Algorithmic Management Diminishes Status: An Unintended Consequence of Using Machines to Perform Social Roles→

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Jago, A. S., Raveendhran, R., Fast, N.J., & Gratch, J. (2024). Journal of Experimental Social Psychology, 110, 104553.

As artificial intelligence (AI) proliferates throughout society, it brings the potential to reshape how people perceive social roles and relationships. Across five preregistered studies, we investigated how AI-based algorithmic management influences perceptions and forecasts of social status. We found that people believe algorithmic management, compared to prototypical human management, leads to lower status in the eyes of others (Study 1). Moreover, forecasts of lower status mediated people's anticipated negative emotions when assessing remote jobs that were framed as primarily algorithmically managed (Study 2). Further, we found that people infer lower status given algorithmic management because they believe it signals that job tasks lack complexity, both when evaluating themselves or others (Studies 3 and 4). Finally, using OpenAI's natural language processing algorithm (GPT-3), we created an actual managerial algorithm and found that the lowered status inferences persist when people are managed by an algorithm that provides instructions, feedback, and monetary incentives (Study 5). We discuss theoretical implications for research on status, hierarchy, and the psychology of technology.

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Is GenAI’s Impact on Productivity Overblown?→

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Waber, B., & Fast, N.J., (2024). Harvard Business Review.

Generative AI like LLMs have been touted as a boon to collective productivity. But the authors argue that leaning into the hype too much could be a mistake. Assessments of productivity typically focus on the task level and how individuals might use and benefit from LLMs. Using such findings to draw broad conclusions about firm-level performance could prove costly. The authors argue that leaders need to understand two core problems of LLMs before adopting them company-wide: 1) their persistent ability to produce convincing falsities and 2) the likely long-term negative effects of using LLMs on employees and internal processes. The authors outline a long-term perspective on LLMs, as well as what kinds of tasks LLMs can perform reliably

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Understanding the Leaders of Tomorrow: The Need to Study Leadership in Adolescence→

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Fast, N.J. (2023). Perspectives on Psychological Science, 18, 829-842.

Leadership traits and behaviors are observed early in human development, and although an improved understanding of youth leadership would usefully inform many real-world contexts (e.g., education, parenting, policy), most empirical work on leadership has been limited to adult populations. The purpose of the current article is to add a developmental perspective to leadership research that has so far been absent. Here, we (a) highlight adolescence as a critical developmental period for leadership emergence and development, (b) argue that leadership among youths is poorly understood and critically understudied, (c) provide exemplars of synergy between research on leadership and adolescent development that are ripe for focused inquiry, and (d) underscore some of the positive consequences of accelerating empirical research on leadership in adolescence, including implications for a deeper understanding of leadership in adult working populations.

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“Inventor’s Bias” at Work: When Low-Performing Algorithms Seem Fair→

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Cratsley, M.J., & Fast, N.J. (2023). International Journal of Human-Computer Interaction, 40, 24-32

This article introduces the “Inventor’s Bias Effect,” the propensity for inventors to be over-optimistic about the positive features and uses of the products they create. We explore this phenomenon in the context of decision-making algorithms by conducting two online studies (N = 1001) where subjects were asked to either create or evaluate an AI-based tool that can automate human resource decisions in an organization. Study 1 revealed that individuals in the role of inventor perceived a low-performing algorithm they created as fairer relative to the ratings of other stakeholders (CEOs, employees, and the general public). The tendency for these “inventors” to personally identify with the products they created mediated this effect. Study 2 showed that inventors’ perceptions of fairness of the algorithms they created translated into an increased desire for the organization to continue using their product, even though it was inaccurate for a third of all decisions. This research demonstrates how stakeholders’ relations to algorithms may encourage biased decision making and highlights the need for caution in organizational and political decision-making processes.

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The Social Alignment Theory of Power: Predicting Associative and Dissociative Behavior in Hierarchies→

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Fast, N.J., & Overbeck, J.R. (2022). Research in Organizational Behavior.

