Hal E. Hershfield

The decision of when to claim Social Security benefits is among the most consequential and irreversible financial choices older Americans face, yet interventions to help guide it have had limited effectiveness. Building upon past research demonstrating that people choose differently and make different predictions for others than they do for themselves, we ask whether making recommendations for another can shift one’s own claiming decision. In two high-powered experiments using national survey panels, we show that older American adults intend to claim retirement income benefits earlier (vs. later) after making guided recommendations for a person who died relatively young (vs. lived to an old age) after retiring. This effect persists when the effect of recalling such a person is disentangled from that of recommending. This research suggests that making guided recommendations for others can be a powerful intervention for one’s own choices in highly consequential domains where trade-offs are difficult to make.

Major life transitions demand high-stakes decisions, yet people often struggle to imagine how their future selves will live with the consequences. To support this limited capacity for mental time travel, we introduce AI-enabled digital twins that have ``lived through'' simulated life scenarios. Rather than predicting optimal outcomes, these simulations extend prospective cognition by making alternative futures vivid enough to support deliberation without assuming which path is best. We evaluate this idea in a randomized controlled study (N=192) using multimodal synthesis - facial age progression, voice cloning, and large language model dialogue - to create personalized avatars representing participants 30 years forward. Young adults 18 to 28 years old described pending binary decisions and were assigned to guided imagination or one of four avatar conditions: single-option, balanced dual-option, or expanded three-option with a system-generated novel alternative. Results showed asymmetric effects: single-sided avatars increased shifts toward the presented option, while balanced presentation produced movement toward both. Introducing a system-generated third option increased adoption of this new alternative compared to control, suggesting that AI-generated future selves can expand choice by surfacing paths that might otherwise go unnoticed. Participants rated evaluative reasoning and eudaimonic meaning-making as more important than emotional or visual vividness. Perceived persuasiveness and baseline agency predicted decision change. These findings advance understanding of AI-mediated episodic prospection and raise questions about autonomy in AI-augmented decisions.

What if users could meet their future selves today? AI-generated future selves simulate meaningful encounters with a digital twin decades in the future. As AI systems advance, combining cloned voices, age-progressed facial rendering, and autobiographical narratives, a central question emerges: Does the modality of these future selves alter their psychological and affective impact? How might a text-based chatbot, a voice-only system, or a photorealistic avatar shape present-day decisions and our feeling of connection to the future? We report a randomized controlled study (N=92) evaluating three modalities of AI-generated future selves (text, voice, avatar) against a neutral control condition. We also report a systematic model evaluation between Claude 4 and three other Large Language Models (LLMs), assessing Claude 4 across psychological and interaction dimensions and establishing conversational AI quality as a critical determinant of intervention effectiveness. All personalized modalities strengthened Future Self-Continuity (FSC), emotional well-being, and motivation compared to control, with avatar producing the largest vividness gains, yet with no significant differences between formats. Interaction quality metrics, particularly persuasiveness, realism, and user engagement, emerged as robust predictors of psychological and affective outcomes, indicating that how compelling the interaction feels matters more than the form it takes. Content analysis found thematic patterns: text emphasized career planning, while voice and avatar facilitated personal reflection. Claude 4 outperformed ChatGPT 3.5, Llama 4, and Qwen 3 in enhancing psychological, affective, and FSC outcomes.

Perspective-taking has been theorized to be a central psychological process in how people make punishment decisions. However, previous research has only tested theory in low-stakes or hypothetical contexts. The current research describes how jurors perspective-take in real capital punishment trials (N = 1,198) and tests a series of hypotheses from previous research in a high-stakes, naturalistic context. In examining the predictors of perspective-taking, we found that jurors are more likely to perspective-take for white victims than black victims, but not more likely to perspective-take if the trial participant is demographically similar to themselves. We further uncovered new findings that older jurors perspective-take less (regardless of whether it is for perpetrators or victims), and women perspective-take for victims more than men do. In examining how perspective-taking relates to capital punishment decisions, we found that jurors who take victims’ perspectives are more likely to vote for the death penalty. We found mixed support for the theory that jurors who take defendants’ perspectives are more lenient. We conclude by discussing the implications of our findings for legal arguments on the arbitrary and biased nature of capital punishment decisions.

In response to the alarming recent decline in US math achievement, we conducted a national megastudy in which 140,461 elementary school teachers who collectively taught 2,992,027 students were randomly assigned to receive a variety of behaviorally informed email nudges aimed at improving students’ progress in math. Specifically, we partnered with the nonprofit educational platform Zearn Math to compare the impact of 15 different interventions with a reminder-only megastudy control condition. All 16 conditions entailed weekly emails delivered to teachers over 4-wk in the fall of 2021. The best-performing intervention, which encouraged teachers to log into Zearn Math for an updated report on how their students were doing that week, produced a 5.06% increase in students’ math progress (3.30% after accounting for the winner’s curse). In exploratory analyses, teachers who received any behaviorally informed email nudge (vs. a reminder-only megastudy control) saw their students’ math progress boosted by an average of 1.89% during the 4-wk intervention period; emails referencing personalized data (i.e., classroom-specific statistics) outperformed emails that did not by 2.26%. While small in size, these intervention effects were consistent across school socioeconomic status and school type (public, private, etc.) and, further, persisted in the 8-wk post-intervention period. Collectively, these findings underscore both how difficult it is to change behavior and the need for large-scale, rigorous, empirical research of the sort undertaken in this megastudy.

Many people struggle to make tradeoffs between present wants and future wishes, resulting in the tendency to overly discount the value of future rewards. To explain such behavior, past work has pointed to future self-continuity or the perceived connection between a person’s current and future selves. Yet, most of this past work has been conducted on small-to-medium size convenience samples, and as such, little is known regarding the population-level statistics of future self-continuity or how its link to important financial health variables like saving behavior and financial well-being play out in a nationally representative sample. Here, we use a nationally representative sample of over 6,000 Americans to investigate the generalizability of future self-continuity and its connection to financial outcomes such as savings behavior and global financial well-being. We also examine the strength of these associations in the face of a host of other relevant constructs. Overall, this research replicates and extends existing work on the relationship between future self-continuity and financial decision-making among a representative population, and sheds further insight on its potential implications for interventions aimed at enhancing long-term financial well-being.

Many consumers say they want to save for the future yet struggle to do so. This research examines this saving behavior problem from a persuasive messaging standpoint. With the goal of helping people take better care of their future selves, we build on a stream of research that has found that the way people view their identities over time affects the saving decisions they make. Although past research on similarity judgments across time almost exclusively starts with the present self and moves forward to the future self, such judgments could theoretically start at any point in time. Here, we explore the possibility of backward mental time travel, by asking people to start in the future and return to the present. A series of studies shows that mentally traveling from the future to the present—rather than the present to the future—increases perceived similarity between selves across time by reducing the uncertainty of the destination self. Lab studies and two large-scale experiments indicate that, as an important outcome of this novel intervention, mentally traveling from the future to the present has a small but positive impact, systematically increasing savings intentions and savings behavior.