New questions about how humans can – and should – collaborate with Artificial Intelligence (AI) are emerging rapidly with the emergence of generative AI solutions like “ChatGPT”. The AI solutions available today go far beyond previously considered IT because it can re-code procedures, transform data, generate content, and thus alter the process and outcomes of work at an unprecedented scale. The consequence of this development is the question of whether AI is outperforming and replacing humans at non-routine tasks such as knowledge work (KW). This is a non-trivial question because knowledge worker (KWers) and the knowledge-intensive organizations embedded in were, for a long time, seen to be seemingly unaffected by the technological developments stemming from AI. Today, however, there is very limited understanding of the ways that KWers adjust to, and integrate, AI at work. This includes questions addressing ethical concerns related whether technology inhibits or facilitates KWers. With these theoretical challenges in mind, this research in progress sets out to sets out to address the existing research gaps existing in human-AI collaboration within knowledge-intensive domain: 1) there is out-of-dated understanding of relationship between the use of technology and the evolution of KW; 2) how are KWers highly attached with technology influenced by AI; and 3) the expectation about how human-AI collaboration should shape the nature of KW still remain unclear. Thus, this research aims to revisit the concept of KW in light of ongoing AI technology progress, outline the AI-driven phenomenon in knowledge-intensive domain and generate in-depth insights on how human–AI collaboration is reshaping the nature of KW.
Jiang, Mingyuan; Karanasios, Stan; Breidbach, Christoph F.; and Namvar, Morteza, "What We Don’t Know (Yet) about Human-AI Collaboration" (2023). Digit 2023 Proceedings. 7.