Dynamics of Trust: Unpacking Trust in Human-AI Collaboration in Decision-Making

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Baduna, Maryam; Hylving, Lena

Abstract: This literature review examines trust in AI-augmented decision-making systems i ... Expand

Abstract: This literature review examines trust in AI-augmented decision-making systems in collaborative settings. The analysis suggests that human characteristics, AI characteristics, the decision-making environment, and the collaboration setting are antecedents of human trust in AI. This literature review contributes to the theoretical knowledge of trust with a dynamic learned trust framework, which represents an integrated understanding of trust in AI in human-AI collaborative decision-making. The review also provides practical implications for AI designers and implementors for improving the trustworthiness and adoption of AI for human-AI collaboration. By providing insight for researchers and audiences in information systems, organization and management, this paper can serve as a starting point for investigating the nuances, complexities and dynamics of trust in human-AI relationships. Collapse

Topics: decision making artificial intelligence human AI collaboration human computer interaction expert system

Methods: literature study literature sample computational algorithm synthesis machine learning

Explainable artificial intelligence in information systems: A review of the status quo and future research directions

2023 | Electronic Markets | Citations: 4

Authors: Brasse, Julia; Broder, Hanna Rebecca; Förster, Maximilian; Klier, Mathias; Sigler, Irina

Abstract: The quest to open black box artificial intelligence (AI) systems evolved into an ... Expand

Abstract: The quest to open black box artificial intelligence (AI) systems evolved into an emerging phenomenon of global interest for academia, business, and society and brought about the rise of the research field of explainable artificial intelligence (XAI). With its pluralistic view, information systems (IS) research is predestined to contribute to this emerging field; thus, it is not surprising that the number of publications on XAI has been rising significantly in IS research. This paper aims to provide a comprehensive overview of XAI research in IS in general and electronic markets in particular using a structured literature review. Based on a literature search resulting in 180 research papers, this work provides an overview of the most receptive outlets, the development of the academic discussion, and the most relevant underlying concepts and methodologies. Furthermore, eight research areas with varying maturity in electronic markets are carved out. Finally, directions for a research agenda of XAI in IS are presented. Collapse

Topics: explainable artificial intelligence artificial intelligence user requirement electronic market user experience

Methods: literature study literature sample cluster analysis synthesis machine learning

Theories: information systems theory activity theory agency theory attribution theory cognitive fit theory

Natural Language Processing for Medical Texts – A Taxonomy to Inform Integration Decisions into Clinical Practice

2023 | International Conference on Information Systems | Citations: 0

Authors: Braun, Marvin; Kolbe, Lutz; Neumann, Caspar

Abstract: Electronic health records (EHR) have significantly amplified the volume of info ... Expand

Abstract: Electronic health records (EHR) have significantly amplified the volume of information accessible in the healthcare sector. Nevertheless, this information load also translates into elevated workloads for clinicians engaged in extracting and generating patient information. Natural Language Process (NLP) aims to overcome this problem by automatically extracting and structuring relevant information from medical texts. While other methods related to artificial intelligence have been implemented successfully in healthcare (e.g., computer vision in radiology), NLP still lacks commercial success in this domain. The lack of a structured overview of NLP systems is exacerbating the problem, especially with the emergence of new technologies like generative pre-trained transformers. Against this background, this paper presents a taxonomy to inform integration decisions of NLP systems into healthcare IT landscapes. We contribute to a better understanding of how NLP systems can be integrated into daily clinical contexts. In total, we reviewed 29 papers and 36 commercial NLP products. Collapse

Topics: health information system artificial intelligence database system healthcare data information technology infrastructure

Methods: natural language processing computational algorithm information extraction literature sample NLP application

A Design Research Journey

2023 | Communications of the Association for Information Systems | Citations: 2

Authors: Gregor, Shirley

Abstract: ... Expand

Abstract: Collapse

Topics: expert system mainframe

Methods: design science action design research theory development qualitative coding action research

Disentangling the Tension Between Automation and Augmentation with Artificial Intelligence in Healthcare

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Grüning, Maximilian; Trenz, Manuel; Santos, Daniel Pinto dos

Abstract: Artificial Intelligence (AI) has the potential to be a powerful tool for the fu ... Expand

Abstract: Artificial Intelligence (AI) has the potential to be a powerful tool for the future of medical professionals. However, we recognize a tension between AI independence (automation) and human involvement (augmentation) in medical decision-making. To resolve this tension, we conducted a systematic literature review to gain an overview of the current knowledge of AI in healthcare. In this systematic literature review, we search and analyze the leading journals in management and information systems for a period from 2012 to 2022. We find that several tasks related to diagnosis, treatment, or administrative work can be effectively automated or augmented with AI. We contribute to information systems research by highlighting possible scenarios for the effective use of AI in medical decision-making. Understanding and mitigating these tensions are particularly important for medical decision-makers, regulators, and managers who are struggling with guidelines for the appropriate use of AI and certification of accountability. Collapse

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

Methods: literature sample structured literature research literature study artificial neural network business process modeling

Guidance in Business Intelligence & Analytics Systems: A Review and Research Agenda

2023 | European Conference On Information Systems | Citations: 0

Authors: Gunklach, Jonas; Nadj, Mario

Abstract: While the data amount grows exponentially, the number of people with analytical ... Expand