Evolutionary social psychologists have demonstrated that powerholders generally attain and maintain rank in social hierarchies through two distinct types of behaviors: associative (prestige-based) strategies or dissociative (dominance-based) strategies. However, the dual-strategies literature lacks a theoretical account of when and why people adopt one approach over the other. We provide a theoretical model of power to address this question and also expand the focus to include low-power versions of associative (persuasion-based) and dissociative (passivity-based) strategies. To develop our framework, we build on the distinction between power (i.e., asymmetric control over valued resources) and volitional influence (i.e., the ability to produce willful changes in others). We posit that individuals who perceive high volitional influence with regard to another party are in a state of social alignment, because their interests and those of the other party are, or can easily become, aligned. As a result, they pursue associative strategies (prestige for high-power actors, or persuasion for low-power actors). In contrast, individuals with low perceived volitional influence are in a state of social misalignment, because their interests and those of the other party are misaligned. As a result, they pursue dissociative strategies (dominance for high-power actors, or passivity for low-power actors). To help distinguish between power and volitional influence, we offer a new capital-based typology of power and outline key antecedents of volitional influence. We conclude by outlining future directions for research on power and key topics in organizational behavior.

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The Power To Do Harm: AI Assistants Pave the Way for Unethical Behavior→

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Gratch, J., & Fast, N.J. (2022). Current Opinion in Psychology, 47.

Advances in artificial intelligence (AI) enable new ways of exercising and experiencing power by automating interpersonal tasks such as interviewing and hiring workers, managing and evaluating work, setting compensation, and negotiating deals. As these techniques become more sophisticated, they increasingly support personalization where users can “tell” their AI assistants not only what to do, but how to do it: in effect, dictating the ethical values that govern the assistant’s behavior. Importantly, these new forms of power could bypass existing social and regulatory checks on unethical behavior by introducing a new agent into the equation. Organization research suggests that acting through human agents (i.e., the problem of indirect agency) can undermine ethical forecasting such that actors believe they are acting ethically, yet a) show less benevolence for the recipients of their power, b) receive less blame for ethical lapses, and c) anticipate less retribution for unethical behavior. We review a series of studies illustrating how, across a wide range of social tasks, people may behave less ethically and be more willing to deceive when acting through AI agents. We conclude by examining boundary conditions and discussing potential directions for future research.

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Humans Judge, Algorithms Nudge: The Psychology of Behavior Tracking Acceptance→

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Raveendhran, R., & Fast, N.J. (2021). Organizational Behavior and Human Decision Processes, 164, 11-26.

This article examines employees’ acceptance of behavior tracking in the workplace. We theorize that people more willingly accept behavior tracking when it is conducted solely by technology (i.e., computer algorithms) rather than by humans. We posit that this is driven by the expectation that human-free tracking feels less judgmental and will, therefore, allow for a greater subjective sense of autonomy. The results of five experiments supported these predictions, revealing that participants were more likely to accept technology-operated than human-operated tracking (Experiments 1–5), an effect driven by reduced concerns about potential negative judgment, which, in turn, increased subjective sense of autonomy (Experiment 2). The stated purpose for tracking (Experiment 3), relation to the human tracker (Experiment 4), and type of behaviors tracked (Experiment 5) did not eliminate the effect. Technology-operated tracking also led to higher anticipation of intrinsic motivation (Experiments 3–4). Implications for research on the future of work are discussed.

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Power and Decision Making: New Directions for Research in the Age of Artificial Intelligence→

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Fast, N.J., and Schroeder, J. (2020). Current Opinion in Psychology, 33, 172-176.

Throughout history, the experience of power has occurred within the context of human-human interactions. Such power can influence decision making through at least two primary mechanisms: 1) increased goal-orientation, and 2) increased activation of social role expectations. Importantly, new advances in artificial intelligence (AI) are creating the potential to experience power in human-AI interactions. To the extent that some forms of AI can be made to seem like low-power humans (e.g., autonomous digital assistants), people may feel powerful when interacting with such entities. However, it is unclear whether feeling power over AI will lead to the same psychological consequences as feeling power over humans. In this article, we review findings on power and decision making and then consider how they may be meaningfully extended by considering interactions with artificially intelligent digital assistants. We conclude with a call for new theorizing and research on power in the age of artificial intelligence.

