HUMAN-AI COLLABORATION IN ORGANISATIONS: A LITERATURE REVIEW ON ENABLING VALUE CREATION

2023 | European Conference On Information Systems | Citations: 0

Authors: Raftopoulos, Marigo; Hamari, Juho

Abstract: ... Expand

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Topics: artificial intelligence value creation systems development decision making database system

Methods: literature study qualitative content analysis machine learning literature sample structured literature research

Theories: socio technical theory dynamic capabilities theory sociotechnical systems theory

Building Trust in AI: A new Understanding of the Role of Reliability

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Schmid, Amelie; Wiesche, Manuel

Abstract: It is well known that trust represents a crucial success factor for the adoptio ... Expand

Abstract: It is well known that trust represents a crucial success factor for the adoption of a technology. Among others, the reliability of the technology has a direct impact on the process of building trust. In the present paper, it is claimed that there is a contradiction related to the impact of reliability on building trust between former technologies and AI with its specific characteristics. Moreover, the static relationship between the process of building trust in AI and the corresponding measures, as reported in the literature, require a new approach. To close this gap, an analysis of an AI implementation and operation within an international automotive supplier was conducted. Based on 17 interviews -as main outcome -workers accept a lower level of reliability without a negative impact on the process of building trust. In order to explain and understand this finding the importance of organizational measures for trust calibration are discussed. Collapse

Topics: artificial intelligence research and development explainable artificial intelligence weak AI

Methods: qualitative interview qualitative coding personal interview grounded theory business process modeling

Theories: failure mode and effects analysis

Ethical Marketing AI?A Structured Literature Review of the Ethical Challenges Posed by Artificial Intelligence in the Domains of Marketing and Consumer Behavior

2023 | HICSS | Citations: 0

Authors: Su, Yiran; Wang, Emma Junhong; Berthon, Pierre

Abstract: With the increasing use of AI in marketing, ethical repercussions are beginning ... Expand

Abstract: With the increasing use of AI in marketing, ethical repercussions are beginning to emerge. From privacy issues, through discrimination of marginalized groups, to emergent systemic social distortions, AI is changing the marketing ethical landscape. In this paper we conduct a structured literature review of the emerging ethical issues posed by AI in the domains of marketing and consumer behavior. We identify three clusters of ethical issues (algorithm, society and existential) and map these to the marketing domains of systems, brands, and consumers. We conclude that the field of ethical marketing AI is still very much in its infancy, but such is the rate of development ethical marketing AI is likely to become important field for academics and practitioners alike. Collapse

Topics: artificial intelligence marketing management responsible artificial intelligence consumer behavior social media

Methods: literature study machine learning literature sample structured literature research computational algorithm

Theories: socio technical theory

What Makes AI Different? Exploring Affordances and Constraints - The Case of Auditing

2023 | European Conference On Information Systems | Citations: 0

Authors: Yang, Jiaqi; Marrone, Mauricio; Amrollahi, Alireza

Abstract: This study aims to gain a comprehensive understanding of the differences betwee ... Expand

Abstract: This study aims to gain a comprehensive understanding of the differences between classic IT and AI artefacts. To achieve this objective, the study employs a grounded theory literature review approach and analyses 81 papers related to the application of classic IT and AI artefacts in the auditing industry. Drawing on the Technology Affordances and Constraints Theory, we examine the actions that can be potentially enabled or restricted by using classic IT and AI artefacts. This analysis allows us to conceptualise and compare the affordances and constraints associated with these two types of artefacts. The study addresses the need for more research on AI from both social and technical perspectives. Our findings may facilitate practitioners in improving their business processes and promoting effective collaboration between humans and AI. Collapse

Topics: artificial intelligence affordance auditing information system artificial general intelligence weak AI

Methods: machine learning literature study image processing business process modeling design artifact

Theories: theory of affordance

Cognitive automation

2022 | Electronic Markets | Citations: 6

Authors: Engel, Christian; Ebel, Philipp; Leimeister, Jan Marco

Abstract: Facilitated by AI technology, the phenomenon of cognitive automation extends the ... Expand

Abstract: Facilitated by AI technology, the phenomenon of cognitive automation extends the scope of deterministic business process automation (BPA) through the probabilistic automation of knowledge and service work. By transforming work systems through cognitive automation, organizations are provided with vast strategic opportunities to gain business value. However, research lacks a unified conceptual lens on cognitive automation, which hinders scientific progress. Thus, based on a Systematic Literature Review, we describe the fundamentals of cognitive automation and provide an integrated conceptualization. We provide an overview of the major BPA approaches such as workflow management, robotic process automation, and Machine Learning-facilitated BPA while emphasizing their complementary relationships. Furthermore, we show how the phenomenon of cognitive automation can be instantiated by Machine Learning-facilitated BPA systems that operate along the spectrum of lightweight and heavyweight IT implementations in larger IS ecosystems. Based on this, we describe the relevance and opportunities of cognitive automation in Information Systems research. Collapse

Topics: artificial intelligence process automation system robotic process automation database system decision making

Methods: business process modeling machine learning structured literature research literature study deep learning

Theories: probability theory

AI meets Digital: A Critical Review on Artificial Intelligence in Digital Entrepreneurship

2022 | European Conference On Information Systems | Citations: 0

Authors: Gerling, Christoph; Meier, Philip; Koehler, Charlotte

Abstract: Driven by a reduction in the cost of data generation and computing power and si ... Expand

