Abstract Data-centric artificial intelligence (data-centric AI) represents an emerging paradigm that emphasizes the importance of enhancing data systematically and at scale to build effective efficient AI-based systems. The novel complements recent model-centric AI, which focuses on improving performance systems based changes in model using a fixed set data. objective this article is introduce practitioners researchers from field Business Information Systems Engineering (BISE) data-centric...

Abstract The field of artificial intelligence (AI) is advancing quickly, and systems can increasingly perform a multitude tasks that previously required human intelligence. Information facilitate collaboration between humans AI such their individual capabilities complement each other. However, there lack consolidated design guidelines for information facilitating the systems. This work examines how agent transparency affects trust task outcomes in context human-AI collaboration. Drawing on...

Research in artificial intelligence (AI)-assisted decision-making is experiencing tremendous growth with a constantly rising number of studies evaluating the effect AI and without techniques from field explainable (XAI) on human performance. However, as tasks experimental setups vary due to different objectives, some report improved user performance through XAI, while others only negligible effects. Therefore, this article, we present an initial synthesis existing research XAI using...

Recent work has proposed artificial intelligence (AI) models that can learn to decide whether make a prediction for an instance of task or delegate it human by considering both parties' capabilities. In simulations with synthetically generated context-independent predictions, delegation help improve the performance human-AI teams -- compared humans AI model completing alone. However, so far, remains unclear how perform and they perceive when are aware delegated instances them. experimental...

The storming of the U.S. Capitol on January 6, 2021 has led to killing 5 people and is widely regarded as an attack democracy. was largely coordinated through social media networks such Twitter "Parler". Yet little known regarding how users interacted Parler during Capitol. In this work, we examine emotion dynamics with regard heterogeneity across time users. For this, segment user base into different groups (e.g., Trump supporters QAnon supporters). We use affective computing infer emotions...

In recent years, the rapid development of AI systems has brought about benefits intelligent services but also concerns security and reliability. By fostering appropriate user reliance on an system, both complementary team performance reduced human workload can be achieved. Previous empirical studies have extensively analyzed impact factors ranging from task, behavior trust in context one-step decision making. However, tasks with complex semantics that require multi-step workflows remains...

In AI-assisted decision-making, a central promise of having human-in-the-loop is that they should be able to complement the AI system by overriding its wrong recommendations. practice, however, we often see humans cannot assess correctness recommendations and, as result, adhere or override correct advice. Different ways relying on have immediate, yet distinct, implications for decision quality. Unfortunately, reliance and quality are inappropriately conflated in current literature...

In AI-assisted decision-making, a central promise of having human-in-the-loop is that they should be able to complement the AI system by overriding its wrong recommendations. practice, however, we often see humans cannot assess correctness recommendations and, as result, adhere or override correct advice. Different ways relying on have immediate, yet distinct, implications for decision quality. Unfortunately, reliance and quality are inappropriately conflated in current literature...

Machine learning (ML) models are increasingly being used in application domains that often involve working together with human experts. In this context, it can be advantageous to defer certain instances a single expert when they difficult predict for the ML model. While previous work has focused on scenarios one distinct expert, many real-world situations several experts varying capabilities may available. work, we propose an approach trains classification model complement of multiple By...

Artificial intelligence (AI) can improve human decision-making in various application areas. Ideally, collaboration between humans and AI should lead to complementary team performance (CTP) -- a level of that neither them attain individually. So far, however, CTP has rarely been observed, suggesting an insufficient understanding the constituents human-AI contribute decision-making. This work establishes holistic theoretical foundation for developing complementarity. We conceptualize...

Data-centric artificial intelligence (data-centric AI) represents an emerging paradigm emphasizing that the systematic design and engineering of data is essential for building effective efficient AI-based systems. The objective this article to introduce practitioners researchers from field Information Systems (IS) data-centric AI. We define relevant terms, provide key characteristics contrast model-centric one, a framework distinguish AI related concepts discuss its longer-term implications...

Recent developments in Artificial Intelligence (AI) have fueled the emergence of human-AI collaboration, a setting where AI is coequal partner. Especially clinical decision-making, it has potential to improve treatment quality by assisting overworked medical professionals. Even though research started investigate utilization for its benefits do not imply adoption While several studies analyze criteria from technical perspective, providing human-centered perspective with focus on AI's...

Abstract As organizations accumulate vast amounts of data for analysis, a significant challenge remains in fully understanding these datasets to extract accurate information and generate real-world impact. Particularly, the high dimensionality lack sufficient documentation, specifically provision metadata, often limit potential exploit full value via analytical methods. To address issues, this study proposes hybrid approach metadata generation, that leverages both in-depth knowledge domain...

Service robots play an increasingly important role in the service sector. Drawing on moral psychology research, foundations theory as well computers-as-social-actors (CASA) paradigm, this experimental study containing of four online experiments examines extent to which or immoral behavior a robot affects customer responses during interaction. This contributes design science by defining, conceptualizing and operationalizing morality developing corresponding vignette basis manipulate (im)moral...

In AI-assisted decision-making, a central promise of having human-in-the-loop is that they should be able to complement the AI system by overriding its wrong recommendations. practice, however, we often see humans cannot assess correctness recommendations and, as result, adhere or override correct advice. Different ways relying on have immediate, yet distinct, implications for decision quality. Unfortunately, reliance and quality are inappropriately conflated in current literature...

With increasing servitization efficient delivery of maintenance, repair and overhaul services has become a top priority for many manufacturing companies. But, even though variety exact approximate solution methods have been developed vehicle routing problems, companies still heavily rely on manual dispatchers with little to no technical support. This paper outlines why the complex, dynamic deterministic nature real-world scheduling problems limits applicability published solutions problems....

Over the last years, rising capabilities of artificial intelligence (AI) have improved human decision-making in many application areas. Teaming between AI and humans may even lead to complementary team performance (CTP), i.e., a level beyond ones that can be reached by or individually. Many researchers proposed using explainable (XAI) enable rely on advice appropriately thereby reach CTP. However, CTP is rarely demonstrated previous work as often focus design explainability, while...