Just like you like it - The effects of transparency and decision outcome on the evaluation of human and algorithmic decision-making

Algorithms are increasingly offered for human decision-making processes to support individuals with sophisticated data-driven insights in a variety of decision domains. Despite this promising potential, prior findings on the perceptions of algorithmic decision-making are ambiguous. This has led to a vivid discussion regarding the comprehensibility and fairness perceptions associated with human and algorithmic decision agents that also emphasized the role that decision-related factors can play in determining the evaluation of a certain decision. In a preregistered online experiment with 400 participants, we find that differences in the perceptions of decision transparency and fairness can be rather ascribed to the processes and rules applied to arrive at the decision and the decision outcome\u27s sentiment than to the decision agent. However, being confronted with a negative decision outcome in a situation that is characterized by uncertainty, leads to a preference for human decision agents

Fairness as a Determinant of AI Adoption in Recruiting: An Interview-based Study

Traditional recruiting techniques are often characterized by discrimination as human recruiters make biased decisions. To increase fairness in human resource management (HRM), organizations are increasingly adopting AI-based methods. Especially recruiting processes are restructured in order to find promising talents for vacant job positions. However, use of AI in recruiting is a two-edged sword as the neutrality of AI-based decisions highly depends on the quality of the underlying data. In this research-in-progress, we develop a research model explaining AI adoption in recruiting by defining and considering fairness as a determinant. Based on 21 semi-structured interviews we identified dimensions of perceived fairness (diversity, ethics, discrimination and bias, explainable AI) thereby affecting AI adoption. The proposed model addresses research gaps in AI recruiting research in general and arising ethical questions concerning the use of AI in people management in general and recruiting process in particular. We also discuss implications for further research and next steps of this research in progress work

One Save Per Day: How Mobile Technology Can Support Individuals to Adopt Pro-Environmental Behaviors

The pressing issue of climate change requires humanity to reduce its ecological footprint drastically. While policymakers and companies must ensure the availability of green options, individuals are requested to contribute to the reduction of carbon emissions substantially. However, even when individuals recognize the need for pro-environmental behaviors, they often have difficulty meeting their expectations. Mobile technology for sustainability has the potential to support them in overcoming this issue by providing the decisive impetus for environmentally friendly behavior. Drawing upon the affordance perspective, we conducted a longitudinal qualitative study with users of a mobile app that encourages individuals to take daily sustainable actions. We present the affordance strands made possible by the app's features and how they lead to environmentally-friendly behaviors. We could observe behavior change with the app’s features. We also identify enablers and obstacles to affordance actualization. Our study contributes to Green IS research at the individual level and provides practical implications for mobile technology providers

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

Long-Term Efficacy of Pulmonary Rehabilitation in Patients with Occupational Respiratory Diseases

Background: Pulmonary rehabilitation is a well-recognized treatment option in chronic obstructive lung disease improving exercise performance, respiratory symptoms and quality of life. In occupational respiratory diseases, which can be rather cost-intensive due to the compensation needs, very little information is available. Objectives: This study aims at the evaluation of the usefulness of pulmonary rehabilitation in patients with occupational respiratory diseases, partly involving complex alterations of lung function and of the sustainability of effects. Methods: We studied 263 patients with occupational respiratory diseases (asthma, silicosis, asbestosis, chronic obstructive pulmonary disease) using a 4-week inpatient rehabilitation program and follow-up examinations 3 and 12 months later. The outcomes evaluated were lung function, 6-min walking distance (6MWD), maximum exercise capacity (Wmax), skeletal muscle strength, respiratory symptoms, exacerbations and associated medical consultations, quality of life (SF-36, SGRQ), anxiety/depression (HADS) and Medical Research Council and Baseline and Transition Dyspnea Index scores. Results: Compared to baseline, there were significant (p < 0.05) improvements in 6MWD, Wmax and muscle strength immediately after rehabilitation, and these were maintained over 12 months (p < 0.05). Effects were less pronounced in asbestosis. Overall, a significant reduction in the rate of exacerbations by 35%, antibiotic therapy by 27% and use of health care services by 17% occurred within 12 months after rehabilitation. No changes were seen in the questionnaire outcomes. Conclusions: Pulmonary rehabilitation is effective even in the complex settings of occupational respiratory diseases, providing sustained improvement of functional capacity and reducing health care utilization. Copyright (C) 2012 S. Karger AG, Base

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 an Individual Prediction of Maximal Work Rate by 6-Minute Walk Distance and Further Measurements Reliable in Male Patients with Different Lung Diseases?

Background: In patients with chronic lung diseases, the work rate forendurance training is calculated by the maximal work rate (W-max).Because the assessment bears side effects, a prediction by easieraccessible tests would be of practical use. Objective: We addressed thereliability of predicting W-max on the basis of the 6-min walk distance(6MWD) test and a set of further parameters in patients with differentlung diseases. Methods: Baseline data of a longitudinal study including6MWD, W max, peripheral muscle force, lung function, fat-free mass anddyspnea (Modified Medical Research Council score) of 255 men withoccupational lung diseases (104 asthma, 69 asbestosis, 42 silicosis, 40 chronic obstructive pulmonary disease) were evaluated

The Power of Knowledge: A Literature Review on Socio-Technical Perspectives on Organizational Knowledge Management

In a fast-moving world with complex organizational structures and geographic dispersion of employees, an efficient management of knowledge and related systems is crucial for an organizations’ competitive advantage. In this paper we examine social and technological aspects that influence how individuals can be motivated to share and create knowledge by conducting a systematic literature review. As a result, we present a holistic view on the social and technical perspectives of the organizations’ knowledge management thereby outlining the need for an integrated consideration of these two dimensions. Moreover, we place actual social developments and innovative technologies in the context of this research field and outline the need for future academic discussions