Abstract: Driven by a reduction in the cost of data generation and computing power and simultaneous advancement of mathematical methods, algorithms are becoming increasingly capable of mimicking human learning, profound judgment, and decision-making, even outperforming humans in doing so. This recent emergence of artificial intelligence (AI) seems to not only change the way how entrepreneurial endeavors operate but also the way how they emerge. In general, digital technologies are prone to render the processes and outcomes behind entrepreneurial endeavors less bounded and the locus of an entrepreneurial agency less predefined. Addressing the role of AI in this is only nascent so far. We thus suggest it is time to perform a critical review of the literature at the intersection of AI and digital entrepreneurship. Our investigation adopts a socio-technical lens to capture the state of the AI entrepreneurship literature and identify promising research avenues to trigger further discussions. Collapse

Topics: artificial intelligence digital entrepreneurship entrepreneurship database system spreadsheet

Methods: literature sample literature study machine learning structured literature research design artifact

Theories: socio technical theory

Applying XAI to an AI-based system for candidate management to mitigate bias and discrimination in hiring

2022 | Electronic Markets | Citations: 0

Authors: Hofeditz, Lennart; Clausen, Sünje; Rieß, Alexander; Mirbabaie, Milad; Stieglitz, Stefan

Abstract: Assuming that potential biases of Artificial Intelligence (AI)-based systems can ... Expand

Abstract: Assuming that potential biases of Artificial Intelligence (AI)-based systems can be identified and controlled for (e.g., by providing high quality training data), employing such systems to augment human resource (HR)-decision makers in candidate selection provides an opportunity to make selection processes more objective. However, as the final hiring decision is likely to remain with humans, prevalent human biases could still cause discrimination. This work investigates the impact of an AI-based system’s candidate recommendations on humans’ hiring decisions and how this relation could be moderated by an Explainable AI (XAI) approach. We used a self-developed platform and conducted an online experiment with 194 participants. Our quantitative and qualitative findings suggest that the recommendations of an AI-based system can reduce discrimination against older and female candidates but appear to cause fewer selections of foreign-race candidates. Contrary to our expectations, the same XAI approach moderated these effects differently depending on the context. Collapse

Topics: artificial intelligence explainable artificial intelligence decision making personality IT skill

Methods: survey moderation analysis experimental group qualitative content analysis survey design

Artificial Intelligence (AI) and Digital Transformation in the Insurance Market: A Case Study Analysis of BGL Group

2022 | HICSS | Citations: 0

Authors: Holland, Christopher

Abstract: Artificial Intelligence (AI) is transforming the insurance industry and there ar ... Expand

Abstract: Artificial Intelligence (AI) is transforming the insurance industry and there are many examples in the business press and at industry conferences. However, there is a paucity of detailed conceptual analysis and evaluation of AI technology that places AI in a strategic context and considers how different AI applications fit together and form a coherent picture. In this paper, a detailed case study of BGL group, a leading European insurance firm, is presented. A general business process model of insurance companies is used to structure the analysis. Five AI applications are described using an insurance firm-customer data flow diagram, which illustrates the marketing impact of AI technology and shows the nature of the business value creation process. The results are generalized into an AI customer lifecycle model, which has broad applicability to digital transformation projects. The likely future direction of AI in insurance is outlined and further research opportunities are identified. Collapse

Topics: artificial intelligence weak AI business model business process management digital transformation

Methods: case study focus group usability testing machine learning

Review of Research on Human Trust in Artificial Intelligence

2022 | International Conference on Information Systems | Citations: 9

Authors: Li, Yonggang; Hahn, Jungpil

Abstract: Artificial Intelligence (AI) represents today's most advanced technologies that ... Expand

Abstract: Artificial Intelligence (AI) represents today's most advanced technologies that aim to imitate human intelligence. Whether AI can successfully be integrated into society depends on whether it can gain users' trust. We conduct a comprehensive review of recent research on human trust in AI and uncover the significant role of AI's transparency, reliability, performance, and anthropomorphism in developing trust. We also review how trust is diversely built and calibrated, and how human and environmental factors affect human trust in AI. Based on the review, the most promising future research directions are proposed. Collapse

Topics: artificial intelligence robotic usability human computer interaction privacy

Methods: literature study computational algorithm self reported survey

AI-based Conversational Agents for Customer Service – A Study of Customer Service Representative’ Perceptions Using TAM 2

2022 | International Conference on Business Informatics | Citations: 0

Authors: Sonntag, Martin; Mehmann, Jens; Teuteberg, Frank

Abstract: This study aimed to identify the various factors that may influence customer ser ... Expand

Abstract: This study aimed to identify the various factors that may influence customer service representatives’ perceptions of artificial intelligence (AI)-based conversational agents (CAs) for customer service. By analyzing 180 publications, a conceptual research model is developed for identifying the factors that may influence customer service representatives’ perceptions of AI-based CAs for customer service. The underlying conceptual research model comprises ten factors. The study is grounded in the application of the Technology Acceptance Model 2 (TAM 2) approach. The research model is empirically evaluated with survey data from 128 participants. Our results show that the direct positive effect of subjective norm on customer service representatives’ perception of using AIbased CAs in customer service decreases with increasing experience. Moreover, our results reveal new insights regarding trust. The results of this study provide an overview of the predominant characteristics of the influencing factors of customer service representatives’ perceptions of AI-based CAs for customer service. Collapse

Topics: customer service artificial intelligence perceived ease of use data quality weak AI

Methods: survey data transformation literature sample factor analysis exploratory factor analysis

Theories: technology acceptance model