Ready to Grip AI's Potential? Insights from an Exploratory Study on Perceptions of Human-AI Collaboration

被引:0
|
作者
Andrei, Andreia Gabriela [1 ]
Matcu-Zaharia, Mara [2 ]
Mariciuc, Dragos Florentin [2 ]
机构
[1] Alexandru Ioan Cuza Univ, Fac Econ & Business Adm, Dept Management Mkt & Business Adm, Iasi, Romania
[2] Alexandru Ioan Cuza Univ, Sch Econ & Business Adm, Iasi, Romania
关键词
generative AI; Human-AI collaboration; generation Z; Industry; 4.0; AI; SMES; ONLINE; IMPACT;
D O I
10.18662/brain/15.2/560
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
One of the emerging technologies arising with Industry 4.0 is generative artificial intelligence (AI). Despite its disruptive nature and controversies, the effective and ethical use of AI is increasingly preoccupying organizations of all sizes as well as their employees. Focusing on generative AI, this paper presents findings from a qualitative study that provides insights into how Generation Z, the newest workforce, perceives human-AI collaboration. Based on in-depth interviews and a micro-meso-macro approach, the study reveals a dual perspective. Participants recognized the advantages AI brings, such as increased efficiency, productivity, and information availability. However, they were concerned about various risks such as: technology addiction, job loss, data privacy and ethical issues. At the micro level, generative AI was seen as beneficial for providing information and inspiration, but over-reliance could limit people's skills and create dependency. At the meso, organizational level, it could increase efficiency and productivity, but potentially replace jobs. At the macro, societal level, generative AI could support innovation but risks dehumanizing communication and relationships. Data privacy and ethics concerns were expressed at all three levels, indicating that a combination of institutional safeguards and awareness of data privacy and ethics at all levels is required to achieve the full benefits of generative AI. This would help organisations to capitalise on technological advances and support the development of ethical use of AI tools
引用
收藏
页码:1 / 22
页数:22
相关论文
共 50 条
  • [31] Designing Transparency for Effective Human-AI Collaboration
    Michael Vössing
    Niklas Kühl
    Matteo Lind
    Gerhard Satzger
    Information Systems Frontiers, 2022, 24 : 877 - 895
  • [32] Synthesizing Explainable Behavior for Human-AI Collaboration
    Kambhampati, Subbarao
    AAMAS '19: PROCEEDINGS OF THE 18TH INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS AND MULTIAGENT SYSTEMS, 2019, : 1 - 2
  • [33] Adaptive trust calibration for human-AI collaboration
    Okamura, Kazuo
    Yamada, Seiji
    PLOS ONE, 2020, 15 (02):
  • [34] Enhancing human-AI collaboration: The case of colonoscopy
    Introzzi, Luca
    Zonca, Joshua
    Cabitza, Federico
    Cherubini, Paolo
    Reverberi, Carlo
    DIGESTIVE AND LIVER DISEASE, 2024, 56 (07) : 1131 - 1139
  • [35] Searching Over Search Trees for Human-AI Collaboration in Exploratory Problem Solving: A Case Study in Algebra
    Jones, Benjamin T.
    Tanimoto, Steven L.
    2018 IEEE SYMPOSIUM ON VISUAL LANGUAGES AND HUMAN-CENTRIC COMPUTING (VL/HCC), 2018, : 33 - 37
  • [36] Human-AI Collaboration: The Effect of AI Delegation on Human Task Performance and Task Satisfaction
    Hemmer, Patrick
    Westphal, Monika
    Schemmer, Max
    Vetter, Sebastian
    Vossing, Michael
    Satzger, Gerhard
    PROCEEDINGS OF 2023 28TH ANNUAL CONFERENCE ON INTELLIGENT USER INTERFACES, IUI 2023, 2023, : 453 - 463
  • [37] Teaming Up with an AI: Exploring Human-AI Collaboration in a Writing Scenario with ChatGPT
    Luther, Teresa
    Kimmerle, Joachim
    Cress, Ulrike
    AI, 2024, 5 (03) : 1357 - 1376
  • [38] AI and XAI second opinion: the danger of false confirmation in human-AI collaboration
    Rosenbacke, Rikard
    Melhus, Asa
    McKee, Martin
    Stuckler, David
    JOURNAL OF MEDICAL ETHICS, 2024,
  • [39] Working With and Around Artificial Intelligence: AI Crafting and Human-AI Collaboration in Recruitment
    Laukkarinen, Matti
    INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION, 2025,
  • [40] Do We Learn From Each Other: Understanding the Human-AI Co-Learning Process Embedded in Human-AI Collaboration
    Lu, Jinwei
    Yan, Yikuan
    Huang, Keman
    Yin, Ming
    Zhang, Fang
    GROUP DECISION AND NEGOTIATION, 2024, : 235 - 271