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When Eliminating Bias Isn't Fair: Algorithmic Reductionism and Procedural Justice in Human Resource Decisions→

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Newman, D., Fast, N.J., and Harmon, D.J. (2020). Organizational Behavior and Human Decision Processes., 160, 149-167.

The perceived fairness of decision-making procedures is a key concern for organizations, particularly when evaluating employees and determining personnel outcomes. Algorithms have created opportunities for increasing fairness by overcoming biases commonly displayed by human decision makers. However, while HR algorithms may remove human bias in decision making, we argue that those being evaluated may perceive the process as reductionistic, leading them to think that certain qualitative information or contextualization is not being taken into account. We argue that this can undermine their beliefs about the procedural fairness of using HR algorithms to evaluate performance by promoting the assumption that decisions made by algorithms are based on less accurate information than identical decisions made by humans. Results from four laboratory experiments (N = 798) and a large-scale randomized experiment in an organizational setting (N = 1654) confirm this hypothesis. Theoretical and practical implications for organizations using algorithms and data analytics are discussed.

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It’s Not What You Say, It’s How You Say It: Conversational Flow as a Predictor of Networking Success→

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Truong, M., Fast, N.J., and Kim, J. (2020). Organizational Behavior and Human Decision Processes, 158, 1-10.

Networking success, or the capacity to make new connections and develop relationships, is an increasingly important component of professional performance. Others’ perceptions of one’s networking skills shape success, but little is known about the factors that drive these perceptions. In the present research, we theorize that the ability to establish and maintain flow during conversations uniquely predicts individuals’ networking success above and beyond other factors, such as extraversion, attractiveness, or interestingness. Consistent with this idea, Study 1 showed that individuals’ ability to maintain conversational flow during live, synchronous conversations is positively associated with networking success during a speed-networking event, even after factoring in other potential predictors. In Study 2, participants reported on their existing networks, indicating that strong networkers are better at maintaining conversational flow than weak networkers. In Studies 3a-3b, we manipulated conversational flow and demonstrated that participants attribute stronger networking skills and are more eager to connect with a target who maintains high (versus low) levels of conversational flow.

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Privacy Matters… Or Does It? Algorithms, Rationalization, and the Erosion of Concern for Privacy→

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Fast, N.J., and Jago, A.S. (2020). Current Opinion in Psychology, 31, 44-48.

Products and services built around artificially intelligent algorithms offer a host of benefits to users but they require vast amounts of personal data in return. As a result, privacy is perhaps more vulnerable today than ever before. We posit that this vulnerability is not only technical, but psychological. Whereas people have historically cared about and fought for the right to privacy, the diffusion and conveniences of algorithms could be systematically eroding people’s capacity and psychological motivation to take meaningful action. Specifically, we examine four factors that increase the tendency to rationalize privacy-reducing algorithms: 1) awareness of the benefits and conveniences of algorithms, 2) a low perceived probability of experiencing harm, 3) exposure to negative consequences only after usage has already begun, and 4) certainty that losing privacy is inevitable. We suggest that future research should consider these and related factors in order to better understand the changing psychology of privacy.

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Virtual (Freedom From) Reality: Evaluation Apprehension and Leaders’ Preference for Communicating Through Avatars→

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Raveendhran, R., Fast, N.J., and Carnevale, P.J. (2020). Computers in Human Behavior, 111, 1-12.

Virtual reality is spreading rapidly as an emerging communication tool in organizations. The present research examines when and why leaders might prefer interacting with their subordinates virtually, via computer avatars (graphical computer representations of humans), rather than through face-to-face interactions. We examine this question in the context of monitoring and seek to understand the underlying psychology that drives leaders’ preference for interacting via avatars. Across two experiments, we tested our predictions that (1) contexts that require frequent monitoring increase leaders' preference for interacting via avatars, and (2) this preference is driven by concerns about negative social evaluation. Results supported our predictions, indicating that contexts requiring frequent monitoring increase leaders' preference for interacting via avatars (Experiment 1), and this effect was due to increased concerns about negative social evaluation (Experiment2). We also explored the role of personality on this effect (Experiment 2). Theoretical implications for the psychology of leadership in the digital era and the adoption of novel technologies are discussed.

