Blame Ascriptions Toward Autonomous Agents

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Publicado en:ProQuest Dissertations and Theses (2025)
Autor principal: Killoran, Jayson Andrew
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ProQuest Dissertations & Theses
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100 1 |a Killoran, Jayson Andrew 
245 1 |a Blame Ascriptions Toward Autonomous Agents 
260 |b ProQuest Dissertations & Theses  |c 2025 
513 |a Dissertation/Thesis 
520 3 |a As autonomous agents become embedded in organizational and everyday contexts, humans are increasingly delegating tasks to them. Yet when undesirable outcomes occur, people may blame the autonomous agent. This thesis investigates how blame is socially expressed, referred to as blame ascriptions, toward autonomous agents following IS delegation and undesirable outcomes.I present the results of a three-phased literature review in Chapter 2. Drawing from multiple theoretical perspectives, I develop a conceptual model and theoretical propositions in Chapter 3 that organize the process of ascribing blame toward autonomous agents into Triggering Blame, Enacting Blame, and Diagnosing Blame. Using a theoretical typology, I posit three unique blame ascriptions toward autonomous agents: Diminished Control, Ignorance, and Condemnation.Chapter 4 presents the results of a qualitative study involving 34 interviews across three domains, where I validate the proposed narratives and uncover a fourth narrative called Erosion of Skills. These narratives reveal that humans ascribe blame toward autonomous agents for superseding human control, confounding human judgment, committing moral harm, or diminishing human skills. Chapter 5 presents the results of a quantitative study, which uses an experimental vignette design to examine how the perceived agency attributes of autonomous agents influence blame ascription and IS delegation. The findings show that the perceived agency attributes of autonomy and inscrutability lead to increased blame ascription, blame ascription is negatively associated with IS delegation, and reflection may reduce the ascription of blame.This research contributes to information systems scholarship by theorizing blame ascription as a socially constructed and narratively expressed response to undesirable outcomes perceived to be caused by autonomous agents. Contrary to prevailing research that emphasizes the negative implications of blame, this thesis demonstrates that certain forms of blame ascriptions can serve a productive role in diagnosing outcomes and guiding future design and use practices. Moreover, the results of the two studies suggest the importance of context in the ascription of blame, and that reflection may play a pivotal role in the relationship between the enactment of a blame ascription and future IS delegation to autonomous agents. 
653 |a Higher education 
653 |a Delegation of authority 
653 |a Structural equation modeling 
653 |a Decision making 
653 |a Autonomous vehicles 
653 |a Ethics 
653 |a Emotions 
653 |a Boundary conditions 
653 |a Chatbots 
653 |a Artificial intelligence 
653 |a Automotive engineering 
653 |a Management 
653 |a Mathematics 
653 |a Transportation 
773 0 |t ProQuest Dissertations and Theses  |g (2025) 
786 0 |d ProQuest  |t ProQuest Dissertations & Theses Global 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3283373825/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3283373825/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch