Lady Luck: Anthropomorphized Luck Creates Perceptions of Risk-Sharing and Drives Pursuit of Risky Alternatives

Abstract

We examine decision-making under risk as a function of the degree to which consumers anthropomorphize their luck. We propose that consumers make riskier financial decisions when they anthropomorphize (vs. objectify) their luck and that this effect occurs because humanizing luck engenders a perceived sharing of risk in the presence of "lady luck." A series of experiments shows that consumers among whom anthropomorphized versus objectified luck is salient display greater risk-taking in financial, but not social, decisions. These effects are heightened among consumers who frequently engage in risky decision-making and are driven by perceptions of risk-sharing produced by anthropomorphized luck. Collectively, these findings document how anthropomorphizing luck can influence consumers' decision-making within the financial domain. We discuss important consumer welfare implications associated with the negative consequences that result from repeated detrimental consumer behaviors, particularly given the pervasive use of anthropomorphized luck by marketers in the gambling domain.For a change, lady luck seemed to be smiling on me. Then again, maybe the fickle wench was just lulling me into a false sense of security while she reached for a rock.

Sophia Sophia tell me more, which is the most risk-free plan of all? AI anthropomorphism and risk aversion in financial decision-making

“…Since the seminal work of Mori (uncanny valley theory;1970, scholars have been investigating human-like robotics and other applications. However, the way consumers respond to anthropomorphized and non-anthropomorphized AI agents still remains underexamined (Kulow et al, 2021). This present work therefore attempts to address this void by looking into the downstream impact of AI anthropomorphism on consumers' risk preferenceswhether anthropomorphizing AI can alter consumer psychology, and if so, how (Kim and McGill, 2011)?…”

“…To better understand the rationale behind anthropomorphism, scholars from a myriad of disciplines have been investigating factors influencing when , why , who engages in anthropomorphism, and in what way/how they do so. In this line of inquiry, two prominent motivators surface, shedding light upon why people engage in anthropomorphism: (1) the motivation to feel socially affiliated with others (Kulow et al ., 2021) – being connected with a human-like inanimate agents can serve as a substitute for social affiliation – and (2) the motivation to comprehend uncertainty – imbuing non-human objects with human-like features allow consumers to understand such inanimate agents better (Chan, 2020).…”

“…probabilities) has been corroborated in research across disciplines, such as marketing, economics, finance, and social psychology. For example, Kulow et al . (2021) found that humanizing luck (e.g.…”

“…Second, the findings illustrate that anthropomorphizing AI-enabled chatbots in the context of financial decision-making involving risks results in greater risk aversion, as the focal risks involved appear to be more psychologically attached. Interestingly, in a relevant inquiry regarding risks, the authors found that anthropomorphizing (vs. objectifying) luck leads consumers to make riskier financial decisions as anthropomorphization thereof activates a perception that luck is shared (Kulow et al ., 2021). The conflicting findings therefore invite future researchers to look into potential moderators to account for such disparities.…”

“…Consumers prevalently encounter financial offerings by AI, in which multiple investment options might be proposed with varying levels of risk and return. The disparity of consumers' risk preference may affect what investment choices one might make, thereby highlighting the imperative of understanding the factors influencing risk preferences (Kulow et al ., 2021). Extant research in this realm of inquiry has substantiated the role of diverse individual difference factors in influencing risk preferences, including life strategy (fast vs. slow; Jonason et al ., 2010), socioeconomic status, and inherent risk tolerance level (Faff et al ., 2008).…”