Abstract: While the data amount grows exponentially, the number of people with analytical and technical skills is only slowly increasing. This skill gap is putting pressure on the labor market and increasing the need for personnel with these skills. At the same time, companies are forced to think of alternative ways to empower their less-skilled workforce to take on Business Intelligence and Analytics (BI&A) tasks. One promising attempt to address these challenges may turn to the concept of guidance. However, the current body of research on guidance in BI&A systems is scattered and lacks a structured investigation from which future research avenues can be derived. To address this gap, this article analyzes five categories, namely BI&A phases, guidance degree, guidance generation, user roles, and interactivity form. Reviewing 82 articles, our contribution is to synopsize articles on guidance in BI&A systems and to suggest five research avenues. Collapse

Topics: analytical information system data visualization data quality business intelligence artificial intelligence

Methods: exploratory data analysis machine learning literature sample time series analysis longitudinal research

AI Labor Markets: Toward a Dynamic Skills-Based Approach to Measurement

2023 | International Conference on Information Systems | Citations: 0

Authors: Kim, Jeongmin; Rai, Arun; Lin, Yu-Kai

Abstract: Artificial intelligence (AI) is transforming the nature of work and reshaping l ... Expand

Abstract: Artificial intelligence (AI) is transforming the nature of work and reshaping labor markets. Viewing labor as a bundle of skills, recent research has analyzed AI skills and offered important insights about the impacts of AI on labor markets. We add to this ongoing discourse and argue that taking a dynamic skill-based approach to measurement is critical: just like the development of AI is emergent and ever-evolving, so are AI skills. Taking stock of the literature, we show that existing studies tend to take a static approach to measuring AI skills, which fails to fully reflect the dynamic phenomenon of AI skills and could cause measurement errors. We propose a dynamic co-occurrence method and demonstrate that it performs better than the extant static methods, which can cause severe Type I and II errors, omit emerging AI skills, and temporally over-and underestimate the demands for AI skills and jobs. Collapse

Topics: artificial intelligence online labor market artificial general intelligence expert system

Methods: literature study machine learning robustness check artificial neural network natural language processing

Using AI to Improve Sustainable Agricultural Practices: A Literature Review and Research Agenda

2023 | Communications of the Association for Information Systems | Citations: 0

Authors: Lakshmi, Vijaya; Corbett, Jacqueline

Abstract: The world is confronted with the grand challenge of food insecurity amidst grow ... Expand

Abstract: The world is confronted with the grand challenge of food insecurity amidst growing populations and the climate crisis. Artificial intelligence (AI) deployed in agricultural decision support systems (AgriDSS) raises both hopes and concerns for increasing agricultural productivity in sustainable ways. We conduct a scoping review to uncover the roadblocks to the use of AI-supported AgriDSS in sustainable agriculture. Based on the corpus of 121 articles, we find that the effective use of AI-supported AgriDSS is hindered at technical, social, ethical, and ecological levels. Then, drawing on the experiential learning perspective, we propose how conjoint experiential learning (CEL) can enhance sustainable agricultural practices by enhancing both AI and human learning and overcoming roadblocks in using AgriDSS. Based on this conceptual framework, we build a research agenda that suggests blind spots and possible directions for future research. Collapse

Topics: artificial intelligence decision support system human computer interaction human in the loop decision making

Methods: literature sample literature study computational algorithm qualitative coding artificial neural network

Context-Aware Service Modelling: A Knowledge-Centric Framework

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Le Dinh, Thang; Vu, Thi My Hang; Dam, Nguyen Anh Khoa; Ralyté, Jolita

Abstract: A context-aware service aims at proposing suitable solutions for customer situa ... Expand

Abstract: A context-aware service aims at proposing suitable solutions for customer situations to increase their satisfaction. This goal can only be achieved if the customer context is correctly taken into account by the service. Even though smart service systems and knowledge-based systems have been investigated in recent years, few studies have focused on how to reconcile the two perspectives: service science and knowledgecentric, in order to maximize the benefits of each field in context-aware service development. This paper aims at proposing a modeling framework for the conception of context-aware service systems. While taking contextual knowledge into consideration, the framework defines the key constructs of context-aware services as well as their relationships and proposes a method comprising a set of patterns and a process model guiding the application of these constructs in a specific domain. The application of the framework is briefly illustrated to model credit card services for the banking sector to validate its utility and applicability. Collapse

Topics: website business process management expert system

Methods: literature study business process modeling case study

The implementation of artificial intelligence in organizations: A systematic literature review

2023 | Information & Management | Citations: 0

Authors: Lee, Maggie C.M.; Scheepers, Helana; Lui, Ariel K.H.; Ngai, Eric W.T.

Abstract: This study seeks to thoroughly understand the organizational context in which Ar ... Expand

Abstract: This study seeks to thoroughly understand the organizational context in which Artificial Intelligence (AI) would be implemented, through a systematic review and analysis of articles published (up to 2021) in 31 journals on information systems, business, management, and operations management. Seventy themes are identified from the literature and categorized into organizational, information systems, technological, and people dimensions for the antecedents, challenges, guidelines, and consequences of AI implementation in organizations. A conceptual framework for understanding AI implementation in organizations is also proposed. This study provides a research agenda to guide future research and facilitate knowledge accumulation and creation on AI implementation. Collapse

Topics: artificial intelligence robotic process automation database system expert system accounting

Methods: literature study literature sample structured literature research business process modeling mixed method