The Use and Effects of Knowledge-Based System Explanations: Theoretical Foundations and a Framework for Empirical Evaluation

By Jasbir Singh Dhaliwal, Izak Benbasat. 1996

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Citations in the corpus

Explanation in Human-AI Systems: A Literature Meta-Review, Synopsis of Key Ideas and Publications, and Bibliography for Explainable AI (2019, background): “…era, there was substantial research attempting to show that expert systems that provided and explanations had greater impact on reasoning (cf. Dhaliwal and Benbasat, 1996; Eining and Door, 1991; Murphy, 1990), with the effect depending on the skill level of the users (Lamberti and Wallace,…”
Designs for explaining intelligent agents (2009, background): “They also realized early that providing explanations contributed to the acceptance of the system by its intended users, in this case, physicians and medical students (Dhaliwal and Benbasat, 1996).”
Expert system methodologies and applications - a decade review from 1995 to 2004 (2005, background): “The four main components of KBS are usually distinguished as: a knowledge base, an inference engine, a knowledge engineering tool, and a specific user interface ( Dhaliwal & Benbasat, 1996 ).”
A systematic review and taxonomy of explanations in decision support and recommender systems (2017, background): “2 There is a large number of surveys that provide an overview of explanations published elsewhere (Tintarev and Masthoff 2007b, 2011; Swartout and Moore 1993; Chandrasekaran et al. 1989; Dhaliwal and Benbasat 1996; Gregor and Benbasat 1999; Moulin et al. 2002; Lacave and Díez 2002, 2004; Sørmo et al”
Explainable Artificial Intelligence: Objectives, Stakeholders, and Future Research Opportunities (2020, background): “…improved understanding about the system, consequently influencing the effectiveness and efficiency of judgmental decision making, as well as on the perception of the system’s usefulness, ease of use, satisfaction, and trust (Dhaliwal & Benbasat, 1996; Mao & Benbasat, 2000; Ye & Johnson, 1995).”
Knowledge warehouse: an architectural integration of knowledge management, decision support, artificial intelligence and data warehousing (2002, background): “Such a research thrust, based on the lens model [8] and [36], would provide a missing link in the current research [13].”
Explanatory Power of Intelligent Systems : A Research Framework (2004, background): “Dhaliwal and Benbasat (1996) distinguish between feedforward versus feedback advice, using the cognitive feedback paradigm (Todd and Hammond, 1956).”
Recommendation Agents for Electronic Commerce: Effects of Explanation Facilities on Trusting Beliefs (2007, background): “KBS explanations deliver knowledge about a KBS’s actions to make it more transparent to its us-ers—what the system does, how it works, and why its actions are appropriate [19, 28].”
Studying Knowledge Management in Information Systems Resarch: Discourses and Theoretical Assumptions (2002, background): “…is a great divergence of knowledge management related topics covered in the normative discourse, one unifying theme is that much of the research frames the research question in the context of problem solving and decision-making tasks (e.g., Dhaliwal and Benbasat 1996; Zhu et al. 1997; Gray 2000).”
Knowledge management technologies and applications - literature review from 1995 to 2002 (2003, background): “Four main components of KBS are usually distinguished: a knowledge base, an inference engine, a knowledge engineering tool, and a specific user interface (Dhaliwal & Benbasat, 1996).”