How AI-Based Systems Can Induce Reflections: The Case of AI-Augmented Diagnostic Work

2023 | Management Information Systems Quarterly | Citations: 0

Authors: Abdel-Karim, Benjamin; Pfeuffer, Nicolas; Carl, K. Valerie; Hinz, Oliver

Abstract: This paper addresses a thus-far neglected dimension in human-artificial intelli ... Expand

Abstract: This paper addresses a thus-far neglected dimension in human-artificial intelligence (AI) augmentation: machine-induced reflections. By establishing a grounded theoretical-informed model of machine-induced reflection, we contribute to the ongoing discussion in information systems (IS) regarding AI and research on reflection theories. In our multistage study, physicians used a machine learning-based (ML) clinical decision support system (CDSS) to see if and how this interaction can stimulate reflective practice in the context of an X-ray diagnosis task. By analyzing verbal protocols, performance metrics, and survey data, we developed an integrative theoretical foundation to explain how ML-based systems can help stimulate reflective practice. Individuals engage in more critical or shallower modes depending on whether they perceive a conflict or agreement with these CDSS systems, which in turn leads to different levels of reflection depth. By uncovering the process of machine-induced reflections, we offer IS research a different perspective on how such AI-based systems can help individuals become more reflective, and consequently more effective, professionals. This perspective stands in stark contrast to the traditional, efficiency-focused view of MLbased decision support systems and also enriches theories on human-AI augmentation. Collapse

Topics: artificial intelligence decision making decision support system algorithmic transparency recommender system

Methods: cognitive walkthrough survey theory development qualitative interview Student's t-test

Theories: learning theory information systems theory theory of abduction

Input control and its signalling effects for complementors' intention to join digital platforms

2023 | Information Systems Journal | Citations: 2

Authors: Adam, Martin; Croitor, Evgheni; Werner, Dominick; Benlian, Alexander; Wiener, Martin

Abstract: Existing information systems (IS) research on platform control has largely focus ... Expand

Abstract: Existing information systems (IS) research on platform control has largely focused on examining how input control (i.e., the mechanisms used to control platform access) affects complementors' intentions and behaviours after their decision to join a digital platform. Yet, our understanding of how input control is perceived before this decision and how such perceptions influence prospective complementors' intention to join a platform is still nascent. In this regard, our study views input control as a salient signal that shapes prospective complementors' expected benefits and costs (i.e., their performance and effort expectancy), and ultimately their decision to join a digital platform. Drawing on signalling theory and the antecedent-benefit-cost (ABC) framework, we conducted a randomized online experiment in the context of donation-based crowdfunding. The experiment results offer empirical support for this view by showing that input control has distinct and complex signalling effects for prospective complementors. In particular, our findings reveal curvilinear and competing signalling effects, with perceived input control increasing both performance expectancy (at a decreasing rate) and effort expectancy (at an increasing rate). Also, we find that performance expectancy linearly increases prospective complementors' intention to join a platform, whereas effort expectancy linearly decreases their intention to do so. These findings imply that the overall relationship between perceived input control and intention to join follows an inverted U-shape curve, which means that neither a low nor a high, but a moderate degree of perceived input control maximizes prospective complementors' intention to join. In sum, the results of our study provide novel and important insights into the signalling role that perceived input control plays in shaping prospective complementors' decision to join a digital platform. Collapse

Topics: digital platform crowdsourcing crowdfunding behavioral intention digital ecosystem

Methods: experiment mediation analysis survey survey design theory development

Theories: signaling theory

Gamified monetary reward designs: Offering certain versus chance-based rewards

2023 | Information Systems Journal | Citations: 0

Authors: Adam, Martin; Reinelt, Annika; Roethke, Konstantin

Abstract: To motivate visitors to engage with websites, e-tailers widely employ monetary r ... Expand

Abstract: To motivate visitors to engage with websites, e-tailers widely employ monetary rewards (e.g., vouchers, discounts) in their website designs. With advances in user interface technologies, many e-tailers have started to offer gamified monetary reward designs (MRDs), which require visitors to earn the monetary reward by playing a game, rather than simply claiming the reward. However, little is known about whether and why gamified MRDs engage visitors compared to their non-gamified counterpart. Even less is known about the effectiveness of gamified MRDs when providing certain or chance-based rewards, in that visitors do or do not know what reward they will gain for successfully performing in the game. Drawing on cognitive evaluation theory, we investigate gamified MRDs with certain or chance-based rewards and contrast them to non-gamified MRDs with certain rewards in user registration systems. Our results from a multi-method approach encompassing the complementary features of a randomised field experiment (N = 651) and a randomised online experiment (N = 330) demonstrate differential effects of the three investigated MRDs on user registration. Visitors encountering either type of gamified MRD are more likely to register than those encountering a non-gamified MRD. Moreover, gamified MRDs with chance-based rewards have the highest likelihood of user registrations. We also show that MRDs have distinct indirect effects on user registration via anticipated experiences of competence and sensation. Overall, the paper offers theoretical insights and practical guidance on how and why gamified MRDs are effective for e-tailers. Collapse

