Since November and the commercial announcement of OpenAI’s new tool, ChatGPT, artificial intelligence tools, chat bots, image generators, and other forms of the technology have been one of the constant headlines in global conversation. Though many of these chatbots have been around for a period of time, the public consciousness is really just now beginning to identify all the possibilities (positive and negative) of what can be accomplished through the incorporation of AI into their daily lives.
There have been arguments about the ethics of utilizing these technologies in classrooms, and in the workplace. Educators worry about what this means to the development of writing skills and plagiarism, understandably so. But, what does this mean for individuals in the workforce? Can these technologies be used in an effective manner to transfer knowledge and build even greater instructional opportunities, leading to higher levels of productivity for individuals and organizations?
The fields of instructional design and human performance technology are beginning to heavily embed artificial intelligence into many of the platforms utilized by designers in these areas. For example, the learning management system, Kajabi, has already integrated AI into their platform to support the development of course outlines, landing page copy, email copy, lesson and social media content, and video scripts. Advocates of human performance technology identify as future oriented, solution focused, and up to the task of taking on challenging problems to improve working situations for others (Vantiem et al., 2004, p.10). The argument should be made then, that wherever possible in the workplace, we should be identifying opportunities to leverage tools such as Chat GPT or Google’s Bard, to enhance the performance of individuals in our collective organizations.
In fact, looking at the following three objectives of human performance: performance, conditions, and criterion (Wilmoth et al., 2010, p.8) one could argue that excluding these AI tools would indeed be limiting the possibilities and potential ceiling of performance one would hope to see in an organization’s base. So, the real question we should be asking is not whether companies should be integrating these tools into their workflow, but rather “What is the most effective way to leverage AI in my organization?”
The interaction between individuals and AI can be thought of in a similar fashion to that of individuals in business organizations wishing to transfer explicit knowledge from one to the other. This exchange relies heavily on effective communication between individuals (Cheng et al., 2010, p.446). There needs to be experimentation and constant opportunities for employees to communicate with the AI to create the most effective response. With these responses based on the prompts the individual inputs into the system, the more time one has to learn what an effective prompt looks like, the better they will be able to learn, create, and produce with the help of these tools.
References
Cheng, J., Son, S. J., & Bonk, C. J. (2010). Technology and Knowledge Management. International Handbook of Workplace Learning (pp. 381-391). Sage Publications.
Sanchez, C. (2023, January 26). 11 Ways to Do More Work in Less Time with AI. Contrarian Thinking. Retrieved April 2, 2023, from https://contrarianthinking.co/11-ways-to-do-more-work-in-less-time-with-ai/
Vantiem, D. M., Mosely, M., & Dessinger, J. C. (2004). Performance Technology Defined. Fundamentals of Performance Technology, 2-20.
Wilmoth, F. S., Prigmore, C., & Bray, M. (2010). HPT models. In R. Watkins & D. Leigh Handbook of improving performance in the workplace. Selecting and implementing performance interventions, 2, 5-26.
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