Who Made This? Algorithms and Authorship Credit.

Producers and creators often receive assistance with work from other people. Increasingly, algorithms can provide similar assistance. When algorithms assist or augment producers, does this change individuals' willingness to assign credit to those producers? Across four studies spanning several domains (e.g., painting, construction, sports analytics, and entrepreneurship), we find evidence that producers receive more credit for work when they are assisted by algorithms, compared with humans. We also find that individuals assume algorithmic assistance requires more producer oversight than human assistance does, a mechanism that explains these higher attributions of credit (Studies 1-3). The greater credit individuals assign to producers assisted by algorithms (vs. other people) also manifests itself in increased support for those producers' entrepreneurial endeavors (Study 4). As algorithms proliferate, norms of credit and authorship are likely changing, precipitating a variety of economic and social consequences.

Assumptions About Algorithms' Capacity for Discrimination.

Although their implementation has inspired optimism in many domains, algorithms can both systematize discrimination and obscure its presence. In seven studies, we test the hypothesis that people instead tend to assume algorithms discriminate less than humans due to beliefs that algorithms tend to be both more accurate and less emotional evaluators. As a result of these assumptions, people are more interested in being evaluated by an algorithm when they anticipate that discrimination against them is possible. We finally investigate the degree to which information about how algorithms train using data sets consisting of human judgments and decisions change people's increased preferences for algorithms when they themselves anticipate discrimination. Taken together, these studies indicate that algorithms appear less discriminatory than humans, making people (potentially erroneously) more comfortable with their use.

Generating authenticity in automated work.

In an increasing number of domains, people interact with automated agents (such as algorithms, robots, and computers) instead of humans. Across five studies, we explore the role of authenticity in shaping people's reactions to automated agents' work. In doing so, we examine two basic ways to generate authenticity in autonomous technological work: (a) highlighting the human origins of autonomous technologies and (b) anthropomorphizing autonomous technologies, or presenting them with human-like qualities. We find strong evidence that human origin stories generate authenticity, but much less evidence that simple anthropomorphic cues do so to the same degree (Studies 1-3). Simply prompting people to consider human origins can also generate attributions of authenticity (Study 4), which translates into intended and recommended support for automated work (Study 5). We discuss how managers of organizations can implement automated systems in ways that encourage attributions of authenticity. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Privacy matters or does It? Algorithms, rationalization, and the erosion of concern for privacy.

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.

Collectives in organizations appear less morally motivated than individuals.

[Correction Notice: An Erratum for this article was reported online in Journal of Experimental Psychology: General on Oct 24 2019 (see record 2019-63657-001). In the article "Collectives in Organizations Appear Less Morally Motivated Than Individuals" by Arthur S. Jago, Tamar A. Kreps, and Kristin Laurin, the second affiliation of the first author was omitted from the byline and author note. The byline should appear instead as University of Southern California and University of Washington-Tacoma. The first paragraph of the author note should appear instead as Arthur S. Jago, Department of Management and Organization, University of Southern California, and Milgard School of Business, University of Washington-Tacoma. The third paragraph of the author note should appear instead as the following: Correspondence concerning this article should be addressed to Arthur S. Jago, Milgard School of Business, University of Washington - Tacoma, 1900 Commerce Street DOU 306, Tacoma, WA 98402. Email: ajago@uw.edu] Organizations often benefit from signaling moral values. Across 5 studies, we explore how people attribute moral conviction to different organizational agents. We find that people believe collectives (e.g., groups; entire organizations) have less moral conviction than individuals, even when both agents behave identically (Studies 1 and 2). We test a variety of potential mechanisms for this effect, and find evidence for two parallel pathways: first, people believe collectives have less of a capacity for emotional experience, and therefore are less likely to use emotions when making decisions; and second, people believe collectives are also more self-interested, and therefore more likely to behave out of concern for their reputations rather than morality (Study 3). In examining boundary conditions for this effect, we find that it occurs when people judge generic for-profit companies and government entities, but not family businesses or charities (Study 4). Finally, we demonstrate that, because collectives appear less morally motivated than individuals, people also assume collectives will exhibit less persistence after enacting prosocial initiatives (Study 5). We discuss theoretical, practical, and social implications of these differing attributions of moral conviction. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Corporate personhood: Lay perceptions and ethical consequences.

Modern conceptions of corporate personhood have spurred considerable debate about the rights that society should afford business organizations. Across eight experiments, we compare lay perceptions of how corporations and people use rights, and also explore the consequences of these judgments. We find that people believe corporations, compared to humans, are similarly likely to use rights in protective ways that prevent harm but more likely to use rights in nonprotective ways that appear independent from-or even create-harm (Experiments 1a through 1c and Experiment 2). Because of these beliefs, people support corporate rights to a lesser extent than human rights (Experiment 3). However, people are more supportive of specific corporate rights when we framed them as serving protective functions (Experiment 4). Also as a result of these beliefs, people attribute greater ethical responsibility to corporations, but not to humans, that gain access to rights (Experiments 5a and 5b). Despite their equitability in many domains, people believe corporations and humans use rights in different ways, ultimately producing different reactions to their behaviors as well as asymmetric moral evaluations. (PsycINFO Database Record