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Losing More Than Money: Organizations' Prosocial Actions Appear Less Authentic When Their Resources are Declining→

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Jago, A., Fast, N.J., and Peffer, J. (2020). Journal of Business Ethics., 114, 1-13

Companies often benefit from others’ attributions of moral conviction for prosocial behavior, for example, attributions that a company has a sincere moral desire to improve the environment when behaving sustainably. Across four studies, we explored how organizations’ changing resource positions influenced people’s attributions for the motivations underlying prosocial organizational behaviors. Observers attributed less moral conviction following prosocial behavior when they believed an organization was losing (vs. gaining) economic resources (Studies 1 and 2). This effect was primarily a “penalty” assessed against organizations that were losing resources, as opposed to a “reward” given to organizations gaining resources (Study 3). Finally, we found that this effect occurred because people perceive organizations that are losing resources as more situationally constrained, leading them to attribute less dispositional moral conviction (Study 4). We discuss theoretical and practical implications stemming from how changes in resource access can lead people to be more skeptical of organizations’ motivations following prosocial behavior.

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Consumer Decisions With Artificially Intelligent Voice Assistants→

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Benedict G.C., Suzanne B.S., Theo A.A., Baker, T., Diehl, K., Donkers, B., Fast, N.J., Häubl, G., Johnson, H., Karmarkar, U.R., Oppewal, H., Schmitt, B.H., Schroeder, J., Spiller, S.A., and Steffel, M. (2020). Marketing Letters.

Consumers are widely adopting Artificially Intelligent Voice Assistants (AIVAs). AIVAs now handle many different everyday tasks and are also increasingly assisting consumers with purchasing decisions, making AIVAs a rich topic for marketing researchers. We develop a series of propositions regarding how consumer decision-making processes may change when moved from traditional online purchase environments to AI-powered voice-based dialogs, in the hopes of encouraging further academic thinking and research in this rapidly developing, high impact area of consumer-firm interaction. We also provide suggestions for marketing managers and policymakers on points to pay attention to when they respond to the proposed effects of AIVAs on consumer decisions.

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Technology and Social Evaluation: Implications for Individuals and Organizations→

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Raveendhran, R., and Fast, N.J. (2019). In In R. N. Landers (Ed) The Cambridge Handbook of Technology and Employee Behavior, Cambridge University Press.

In this chapter, we introduce the central idea that, in social situations where the possibility of evaluation by others is salient, technology reduces concerns about social evaluation. We build on this idea to develop insights about the psychological and behavioral consequences of novel technologies for organizational actors. Specifically, we focus on two of the most influential types of new technologies that are becoming popular in organizations – behavior-tracking technology and virtual/augmented reality. We ground our discussion of the psychological impact of these new technologies in the context of monitoring and communication, two key organizational functions that have been continually transformed by technological advances. We present a detailed discussion on behavior-tracking technology and virtual/augmented reality where we explore the opportunities and challenges of using these technologies for monitoring and communication, and examine how these technologies influence people’s experiences of social evaluation in these contexts.

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Lacking Status Hinders Prosocial Behavior Among the Powerful→

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Cho, Y., and Fast, N.J. (2018). Social Behavior and Personality, 46, 1547-1560.

We conducted 2 studies to examine if status has varying effects on prosocial behavior for those at different levels of the power hierarchy. In Study 1 (N = 78), adults employed full-time in the USA responded to an online survey and the results showed that self-perceived power and status interacted to predict prosocial behavior. That is, lacking status led high-power, but not low-power, individuals to engage less in prosocial behavior. In Study 2 (N = 142), we orthogonally manipulated status and power and measured prosocial behavior. Once again, lacking status led to less helping behavior among high-power, but not low-power, participants. These findings show how power and status interact to influence interpersonal helping behavior. Implications for future research on social hierarchy and prosocial behavior are discussed.

Identity and Professional Networking→

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Raj, M., Fast, N.J., and Fisher, O. (2017). Personality and Social Psychology Bulletin, 43, 772-784.

