Game changers: A generative AI prompt protocol to enhance human-AI knowledge co-construction

被引:22
|
作者
Robertson, Jeandri [1 ,2 ]
Ferreira, Caitlin [3 ]
Botha, Elsamari [4 ]
Oosthuizen, Kim [5 ]
机构
[1] Lulea Univ Technol, Lulea, Sweden
[2] Univ Cape Town, Cape Town, South Africa
[3] Univ Cape Town, Grad Sch Business, Cape Town, South Africa
[4] Univ Canterbury, UC Business Sch, Christchurch, New Zealand
[5] Univ Stellenbosch, Business Sch, Cape Town, South Africa
关键词
Large language models; Generative AI; ChatGPT; Prompt engineering; Constructivism; ARTIFICIAL-INTELLIGENCE;
D O I
10.1016/j.bushor.2024.04.008
中图分类号
F [经济];
学科分类号
02 ;
摘要
The democratization of powerful artificial intelligence (AI) tools, including ChatGPT, has sparked the interest of business practitioners given their ability to fundamentally change the way we work. While AI tools are positioned to augment human capabilities, their effective implementation requires the skill to understand where, when and how to best utilize them efficiently. Furthermore, meaningful engagement with the content produced by generative AI (GenAI) necessitates the intricacy of appropriate prompt engineering to optimize the learning process. As the field of GenAI continues to advance, the art of developing impactful prompts has become a necessary skill for harnessing its full potential. This research develops an AI prompting protocol through a constructivist theory lens. Based on the principles of constructivism, where individuals assimilate new knowledge by bridging it with their existing understanding, this research suggests an active engagement process in the human-AI co-construction of knowledge through GenAI. The goal is to empower business managers and their teams to construct effective AI prompts and validate responses, thereby enhancing user interaction, optimizing workflows, and maximizing the potential outcomes of AI chatbots. (c) 2024 Kelley School of Business, Indiana University. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/ licenses/by/4.0/).
引用
收藏
页码:499 / 510
页数:12
相关论文
共 50 条
  • [1] Human-AI agency in the age of generative AI
    Krakowski, Sebastian
    INFORMATION AND ORGANIZATION, 2025, 35 (01)
  • [2] Optimizing Human-AI Collaboration in Chemistry: A Case Study on Enhancing Generative AI Responses through Prompt Engineering
    Vidhani, Dinesh V.
    Mariappan, Manoharan
    CHEMISTRY-SWITZERLAND, 2024, 6 (04): : 723 - 737
  • [3] Can AI explain AI? Interactive co-construction of explanations among human and artificial agents
    Klowait, Nils
    Erofeeva, Maria
    Lenke, Michael
    Horwath, Ilona
    Buschmeier, Hendrik
    DISCOURSE & COMMUNICATION, 2024, 18 (06) : 917 - 930
  • [4] A Cybersecurity Game to Probe Human-AI Teaming
    Olla, Rita
    Hand, Emily
    Louis, Sushil J.
    Houmanfar, Ramona
    Sengupta, Shamik
    2024 IEEE CONFERENCE ON GAMES, COG 2024, 2024,
  • [5] Ironies of Generative AI: Understanding and Mitigating Productivity Loss in Human-AI Interaction
    Simkute, Auste
    Tankelevitch, Lev
    Kewenig, Viktor
    Scott, Ava Elizabeth
    Sellen, Abigail
    Rintel, Sean
    INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION, 2025, 41 (05) : 2898 - 2919
  • [6] AI Creativity and the Human-AI Co-creation Model
    Wu, Zhuohao
    Ji, Danwen
    Yu, Kaiwen
    Zeng, Xianxu
    Wu, Dingming
    Shidujaman, Mohammad
    HUMAN-COMPUTER INTERACTION: THEORY, METHODS AND TOOLS, HCII 2021, PT I, 2021, 12762 : 171 - 190
  • [7] Human-AI Interaction Generation: A Connective Lens for Generative AI and Procedural Content Generation
    Guzdial, Matthew
    PROCEEDINGS OF THE THIRTY-THIRD INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, IJCAI 2024, 2024, : 8529 - 8534
  • [8] Generative AI-enhanced human-AI collaborative conceptual design: A systematic literature review
    Fang, Cong
    Zhu, Yujie
    Fang, Le
    Long, Yonghao
    Lin, Huan
    Cong, Yangfan
    Wang, Stephen Jia
    DESIGN STUDIES, 2025, 97
  • [9] Fairness, Relationship, and Identity Construction in Human-AI Interaction
    Dong, Jie
    JOURNAL OF SOCIOLINGUISTICS, 2024, 28 (05) : 35 - 37
  • [10] The rise of hybrids: plastic knowledge in human-AI interaction
    La Sala, Antonio
    Fuller, Ryan
    Riolli, Laura
    Temperini, Valerio
    JOURNAL OF KNOWLEDGE MANAGEMENT, 2024, 28 (10) : 3023 - 3045