How Do Users Feel When They Use Artificial Intelligence for Decision Making? A Framework for Assessing Users’ Perception

Kushwaha, Amit Kumar; Pharswan, Ruchika; Kumar, Prashant; Kar, Arpan Kumar

doi:10.1007/s10796-022-10293-2

Cited by 12 publications

(2 citation statements)

References 81 publications

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“…Studies of human attitudes toward AI and machines have that sociodemographic factors, technical affinity, as well as knowledge of technology are critical factors that can influence perceptions on AA implementations. Examples include applications of AI in healthcare (Fritsch et al, 2022), AI in decision-making (Kushwaha et al, 2022), general attitudes toward AI (Zhang and Dafoe, 2019;Selwyn et al, 2020), and different forms of automated system applications (Langer, 1992). Therefore, this experiment elicits such factors through several survey questionnaires.…”

Section: Survey Measuresmentioning

confidence: 99%

Evading the algorithm: increased propensity for tax evasion and norm violations in human-computer interactions

Mutzner,

Oberhauser,

Winter

et al. 2023

Front. Behav. Econ.

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Today's modern world is characterized by an increasing shift from human-to-human interaction toward human-computer-interaction (HCI). With the implementation of artificial agents as inspectors, as can be seen in today's airports, supermarkets, or, most recently, within the context of the COVID-19 pandemic, our everyday life is progressively shaped around interacting with automated agents. While our understanding of HCI is evolving, it is still in nascent stages. This is particularly true in the sphere of non-cooperative strategic interactions between humans and automated agents, which remains largely unexplored and calls for further investigation. A deeper understanding of the factors influencing strategic decision-making processes within HCI situations, and how perceptions of automated agents' capabilities might influence these decisions, is required. This gap is addressed by extending a non-cooperative inspection-game experiment with a tax-evasion frame, implementing automated agents as inspectors. Here, a within-subject design is used to investigate (1) how HCI differs from human-to-human interactions in this context and (2) how the complexity and perceived capabilities of automated agents affect human decision-making. The results indicate significant differences in decisions to evade taxes, with participants more likely to evade taxes when they are inspected by automated agents rather than by humans. These results may also be transferred to norm violations more generally, which may become more likely when participants are controlled by computers rather than by humans. Our results further show that participants were less likely to evade taxes when playing against an automated agent described as a complex AI, compared to an automated agent described as a simple algorithm, once they had experienced different agents.

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Section: Survey Measuresmentioning

confidence: 99%

Evading the algorithm: increased propensity for tax evasion and norm violations in human-computer interactions

Mutzner,

Oberhauser,

Winter

et al. 2023

Front. Behav. Econ.

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“…At this stage, artificial intelligence is the most cutting-edge technology in the field of modern information science and technology, providing more intelligent products and services for society [8]. The introduction of artificial intelligence in the field of basketball is not only able to monitor and record the relevant data of athletes' training and competition, understand the athletes' physical condition and technical and tactical deficiencies, and provide them with scientific and reasonable training methods, which not only improves the training effect but also effectively reduces the probability of injury in training [9][10][11]. At the same time, make full use of artificial intelligence technology to promote the basketball coaching decision-making level to the direction of specialization and intelligence, which helps to cultivate more excellent talents for the development of the basketball sports program and promotes the growth of basketball to a wider and stronger direction [12][13].…”

Section: Introductionmentioning

confidence: 99%

Application and Implications of Artificial Intelligence Technology in Basketball Coaching Decision Making

Wang,

HoKun,

et al. 2024

Applied Mathematics and Nonlinear Sciences

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The proliferation of artificial intelligence (AI) technologies is significantly enhancing the precision and efficacy of decision-making in basketball. This study focuses on players from the men’s basketball team at School A, employing AI to model their sports postures, collect athletic performance data, and analyze physiological metrics in real time. By utilizing fuzzy gray correlation analysis, the research aims to identify the factors influencing basketball game outcomes, thereby informing tactical decisions for coaches. Moreover, this paper compares the proposed analysis method with other correlation techniques to evaluate its relative superiority. The findings indicate that post-training, the serum levels of all ten athletes exceeded 400 U/L. Yet, the creatine kinase (CK) levels remained below 6.8 mmol/L, and the urine specific gravity surpassed 1.05, suggesting that the training intensity was high but within the athletes’ physiological tolerances. With a correlation coefficient of 0.4, the study confirms a positive impact of game outcomes on the coach’s tactical adaptations. This underscores the utility of integrating AI systems into basketball to facilitate timely and effective decision-making by coaches.

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Consumers’ Financial Distress: Prediction and Prescription Using Interpretable Machine Learning

de Waal,

Nyawa,

Wamba

2024

Inf Syst Front

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How Do Users Feel When They Use Artificial Intelligence for Decision Making? A Framework for Assessing Users’ Perception

Cited by 12 publications

References 81 publications

Evading the algorithm: increased propensity for tax evasion and norm violations in human-computer interactions

Evading the algorithm: increased propensity for tax evasion and norm violations in human-computer interactions

Application and Implications of Artificial Intelligence Technology in Basketball Coaching Decision Making

Consumers’ Financial Distress: Prediction and Prescription Using Interpretable Machine Learning

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