Despite evidence that large professional networks afford a host of financial and professional benefits, people vary in how motivated they are to build such networks. To help explain this variance, the present article moves beyond a rational self-interest account to examine the possibility that identity shapes individuals’ intentions to network. Study 1 established a positive association between viewing professional networking as identity-congruent and the tendency to prioritize strengthening and expanding one’s professional network. Study 2 revealed that manipulating the salience of the self affects networking intentions, but only among those high in networking identity-congruence. Study 3 further established causality by experimentally manipulating identity-congruence to increase networking intentions. Study 4 examined whether identity or self-interest is a better predictor of networking intentions, providing support for the former. These findings indicate that identity influences the networks people develop. Implications for research on the self, identity-based motivation, and professional networking are discussed.

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When the Bases of Social Hierarchy Collide: Power Without Status Drives Interpersonal Conflict→

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Anicich, E.M., Fast, N.J., Halevy, N., and Galinsky, A.D. (2016). Organization Science, 27, 123-140.

Leveraging the social hierarchy literature, the present research offers a role-based account of the antecedents of interpersonal conflict. Specifically, we suggest that the negative feelings and emotions resulting from the experience of occupying a low-status position interact with the action-facilitating effects of power to produce vicious cycles of interpersonal conflict and demeaning behavior. Five studies demonstrate that power without status leads to interpersonal conflict and demeaning treatment, both in specific dyadic work relationships and among organizational members more broadly. Study 1 provides initial support for the prediction that employees in low-status/high-power roles engage in more conflict with coworkers than all other combinations of status and power. In Studies 2a and 2b, a yoked experimental design replicated this effect and established low-status/high-power roles as a direct source of the interpersonal conflict and demeaning treatment. Study 3 used an experimental manipulation of relative status and power within specific dyadic relationships in the workplace and found evidence of a vicious cycle of interpersonal conflict and demeaning treatment within any dyad that included a low-status/high-power individual. Finally, Study 4 utilized survey and human resource data from a large government agency to replicate the power without status effect on interpersonal conflict and demonstrate that power interacts with subjective status change to produce a similar effect; increasing the status of a high-power role reduces conflict whereas decreasing its status increases conflict. Taken together, these findings offer a role-based account of interpersonal conflict and highlight the importance of making a theoretical distinction between status and power.

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Institutional Frame Switching: How Institutional Logics Shape Individual Action→

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Glaser, V. L., Fast, N.J., Harmon, D. J., and Green, S. E. (2016). In J. Gehman , M. Lounsbury , & R. Greenwood (Eds.) How Institutions Matter! Research in the Sociology of Organizations, Volume 48A, Emerald Group Publishing Limited, 35-69.

Although scholars increasingly use institutional logics to explain macro-level phenomena, we still know little about the micro-level psychological mechanisms by which institutional logics shape individual action. In this paper, we propose that individuals internalize institutional logics as an associative network of schemas that shapes individual actions through a process we call institutional frame switching. Specifically, we conduct two novel experiments that demonstrate how one particularly important schema associated with institutional logics—the implicit theory—can drive individual action. This work further develops the psychological underpinnings of the institutional logics perspective by connecting macro-level cultural understandings with micro-level situational behavior.

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Feeling High But Playing Low: Power, Need to Belong, and Submissive Behavior→

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Rios, K., Fast, N.J., and Gruenfeld, D.H. (2015). Personality and Social Psychology Bulletin, 41, 1135-1146.

Past research has demonstrated a causal relationship between power and dominant behavior, motivated in part by the desire to maintain the social distinctiveness created by one’s position of power. In this article, we test the novel idea that some individuals respond to high-power roles by displaying not dominance but instead submissiveness. We theorize that high-power individuals who are also high in the need to belong experience the social distinctiveness associated with power as threatening, rather than as an arrangement to protect and maintain. We predict that such individuals will counter their feelings of threat with submissive behaviors to downplay their power and thereby reduce their distinctiveness. We found support for this hypothesis across three studies using different operationalizations of power, need to belong, and submissiveness. Furthermore, Study 3 illustrated the mediating role of fear of (positive) attention in the relationship between power, need to belong, and submissive behavior.

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