Modeling and Guiding the Creation of Ethical Human-AI Teams

Flathmann, Christopher; Schelble, Beau G.; Zhang, Rui; McNeese, Nathan J.

doi:10.1145/3461702.3462573

Cited by 20 publications

(8 citation statements)

References 62 publications

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“…Human-AI integration phase faces unique challenges. Some of the challenges HRM will face in the integration phase are role and job design challenges (e.g., Sampson, 2021 ), HCI design challenges (e.g., Arslan et al, 2022 ), human and AI cross-functional team issues (e.g., Klien et al, 2004 ; Arslan et al, 2022 ), responsible design (e.g., Bankins, 2021 ), ethical concerns in terms of decision-making (e.g., Flathmann et al, 2021 ), cultural differences (Herrmann and Pfeiffer, 2023 ), and appropriate oversight and governance (e.g., Wu et al, 2020 ). The main challenges HRM faces in phase two are centered around employee up-skilling and re-skilling, AI solution design and integration challenges, and delineation of responsibility between humans and machines.…”

Section: How Hrm Can Bring Humans and Machines Closer Together In The...mentioning

confidence: 99%

Revisiting the role of HR in the age of AI: bringing humans and machines closer together in the workplace

Fenwick,

Molnar,

Frangos

2024

Front. Artif. Intell.

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The functions of human resource management (HRM) have changed radically in the past 20 years due to market and technological forces, becoming more cross-functional and data-driven. In the age of AI, the role of HRM professionals in organizations continues to evolve. Artificial intelligence (AI) is transforming many HRM functions and practices throughout organizations creating system and process efficiencies, performing advanced data analysis, and contributing to the value creation process of the organization. A growing body of evidence highlights the benefits AI brings to the field of HRM. Despite the increased interest in AI-HRM scholarship, focus on human-AI interaction at work and AI-based technologies for HRM is limited and fragmented. Moreover, the lack of human considerations in HRM tech design and deployment can hamper AI digital transformation efforts. This paper provides a contemporary and forward-looking perspective to the strategic and human-centric role HRM plays within organizations as AI becomes more integrated in the workplace. Spanning three distinct phases of AI-HRM integration (technocratic, integrated, and fully-embedded), it examines the technical, human, and ethical challenges at each phase and provides suggestions on how to overcome them using a human-centric approach. Our paper highlights the importance of the evolving role of HRM in the AI-driven organization and provides a roadmap on how to bring humans and machines closer together in the workplace.

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Section: How Hrm Can Bring Humans and Machines Closer Together In The...mentioning

confidence: 99%

Revisiting the role of HR in the age of AI: bringing humans and machines closer together in the workplace

Fenwick,

Molnar,

Frangos

2024

Front. Artif. Intell.

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“…As modern teams adapt to the potential for and burgeoning reality of AI collaboration, the dynamics of human-AI teaming becomes much more important to understand. 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%

“…In human-AI teams, ethics and ethical decision-making are paramount to team dynamics and outcomes. These teams need ATs that can operate within the necessary ethical dimensions for the contexts in which they operate (Flathmann et al, 2021). This is because ethics directly relates to trust, as humans must be able to trust their ATs to perform and use their autonomy to properly navigate ethical situations or the ethical implications of their actions (Winfield, 2019).…”

Section: Ethics In 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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“…These trust violations can be very costly for human-AI teams, causing reductions in overall team performance (McNeese et al, 2021a), confidence (De Visser & Parasuraman, 2011), and even trust in fellow human teammates (McNeese et al, 2021a). These trust violations by an AT can also be ethical in nature (Flathmann et al, 2021). Specifically, trust in a trustee is specific to the trustor's current goal (Lee & See, 2004), and a trustee can perform an unethical or ethical action that satisfies said goal.…”

Section: Introductionmentioning

confidence: 99%

Towards Ethical AI: Empirically Investigating Dimensions of AI Ethics, Trust Repair, and Performance in Human-AI Teaming

et al. 2022

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Objective Determining the efficacy of two trust repair strategies (apology and denial) for trust violations of an ethical nature by an autonomous teammate. Background While ethics in human-AI interaction is extensively studied, little research has investigated how decisions with ethical implications impact trust and performance within human-AI teams and their subsequent repair. Method Forty teams of two participants and one autonomous teammate completed three team missions within a synthetic task environment. The autonomous teammate made an ethical or unethical action during each mission, followed by an apology or denial. Measures of individual team trust, autonomous teammate trust, human teammate trust, perceived autonomous teammate ethicality, and team performance were taken. Results Teams with unethical autonomous teammates had significantly lower trust in the team and trust in the autonomous teammate. Unethical autonomous teammates were also perceived as substantially more unethical. Neither trust repair strategy effectively restored trust after an ethical violation, and autonomous teammate ethicality was not related to the team score, but unethical autonomous teammates did have shorter times. Conclusion Ethical violations significantly harm trust in the overall team and autonomous teammate but do not negatively impact team score. However, current trust repair strategies like apologies and denials appear ineffective in restoring trust after this type of violation. Application This research highlights the need to develop trust repair strategies specific to human-AI teams and trust violations of an ethical nature.

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Modeling and Guiding the Creation of Ethical Human-AI Teams

Cited by 20 publications

References 62 publications

Revisiting the role of HR in the age of AI: bringing humans and machines closer together in the workplace

Revisiting the role of HR in the age of AI: bringing humans and machines closer together in the workplace

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

Towards Ethical AI: Empirically Investigating Dimensions of AI Ethics, Trust Repair, and Performance in Human-AI Teaming

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