Two-Way Human-Agent Trust Relationships in Adaptive Cognitive Agent, Adaptive Tasking Scenarios: Literature Metadata Analysis

Kennedy, D. N.; Hidalgo, Maartje

doi:10.1007/978-3-030-78462-1_14

Cited by 2 publications

(5 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The hospitality literature has recently recognized the increasing role of AI in the design and delivery of services (Doborjeh et al, 2022). The AI agents have evolved to make decisions IJCHM 36,3 and act on behalf of the users without human intervention, which led to technology agency (Kennedy and Hidalgo, 2021). Agency reflects the capacity to make decisions and choices, perform actions and take the responsibility for the actions performed.…”

Section: Review Of Literature Theoretical Foundations: Technology Agencymentioning

confidence: 99%

“…Risk perceptions can also be related to the unpredictability of algorithmic decision-making, alongside a "black-box process" (Holland Michel, 2020) and the fear of losing knowledge and competencies (Adams et al, 2022). AI-based systems' dynamic and evolving nature makes their actions indeterminate and unpredictable over time (Kennedy and Hidalgo, 2021). Thus, consumers give up their sequential decision-making processes, e.g.…”

Section: Extending the Theoretical Foundationsmentioning

confidence: 99%

“…Autonomous AI-based systems have human-like social intelligence and cognitive capabilities, facilitating the acceptance of technology agency (Yu et al , 2021). AI-based agents with autonomous capabilities can process new encounters and learn, evolve and change (Kennedy and Hidalgo, 2021). They can assist users with tasks based on their preferences by automating tasks, processing, monitoring and customizing (Ozdemir et al , 2023).…”

Section: Review Of Literaturementioning

confidence: 99%

See 2 more Smart Citations

Letting AI make decisions for me: an empirical examination of hotel guests’ acceptance of technology agency

Morosan,

Dursun-Cengizci

2023

IJCHM

View full text Add to dashboard Cite

Purpose This study aims to examine hotel guests’ acceptance of technology agency – the extent to which they would let artificial intelligence (AI)-based systems make decisions for them when staying in hotels. The examination was conducted through the prism of several antecedents of acceptance of technology agency, including perceived ethics, benefits, risks and convenience orientation. Design/methodology/approach A thorough literature review provided the foundation of the structural model, which was tested using confirmatory factor analysis, followed by structural equation modeling. Data were collected from 400 US hotel guests. Findings The most important determinant of acceptance of technology agency was perceived ethics, followed by benefits. Risks of using AI-based systems to make decisions for consumers had a negative impact on acceptance of technology agency. In addition, perceived loss of competence and unpredictability had relatively strong impacts on risks. Research limitations/implications The results provide a conceptual foundation for research on systems that make decisions for consumers. As AI is increasingly incorporated in the business models of hotel companies to make decisions, ensuring that the decisions are perceived as ethical and beneficial for consumers is critical to increase the utilization of such systems. Originality/value Most research on AI in hospitality is either conceptual or focuses on consumers’ intentions to stay in hotels that may be equipped with AI technologies. Occupying a unique position within the literature, this study discusses the first time AI-based systems that make decisions for consumers. The value of this study stems from the examination of the main concept of technology agency, which was never examined in hospitality.

show abstract

Section: Review Of Literature Theoretical Foundations: Technology Agencymentioning

confidence: 99%

Section: Extending the Theoretical Foundationsmentioning

confidence: 99%

Section: Review Of Literaturementioning

confidence: 99%

See 1 more Smart Citation

Letting AI make decisions for me: an empirical examination of hotel guests’ acceptance of technology agency

Morosan,

Dursun-Cengizci

2023

IJCHM

View full text Add to dashboard Cite

show abstract

“…This paper develops a conversational method based on three creative writing strategies to enable a machine to communicate an unexpected risk. During a mission, humans and machines can align their understanding of a situation using communication -an exchange of information tokens (Kennedy and Hidalgo 2021). However, open world situations are more complex than a machine's reference ontology can represent, and the simple vocabulary and dialogue currently supported by artificial intelligence might not be enough to communicate a problem that was unanticipated (Kruijff et al 2015).…”

Section: Introductionmentioning

confidence: 99%

“…In addition, machine communication cannot yet emulate natural back-and-forth interaction (Li et al 2016), making it difficult to maintain a common understanding as a situation changes. In spite of these limits, ongoing 'human-in-the-loop' communication with machines is critical to maintaining trusted performance (Kennedy and Hidalgo 2021). The need for adaptive capabilities have been identified as critical by the National Security Commission on AI 2021, which forecasts that by 2025, human-machine teams should be able to "reason over changing contexts to flexibly adapt teaming strategy" (Schmidt et al 2021, p. 85).…”

Section: Introductionmentioning

confidence: 99%

Communicating Unnamable Risks: Aligning Open World Situation Models Using Strategies from Creative Writing

Cardier

2024

AAAI-SS

View full text Add to dashboard Cite

How can a machine warn its human collaborator about an unexpected risk if the machine does not possess the explicit language required to name it? This research transfers techniques from creative writing into a conversational format that could enable a machine to convey a novel, open-world threat. Professional writers specialize in communicating unexpected conditions with inadequate language, using overlapping contextual and analogical inferences to adjust a reader’s situation model. This paper explores how a similar approach could be used in conversation by a machine to adapt its human collaborator’s situation model to include unexpected information. This method is necessarily bi-directional, as the process of refining unexpected meaning requires each side to check in with each other and incrementally adjust. A proposed method and example is presented, set five years hence, to envisage a new kind of capability in human-machine interaction. A near-term goal is to develop foundations for autonomous communication that can adapt across heterogeneous contexts, especially when a trusted outcome is critical. A larger goal is to make visible the level of communication above explicit communication, where language is collaboratively adapted.

show abstract

Two-Way Human-Agent Trust Relationships in Adaptive Cognitive Agent, Adaptive Tasking Scenarios: Literature Metadata Analysis

Cited by 2 publications

References 35 publications

Letting AI make decisions for me: an empirical examination of hotel guests’ acceptance of technology agency

Letting AI make decisions for me: an empirical examination of hotel guests’ acceptance of technology agency

Communicating Unnamable Risks: Aligning Open World Situation Models Using Strategies from Creative Writing

Contact Info

Product

Resources

About