The New Dream Team? A Review of Human-AI Collaboration Research From a Human Teamwork Perspective

A new generation of information systems based on artificial intelligence (AI) transforms the way we work. However, existing research on human-AI collaboration is scattered across disciplines, highlighting the need for more transparency about the design of human-AI collaboration in organizational contexts. This paper addresses this gap by reviewing the literature on human-AI collaboration through the lens of human teamwork. Our results provide insights into how emerging topics of human-AI collaboration are connected and influence each other. In particular, the review indicates that, with the increasing complexity of organizational settings, human-AI collaboration needs to be designed differently, and team maintenance activities become more important due to increased communicational requirements of humans. Our main contribution is a novel framework of temporal phases in human-AI collaboration, identifying the mechanisms that need to be considered when designing them for organizational contexts. Additionally, we use our framework to derive a future research agenda

EMPOWERING COMMUNITY HEALTH WORKERS WITH MOBILE HEALTH: LEARNINGS FROM TWO PROJECTS ON NON-COMMUNICABLE DISEASE CARE

Community-based healthcare is a promising approach to tackling workforce shortage in healthcare, especially in low- and middle-income countries. Community health workers (CHWs) are lay cadres that bridge healthcare disparities by living in the community where they should provide basic health services, mainly through education. However, high attrition rates and underperformance of these health workers limit the scope of such programs. In addition, mobile health is not the hoped-for silver bullet to solve the two challenges. This paper examines two pilot projects using mobile health for non-communicable disease care from an empowerment perspective. We propose design knowledge of mobile health for the structural empowerment of CHWs. Furthermore, we evaluate their psychological empowerment by analyzing mobile health\u27s intended and unintended consequences. Finally, our study demonstrates how the empowerment of CHWs could help overcome the persisting challenges and lead to a sustainable and resilient health system

Fitness First or Safety First? Examining Adverse Consequences of Privacy Seals in the Event of a Data Breach.

Data breaches are increasing, and fitness trackers have proven to be an ideal target, as they collect highly sensitive personal health data and are not governed by strict security guidelines. Nevertheless, companies encourage their customers to share data with the fitness tracker using privacy seals, gaining their trust without ensuring security. Since companies cannot guarantee security, the question arises on how privacy seals work after not keeping the security promise. This study examines the possibilities to mitigate the consequences of data breaches in advance to maintain the continuance intention. Expectation-confirmation theory (ECT) and privacy assurance statements as a shaping of privacy seals are used to influence customer expectations regarding the data security of fitness trackers in the run-up to a data breach. Results show that the use of privacy assurance statements leads to high-security expectations, and failure to meet these has a negative impact on satisfaction and thus continuance intention

The Double-Edged Sword of Health Data Breaches: A Comparison of Customer and Stock Price Perspectives on the Impact of Data Breaches of Response Strategies

Unauthorized access to personal health data, known as data breaches, causes multi-faceted adverse effects and damage. Companies are trying to counteract the impact on customer relationships through recovery strategies such as compensation. On the other hand, there is also a negative effect on the company's stock price. Here, the literature suggests an opposite effect of response strategies, but this has not been explored further until recently. Our study takes both perspectives into account and examines the impact of data breaches on the market valuation in the health sector through an event study. Our results show a controversial relationship: If companies offered compensation to their customers in response to a data breach, this had a negative effect on the company's stock price. Our paper discusses this finding and derives practical implications and lessons learned for response strategies in the case of recent data breaches in the health sector

Choose your words wisely! Understanding the strategic communication of differential privacy

As a possible solution addressing the growing tension for companies on wanting to collect data and not upset their customers through adverse events simultaneously, differential privacy (DP), an approach that allows the collection of data while ensuring privacy, is gaining in popularity. As many companies increasingly engage in deploying DP, they consequently try to communicate such efforts to their consumers. However, compared to traditional measures, DP has unique characteristics which pose special challenges in its communication. Despite this, prior research did not sufficiently address the user-perspective on DP. Consequently, we adopt an elaboration likelihood lens to investigate how two prevalent descriptions of DP are perceived. By conducting a between-subjects experiment (n=264) we identify powerful mediating effects in the perception of DP, not known before. We contribute to literature by demonstrating the full-mediation of these effects, and to practice by depicting how these can be incorporated in a successful communication strategy

Empowering community health workers with mobile health: learnings from two projects on non-communicable disease care

Community-based healthcare is a promising approach to tackling workforce shortage in healthcare, especially in low- and middle-income countries. Community health workers (CHWs) are lay cadres that bridge healthcare disparities by living in the community where they should provide basic health services, mainly through education. However, high attrition rates and underperformance of these health workers limit the scope of such programs. In addition, mobile health is not the hoped-for silver bullet to solve the two challenges. This paper examines two pilot projects using mobile health for non-communicable disease care from an empowerment perspective. We propose design knowledge of mobile health for the structural empowerment of CHWs. Furthermore, we evaluate their psychological empowerment by analyzing mobile health's intended and unintended consequences. Finally, our study demonstrates how the empowerment of CHWs could help overcome the persisting challenges and lead to a sustainable and resilient health system

THE NEW DREAM TEA(I)M? Rethinking Human-AI Collaboration based on Human Teamwork

The continuing rise of artificial intelligence (AI) creates a new frontier of information systems that has the potential to change the future of work. Humans and AI are set to complete tasks as a team, using their complementary strengths. Previous research investigated several aspects of human-AI collaboration, such as the impact of human-AI teams on performance and how AI can be designed to complement the human teammate. However, experiments are suffering from a lack of comparability due to the unlimited configurations, which ultimately limits their implications. In this study, we develop an overarching framework for experiments on human-AI collaboration, using human teamwork as a theoretical lens. Our framework provides a novel, temporal structure for the research domain. Thereby, emerging topics can be clustered sequentially

Really, What Are They Offering? A Taxonomy of Companies\u27 Actual Response Strategies after a Data Breach

Data breaches have become an everyday phenomenon. As a consequence, organizations no longer solely focus on prevention but also proactively prepare for the next data breach. A key element of these efforts is data breach response strategies that aim to retain trust and loyalty of the affected parties. Prior research provides important insights into the effects, causes, and conditions of effective response strategies. However, an underlying conceptualization of different forms of data breach response strategies is lacking. By analyzing the response strategies of 313 data breaches, we inductively derive a taxonomy of data breach response strategies. Our results suggest that response actions can be classified along eight dimensions including 22 distinct characteristics. Our research provides contributions to research and practice. The taxonomy provides a comprehensive framework and allows to link different research streams logically. Subsequently, the taxonomy helps managers to distinguish different data breach response strategies and implement suitable measures

A Double-Edged Sword of Involvement: On the Tension Between Customers’ Group Value and Self-Interest in Data Breach Response Processes

As data breaches continue to rise, customers exhibit heterogeneous expectations regarding the company\u27s response. Universal responses can show backfire effects since they fail to meet the expectations. Thus, the challenge arises that customer expectations must be known to mitigate the consequences while time is limited to publish the data breach announcement. By drawing on service failure, data breach, and justice research, we theorize that customer involvement provides a viable approach to this challenge. We argue that active customer involvement allows customers to formulate their expectations. Thus, enabling companies to leverage these expectations to provide tailored data breach responses. We test our hypotheses in a digital experiment (n=304). Our results provide a first indication that active customer involvement in a data breach drives positive group value and negative self-interest effects. We contribute to the data breach literature by revealing that customer involvement constitutes a suitable mechanism for identifying customer expectations

Doctors’ Dilemma – Understanding the Perspective of Medical Experts on AI Explanations

As a solution for the pressing issue in medicine of “black-box” artificial intelligence (AI), models that are hard to understand, explainable AI (XAI) is gaining in popularity. XAI aims at making AI more understandable by explaining its working, e.g., through human understandable explanations. However, while prior research found that such explanations must be adapted for the given expert group being addressed, we find limited work on explanations and their effect on medical experts. To address this gap, we conducted an online experiment with such medical experts (e.g., doctors, nurses) (n=204), to investigate how explanations can be utilized to achieve a causal understanding and respective usage of AI. Our results demonstrate and contribute to literature by identifying transparency and usefulness as powerful mediators, which were not known before. Additionally, we contribute to practice by depicting how these can be used by managers to improve the adoption of AI systems in medicine