Investigating the Effects of Perceived Teammate Artificiality on Human Performance and Cognition

Schelble, Beau G.; Flathmann, Christopher; McNeese, Nathan J.; O’Neill, Thomas A.; Pak, Richard; Namara, Moses

doi:10.1080/10447318.2022.2085191

Cited by 9 publications

(3 citation statements)

References 72 publications

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“…However, research has shown that humans hold high expectations for ATs powered by AI, believing they should demonstrate human-like behaviors and capabilities (Flathmann et al, 2021;Zhang et al, 2021). This demand requires ATs to possess the ability to communicate and coordinate with teammate with shared understanding, contribute to shared goals and outcomes, and demonstrate interpersonal and situational awareness (Hauptman et al, 2022;Schelble, Flathmann, McNeese, O'Neill, et al, 2022;Zhang et al, 2021), each of which contribute to the development and sustainment of trust.…”

Section: Human-ai Teamingmentioning

confidence: 99%

Introduction to the Minitrack on Collaboration in Online Communities: Information Processing and Decision Making

Jensen,

Meservy,

Fadel

2024

Proceedings of the Annual Hawaii International Conference on System Sciences

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This study improves the understanding of trust in human-AI teams by investigating the relationship of AI teammate ethicality on individual outcomes of trust (i.e., monitoring, confidence, fear) in AI teammates and human teammates over time. Specifically, a synthetic task environment was built to support a three-person team with two human teammates and one AI teammate (simulated by a confederate). The AI teammate performed either an ethical or unethical action in three missions, and measures of trust in the human and AI teammate were taken after each mission. Results from the study revealed that unethical actions by the AT had a significant effect on nearly all of the outcomes of trust measured and that levels of trust were dynamic over time for both the AI and human teammate, with the AI teammate recovering trust in Mission 1 levels by Mission 3. AI ethicality was mostly unrelated to participants' trust in their fellow human teammates but did decrease perceptions of fear, paranoia, and skepticism in them, and trust in the human and AI teammate was not significantly related to individual performance outcomes, which both diverge from previous trust research in human-AI teams utilizing competency-based trust violations.

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Section: Human-ai Teamingmentioning

confidence: 99%

Introduction to the Minitrack on Collaboration in Online Communities: Information Processing and Decision Making

Jensen,

Meservy,

Fadel

2024

Proceedings of the Annual Hawaii International Conference on System Sciences

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“…-Human performance of work: These factors are related to the ability to work and the desire to perform, as the productive efficiency of the worker is closely related to the human effort because he has a major role in performing the work. (Schelble et al, 2023 ) -Technical factors: These factors depend on the quality and quantity of materials, the level of customer preparation, as well as the raw materials used in the work and job design. Administrative factors must also be available, such as planning, organization and control, which inevitably affects productivity.…”

Section: Dimensions Of Production Efficiencymentioning

confidence: 99%

Does applying financial engineering methods have an impact on improving production efficiency? Does applying financial engineering methods have an impact on improving production efficiency?

Hameed,

Mohsin,

Bani Hani

et al. 2024

sajssh

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The study aims to identify the application of financial engineering methods and production efficiency in the General Fertilizer Manufacturing Company in Basra. To obtain the required information, a sample of (250) workers working at various administrative and production levels in the company was selected as a study population.The questionnaire was used as a main tool for collecting data, and to test the study hypotheses: There is a significant effect of the processes of applying financial engineering methods in improving production efficiency. To measure the effect, analyze correlations, and then arrive at the research results, the two statistical programs (SMART PLS) were used. The research reached a number of conclusions, most notably the existence of an impact of the processes of applying financial engineering methods on the factors influencing the improvement of production efficiency. The study concluded with a number of recommendations, including the necessity of applying financial engineering methods in the company in the study population to improve production efficiency.

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“…On the basis of all of the data obtained, the chatbot builds a detailed profile for each user. This profile is constantly improved and modified, depending on the data that the chatbot collects about the user [34,35].…”

Section: Detailed Analysis Of Preferences and Behaviorsmentioning

confidence: 99%

Practical Approach for Smart and Circular Cities: Chatbots Used in Waste Recycling

Zota,

Cîmpeanu,

Dragomir

et al. 2024

Applied Sciences

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Sustainable development, smart waste management, and circular economy principles are paramount to the significant worldwide trend of smart city-related research and projects. The basic hypothesis of our research is that artificial intelligence (AI)-based IT applications have an increasingly important role in the field of smart cities in terms of issues related to waste management. In our present article, we set out to analyze the characteristics of chatbot applications dedicated to waste recycling in the case of smart cities and propose some innovative ideas to improve the efficiency of such applications. Based on the consultation and analysis of a whole series of chatbot-type applications used to facilitate the recycling activity, we systematically analyze and evaluate five illustrative examples of chatbots employed in the context of material recycling. We provide performance comparisons in a table based on specific relevant criteria. Furthermore, the detailed analysis of these chatbots has led to the idea of improving the performance of this type of application. In this sense, we propose a series of innovative concepts that can be successfully implemented in future chatbots dedicated to the field of the circular economy. Here, we detail the innovative ideas that can promote the circular economy and capitalize on the potential of chatbots in the waste recycling activity. We also identify some possible limitations of these new ideas that we propose to be implemented. As for future research directions, our goal is to develop a chatbot dedicated to improving waste recycling practices within the framework of a smart city. Such innovation holds promise in improving sustainability efforts and fostering environmental stewardship within urban environments.

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Investigating the Effects of Perceived Teammate Artificiality on Human Performance and Cognition

Cited by 9 publications

References 72 publications

Introduction to the Minitrack on Collaboration in Online Communities: Information Processing and Decision Making

Introduction to the Minitrack on Collaboration in Online Communities: Information Processing and Decision Making

Does applying financial engineering methods have an impact on improving production efficiency? Does applying financial engineering methods have an impact on improving production efficiency?

Practical Approach for Smart and Circular Cities: Chatbots Used in Waste Recycling

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