The Acceptance of AI-based Recommendations: An Elaboration Likelihood Perspective

Algorithmic advice has been shown to outperform human reasoning in various domains. However, prior research suggests that humans might be reluctant to accept it and proposed multiple avenues to increase the acceptance. To structure these approaches and potentially shed light on inconclusive results of prior studies, we propose a novel perspective on the acceptance of AI-based recommendations based on the elaboration likelihood model (ELM). This research in progress paper introduces our perspective on AI-based recommendations as persuasive messages, suggests the ELM as a promising approach to guide interventions aiming to increase their acceptance, and develops testable hypotheses to evaluate the model. We, thereby, include the moderating effects of individual and situational variables

Empowering Consumers to Make Environmentally Sustainable Online Shopping Decisions: A Digital Nudging Approach

An ever-increasing share of people is using online shopping to satisfy their consumer needs. This has led to a vivid discussion regarding the environmental sustainability of e-commerce that also emphasized the role that consumer's decisions can play in mitigating its negative impacts. However, while many individuals state that they are willing to act more sustainably, they often struggle to follow through with their `green' intentions. We propose digital nudging as an approach to encourage environmentally sustainable online shopping decisions and empower consumers to act in line with their intentions. In an online experiment with 323 participants, we evaluate the effectiveness of three different nudging interventions (defaults, active choice, and self-nudging) to promote environmentally sustainable shipping options in an online store and assess the consumers' ethics and empowerment perceptions of the nudges. We find that all nudges are effective in changing decisions, but default nudges lead to negative perceptions among consumers

Is It All About Transparency? The Effectiveness and Ethics of a Digital Salience Nudge

Digital nudges offer a promising avenue to promote individual welfare by supporting individuals in their daily decision-making. However, most existing applications merely adapt analog nudges to the digital world, rather than leveraging the unique possibilities that digital environments offer. At the same time, recent discussions raise ethical objections to nudges and suggest disclosing transparent information about nudges as a measure to overcome these. Based on salience theory, we develop a digital salience nudge to increase the healthiness of online food product choices by reducing the visual salience of unhealthy food products. In an online experiment with 399 participants, we evaluate the effectiveness of this nudge and investigate the effect of disclosing transparent information on the nudge. The results suggest that the digital salience nudge reduces the share of unhealthy food product choices by 44% (from 27 to 15%). Disclosing transparent information on the nudge, however, does not change its effectiveness

The influence of algorithm aversion and anthropomorphic agent design on the acceptance of AI-based job recommendations

Artificial intelligence (AI) offers promising tools to support the job-seeking process by providing automatic and user-centered job recommendations. However, job seekers often hesitate to trust AI-based recommendations in this context given the far-reaching consequences of the importance of the decision for a job on their future career and life. This hesitation is largely driven by a lack of explainability, as underlying algorithms are complex and not clear to the user. Prior research suggests that anthropomorphization (i.e., the attribution of human traits) can increase the acceptance of technology. Therefore, we adapted this concept for AI-based recommender systems and conducted a survey-based study with 120 participants. We find that that using an anthropomorphic design in a recommender system for open positions increases job seekers\u27 acceptance of the underlying system. However, algorithm aversion rises if detailed information on the algorithmic origin is being disclosed

Effects of Digital Food Labels on Healthy Food Choices in Online Grocery Shopping

In order to induce the shift in consumer behavior necessary for the mitigation of diet-related diseases, front-of-package labels (FoPL) such as the Nutri-Score that support consumers in their efforts to identify nutritionally valuable products during grocery shopping have been found to be effective; however, they remain non-compulsory in most regions. Counter-intuitively, a similar stream of research on digital web-based FoPL does not yet exist, even though such digital labels hold several advantages over physical labels. Digital FoPL can provide scalable and personalized interventions, are easier to implement than physical labels, and are especially timely due to the recent increase in online grocery shopping. The goal of this study was to demonstrate the technical feasibility and intervention potential of novel, scalable, and passively triggered health behavior interventions distributed via easy-to-install web browser extensions designed to support healthy food choices via the inclusion of digital FoPL in online supermarkets. To that end, we developed a Chrome web browser extension for a real online supermarket and evaluated the effect of this digital food label intervention (i.e., display of the Nutri-Score next to visible products) on the nutritional quality of individuals’ weekly grocery shopping in a randomized controlled laboratory trial (N = 135). Compared to the control group, individuals exposed to the intervention chose products with a higher nutritional quality (e.g., 8% higher healthy trolley index (HETI), 3.3% less sugar, 7.5% less saturated fat). In particular, users with low food literacy seemed to benefit from the digital FoPL (e.g., 11% higher HETI, 10.5% less sugar, 5.5% less saturated fat). Furthermore, participants exposed to the food label advocated its introduction more strongly than the control group (p = 0.081). Consumers worldwide could easily install such applications to display digital food labels on their end devices, and would thus not have to wait for stakeholders in the food industry to eventually reach consensus on mandatory food label introduction.ISSN:2072-664