Topics: website electronic mail electronic commerce gamification website design

Methods: experiment randomized field experiment survey experimental task mixed method

Theories: cognitive evaluation theory self determination theory

Too Tired and in Too Good of a Mood to Worry About Privacy: Explaining the Privacy Paradox Through the Lens of Effort Level in Information Processing

2023 | Information Systems Research | Citations: 0

Authors: Alashoor, Tawfiq; Keil, Mark; Smith, H. Jeff; McConnell, Allen R.

Abstract: The confluence of digital transactions, growing cybersecurity threats, and the i ... Expand

Abstract: The confluence of digital transactions, growing cybersecurity threats, and the internet of the future (e.g., web 3.0 and the metaverse) have made information privacy increasingly important to consumers and companies that rely on consumers willingly sharing their personal information. Although information privacy has been of interest to researchers for decades and much has been learned, one thing that perplexes scholars is the privacy paradox, which we define as a mismatch between stated privacy concerns and actual disclosure behaviors. In this paper, we shed light on this phenomenon and show that low-effort information processing triggered by cognitive depletion (Experiment 1), positive mood (Experiment 2), or both (Experiment 3) significantly attenuates the association between stated privacy concerns and disclosure behaviors. These findings do not indicate that individuals do not care about privacy because we find consistent evidence in the three experiments for a significant negative association between stated privacy concerns and disclosure behaviors when individuals have sufficient cognitive capacity (Experiment 1), experience a negative (or neutral) mood (Experiment 2), or have sufficient cognitive capacity coupled with a negative mood state (Experiment 3). Our findings reveal that the paradox is neither an absolute phenomenon nor a myth, but its existence is conditional on contextual factors, including psychological factors related to information processing. We discuss our contribution to privacy theory and provide implications for consumers, companies, and policymakers. History: Alessandro Acquisti, Senior Editor; Idris Adjerid, Associate Editor. Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.1182. Collapse

Topics: information privacy concern privacy decision making mobile application task productivity

Methods: experiment descriptive statistic statistical hypothesis test theory development Student's t-test

Theories: elaboration likelihood model

D&L: A Natural Language Processing Based Approach for Protecting Sensitive Information from Shoulder Surfing Attacks

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Aldossari, Marran; Zhang, Dongsong

Abstract: Despite the increasing attention and research effort, how to protect sensitive ... Expand

Abstract: Despite the increasing attention and research effort, how to protect sensitive information from shoulder surfing attacks is still under studied. Existing methods for protecting sensitive textual content on users' screens from shoulder surfing attacks have various limitations, including ineffectiveness, insufficient protection of sensitive information, low usability, and high cognitive workload. To address those limitations, this paper proposes, develops, and evaluates a new solution called "detection and labeling" (D&L), which uses NLP techniques to automatically detect and label sensitive information in the textual content. The labeled and hidden sensitive information is then read to users through their headphones upon their clicking a label. Evaluation results demonstrate that D&L improves protection, enhances usability, reduces users' cognitive workload, and allows faster browsing speed compared to the baseline methods. Collapse

Topics: electronic mail laptop computer usability privacy perceived ease of use

Methods: survey parametric test experiment Tukey HSD for post poc analysis ANOVA

When Reflection Hurts: The Effect of Cognitive Processing Types on Organizational Adaptation to Discontinuous Change

2023 | Organization Science | Citations: 1

Authors: Alves, Marlon Fernandes Rodrigues; Vastola, Vincenzo; Vasconcelos Ribeiro Galina, Simone; Zollo, Maurizio

Abstract: Technological breakthroughs, institutional disruptions, and natural disasters of ... Expand

Abstract: Technological breakthroughs, institutional disruptions, and natural disasters often alter the course of organizations and entire industries. Such discontinuous changes threaten organizations’ survival by affecting the value of the knowledge accumulated in routines and capabilities. Although it is widely acknowledged that managerial cognition is a critical antecedent of organizational responses to discontinuous change, the role of type 1 (intuitive) and type 2 (reflective) processing in the adaptation of shared patterns of behavior, that is, routines, remains understudied. Drawing on dual-process theory, we propose that particular features of type 1 processing render this approach superior to type 2 processing, especially in highly ambiguous environments in which information is limited and difficult to verify. We tested our hypotheses in a longitudinal experiment linking individual-level factors with organizational-level practices of routine adaptation. Experienced managers, paired in 80 groups, developed routines in a first round of a simulation game; in a second round, we then introduced a discontinuous change making previous routines obsolete in order to observe how they adapted. The data show that priming type 1 processing facilitates organizational adaptation more than type 2 processing by providing faster, more routinized, efficiently coordinated, and optimal responses. In addition, type 1 appears to be more functional in highly ambiguous environments, whereas type 1 and type 2 processes yield similar levels of performance under low levels of ambiguity. Overall, our study advances the understanding of the nondeliberative dimension of organizational adaptation to discontinuous change.History: This paper has been accepted for the Organization Science Special Issue on Experiments in Organizational Theory.Funding: This work was supported by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Finance Code 001).Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2021.1517. Collapse

