provides roboticists with a large trove of tools to develop trustworthy robots. However, challenges remain when it comes to trust in real-world human-robot interaction (HRI) settings: there exist outstanding issues in trust measurement, guarantees on robot behavior (e.g., with respect to user privacy), and handling rich multidimensional data. We examine how recent advances in psychometrics, trustworthy systems, robot-ethics, and deep learning can provide resolution to each of these issues. In conclusion, we are of the opinion that these methodological advances could pave the way for the creation of truly autonomous, trustworthy social robots.

Choosing for you: Diminished self-other discrepancies in financial decisions under risk in the elderly.

Many older adults hold powerful positions in governments and corporate boards throughout the world. Accordingly, older adults often have to make important financial decisions on behalf of others under risk. Although it is common to observe younger adults taking more risks when making financial decisions for others, it is unclear if older adults exhibit the same self-other discrepancies. Here, we conducted 2 studies (88 and 124 participants, respectively) to examine self-other discrepancies in financial decision making under risk in older adults. We focused on 3 aspects of financial decision making: loss aversion (a tendency to weight potential losses more strongly than potential gains), risk-aversion asymmetry (a tendency to be risk-averse for potential gains and risk-seeking for potential losses), and risk preferences separately in gain and loss domains. Using computational modeling and behavioral economics tasks, we found weaker self-other discrepancies in older adults (compared with younger adults) across all 3 aspects. We also replicated the age differences in self-other discrepancies in loss aversion across 2 largely nonoverlapping cohorts. Thus, it appears that when making financial decisions on behalf of others, older adults, relative to younger adults, have a stronger disposition to regard others' financial outcomes as important as their own. (PsycINFO Database Record

Generous to whom? The influence of oxytocin on social discounting.

Oxytocin is thought to play an essential role in pro-social behaviors, such as generosity and altruism, in humans. Yet, most research in humans that demonstrated the pro-social effect of oxytocin had participants interact with partners who were total strangers to them. In real life, however, people often interact with others varying in social relatedness with them (a concept known as social distance), ranging from their parents to total strangers. Here we employed the social-discounting framework to investigate whether the effect of oxytocin on prosociality depends on the social distance between the participants and their interaction partners. In a double-blind, placebo-controlled experiment (n=172 participants), we measured the amount of money participants were willing to forgo to another person as a function of social distance. We found that oxytocin administration selectively enhanced amount of money forgone toward total strangers, as opposed to someone closer to participants, suggesting that social distance constrained the pro-social effect of oxytocin.