Human confidence in artificial intelligence and in themselves: The evolution and impact of confidence on adoption of AI advice

Chong, Leah; Zhang, Guanglu; Goucher-Lambert, Kosa; Kotovsky, Kenneth; Cagan, Jonathan

doi:10.1016/j.chb.2021.107018

Cited by 117 publications

(60 citation statements)

References 28 publications

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“…Trust can be seen as the specific beliefs about technology and the willingness to rely on technology in risky situations (Siau and Wang, 2018 ). Thus, trust might determine if and how individuals interact with AI (see also Glikson and Woolley, 2020 ; Chong et al, 2022 ) for distributed cognition. The question arises whether there are individual differences when it comes to trusting AI.…”

Section: Outlook On Distributed Cognition In An Ai-enhanced Futurementioning

confidence: 99%

Supporting Cognition With Modern Technology: Distributed Cognition Today and in an AI-Enhanced Future

Grinschgl

Neubauer

2022

Front. Artif. Intell.

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In the present article, we explore prospects for using artificial intelligence (AI) to distribute cognition via cognitive offloading (i.e., to delegate thinking tasks to AI-technologies). Modern technologies for cognitive support are rapidly developing and increasingly popular. Today, many individuals heavily rely on their smartphones or other technical gadgets to support their daily life but also their learning and work. For instance, smartphones are used to track and analyze changes in the environment, and to store and continually update relevant information. Thus, individuals can offload (i.e., externalize) information to their smartphones and refresh their knowledge by accessing it. This implies that using modern technologies such as AI empowers users via offloading and enables them to function as always-updated knowledge professionals, so that they can deploy their insights strategically instead of relying on outdated and memorized facts. This AI-supported offloading of cognitive processes also saves individuals' internal cognitive resources by distributing the task demands into their environment. In this article, we provide (1) an overview of empirical findings on cognitive offloading and (2) an outlook on how individuals' offloading behavior might change in an AI-enhanced future. More specifically, we first discuss determinants of offloading such as the design of technical tools and links to metacognition. Furthermore, we discuss benefits and risks of cognitive offloading. While offloading improves immediate task performance, it might also be a threat for users' cognitive abilities. Following this, we provide a perspective on whether individuals will make heavier use of AI-technologies for offloading in the future and how this might affect their cognition. On one hand, individuals might heavily rely on easily accessible AI-technologies which in return might diminish their internal cognition/learning. On the other hand, individuals might aim at enhancing their cognition so that they can keep up with AI-technologies and will not be replaced by them. Finally, we present own data and findings from the literature on the assumption that individuals' personality is a predictor of trust in AI. Trust in modern AI-technologies might be a strong determinant for wider appropriation and dependence on these technologies to distribute cognition and should thus be considered in an AI-enhanced future.

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Section: Outlook On Distributed Cognition In An Ai-enhanced Futurementioning

confidence: 99%

Supporting Cognition With Modern Technology: Distributed Cognition Today and in an AI-Enhanced Future

Grinschgl

Neubauer

2022

Front. Artif. Intell.

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“…Considering trust in working with an AI companion, previous work has focused on tasks with a well defned "correct" outcome. These include tasks like controlling an automated pasteurization plant [56], controlling central heating for a plant [66], and playing chess [18]. However, evaluating the efect of trust in creative tasks like storywriting is challenging since the most desirable outcome is inherently subjective.…”

Section: Implications Of Storywriters' Trustmentioning

confidence: 99%

From Tool to Companion: Storywriters Want AI Writers to Respect Their Personal Values and Writing Strategies

Biermann

Ning

Yoon

2022

Designing Interactive Systems Conference

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Modern large-scale language models approach the quality of humanlevel writing. This promises the advent of AI writing companions performing AI-led writing under human control, surpassing traditional writing tools limited to revision and ideation supports. However, human-AI co-writing may endanger writers' control, autonomy, and ownership by overstepping co-creative boundaries. Our design workbook study with 7 hobbyists and 13 professional writers elicited three sets of primary barriers to the adoption of human-AI co-writing. Storywriters desire retaining control over writing rather than letting AI take the lead when they (1) prioritize emotional values in turning ideas into words over the productivity of AI-generated writing; (2) have high self-confdence and distrust AI in challenging sub-tasks (e.g., creating characters and dialogue); and (3) expect the AI control mechanism to mismatch their writing strategies. We lay the groundwork for AI companions that respect storywriters' personal values and writing methods. CCS CONCEPTS• Human-centered computing → Empirical studies in interaction design; • Computing methodologies → Natural language generation; • Applied computing → Arts and humanities.

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“…From the conceptual conception in the 1960s to the practical application today, artificial intelligence [15][16][17][18][19] has triggered three upsurges of development and application. Different from previous academic research, business demand is the primary factor leading this upsurge.…”

Section: Introductionmentioning

confidence: 99%

Innovative Design of Artificial Intelligence in Intangible Cultural Heritage

Xie

2022

Scientific Programming

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Driven by artificial intelligence technology, the research of intangible cultural heritage innovative design is carried out. Firstly, the appearance modeling characteristics, decorative element characteristics, and composition form characteristics of typical intangible cultural heritage products are analyzed. According to the collected relevant data of intangible cultural heritage products and existing products, combined with the regional cultural characteristics of intangible cultural heritage products and other factors, the analysis Atlas of intangible cultural heritage product innovation design is constructed. Based on perceptual engineering, the elements of intangible cultural heritage product innovation design for user participation are determined according to the needs and perceptual images of users. The shape grammar is used to extract the elements of intangible cultural heritage products, deduce and deform them, and finally generate the preliminary design scheme.

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Human confidence in artificial intelligence and in themselves: The evolution and impact of confidence on adoption of AI advice

Cited by 117 publications

References 28 publications

Supporting Cognition With Modern Technology: Distributed Cognition Today and in an AI-Enhanced Future

Supporting Cognition With Modern Technology: Distributed Cognition Today and in an AI-Enhanced Future

From Tool to Companion: Storywriters Want AI Writers to Respect Their Personal Values and Writing Strategies

Innovative Design of Artificial Intelligence in Intangible Cultural Heritage

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