Topics: decision making strategic management innovation management problem solving task productivity

Methods: experiment longitudinal research parametric test ANOVA statistical hypothesis test

Theories: dual-system theory dynamic capabilities theory

How Does AI-Work Interaction Affect Individuals Behavior? The Role of Appraisals

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Ansari, Kimia; Abouei, Mahdi; Ghasemaghaei, Maryam

Abstract: Artificial intelligence (AI) has become a trend in capturing valuable insights ... Expand

Abstract: Artificial intelligence (AI) has become a trend in capturing valuable insights in organizations that were not achievable previously. Despite the anticipated benefits of implementing AI, the outcomes reveal contradictions. This study elaborates on the role of new AI-work interaction (in terms of augmentation and automation) in such seemingly incongruent results using the transactional theory of stress. Specifically, we propose that depending on individuals' perceived expertise, they may perceive such a new interaction either as inspirational or impeding. Therefore, if individuals appraise new AI-work interactions as possibly harmful and find that they do not have enough expertise to cope efficiently, they will likely withdraw and resist AI use. However, if they appraise the situation as potentially positive and find themselves highly capable of efficiently dealing with it, they will try to increase the effort to meet environmental demands and not resist the use of AI. Collapse

Topics: artificial intelligence organizational change

Methods: survey statistical power analysis survey design experimental task experiment

Similar Affordances, Different Use Practices? An Investigation of Socio-Cultural Contexts in Facebook, Instagram and Twitter

2023 | International Conference on Information Systems | Citations: 0

Authors: Arslan, Kader; Trier, Matthias

Abstract: ... Expand

Abstract: Collapse

Topics: Twitter Instagram Facebook affordance user experience

Methods: survey robustness check survey design nonparametric test literature study

Theories: theory of affordance

Counterfactual Explanations for Incorrect Predictions Made by AI Models

2023 | International Conference on Information Systems | Citations: 0

Authors: Asrzad, Amir; Li, Xiaobai

Abstract: Advanced AI models are powerful in making accurate predictions for complex prob ... Expand

Abstract: Advanced AI models are powerful in making accurate predictions for complex problems. However, these models often operate as black boxes. This lack of interpretability poses significant challenges, especially in high-stakes applications such as finance, healthcare, and criminal justice. Explainable AI seeks to address the challenges by developing methods that can provide meaningful explanations for humans to understand. When black box models are used for prediction, they inevitably produce errors. It is important to appropriately explain incorrect predictions. This problem, however, has not been addressed in the literature. In this study, we propose a novel method to provide explanations for misclassified cases made by black box models. The proposed method takes a counterfactual explanation approach. It builds a decision tree to find the best counterfactual examples for explanations. Incorrect predictions are rectified using a trust score measure. We validate the proposed method in an evaluation study using real-world data. Collapse

Topics: artificial intelligence explainable artificial intelligence local interpretable model agnostic explanation decision making enterprise information system

Methods: machine learning decision tree classification literature study random forest classification experiment

The Consequences of Rating Inflation on Platforms: Evidence from a Quasi-Experiment

2023 | Information Systems Research | Citations: 0

Authors: Aziz, Arslan; Li, Hui; Telang, Rahul

Abstract: Informative online ratings enable digital platforms to reduce the search cost fo ... Expand

Abstract: Informative online ratings enable digital platforms to reduce the search cost for buyers to find good sellers. However, rating inflation, a phenomenon in which average rating increases and rating variance across listings decreases, threatens the informativeness of ratings. We empirically identify the consequences of rating inflation by conducting a quasi-experiment with a digital platform that exogenously changed its rating display rule in a treated neighborhood, which resulted in rating inflation. Using a differences-in-differences approach, we find that platforms benefit from one aspect of rating inflation: user purchases and seller sales increase because of the increased average rating. However, they also face negative consequences: rating inflation causes a decrease in user trial and a greater concentration of sales among popular restaurants. Overall, our results illustrate the potential consequences of rating inflation that platforms need to consider when designing and managing their rating system.History: Xiaoquan (Michael) Zhang, Senior Editor; Gordon Burtch, Associate Editor.Supplemental Material: The online appendices are available at https://doi.org/10.1287/isre.2022.1134. Collapse

Topics: digital platform mobile application word of mouth ease of use consumer behavior

Methods: experiment pilot experiment experimental group robustness check quasi experiment