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Decision support for efficient XAI services - A morphological analysis, business model archetypes, and a decision tree
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2022 | Electronic Markets | Citations: 2
Authors: Gerlach, Jana; Hoppe, Paul; Jagels, Sarah; Licker, Luisa; Breitner, Michael H.

Abstract: The black-box nature of Artificial Intelligence (AI) models and their associated ... Expand

Abstract: The black-box nature of Artificial Intelligence (AI) models and their associated explainability limitations create a major adoption barrier. Explainable Artificial Intelligence (XAI) aims to make AI models more transparent to address this challenge. Researchers and practitioners apply XAI services to explore relationships in data, improve AI methods, justify AI decisions, and control AI technologies with the goals to improve knowledge about AI and address user needs. The market volume of XAI services has grown significantly. As a result, trustworthiness, reliability, transferability, fairness, and accessibility are required capabilities of XAI for a range of relevant stakeholders, including managers, regulators, users of XAI models, developers, and consumers. We contribute to theory and practice by deducing XAI archetypes and developing a user-centric decision support framework to identify the XAI services most suitable for the requirements of relevant stakeholders. Our decision tree is founded on a literature-based morphological box and a classification of real-world XAI services. Finally, we discussed archetypical business models of XAI services and exemplary use cases. Collapse

Semantic filters: DataRobot

Topics: explainable artificial intelligence business model decision support artificial intelligence website

Methods: decision tree classification cluster analysis computational algorithm literature study k-means clustering
Information Technology Firms: Creating Value through Digital Disruption
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2019 | Communications of the Association for Information Systems | Citations: 2
Authors: Templeton, Gary F.; Petter, Stacie; French, Aaron M.; Larsen, Kai R.; Pace, Ben

Abstract: Information technology (IT) firms compose the majority of the most highly valued ... Expand

Abstract: Information technology (IT) firms compose the majority of the most highly valued corporations in the world based on market capitalization. To date, only Apple and Amazon—both IT companies—have reached or nearly reached a USD trillion-dollar market capitalization. The value that IT provides speaks to how managers exploit disruptive technologies to create value in both IT and non-IT firms. A panel held at the 2018 Americas Conference on Information Systems (AMCIS) discussed various ways in firms build value around IT through successful management. This paper reports on the panel discussion from a variety of perspectives, which include practitioner and researcher worldviews. This panel report also provides a sample frame that researchers can use in quantitative research involving IT firms and advocates for increased research to understand the wide range of strategies IT firms use to create value. Collapse

Semantic filters: DataRobot

Topics: social network communication service infrastructure information system use digital disruption mobile application

Methods: literature sample machine learning

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Decision support for efficient XAI services - A morphological analysis, business model archetypes, and a decision tree

Information Technology Firms: Creating Value through Digital Disruption