As artificial intelligence transforms organizational life, understanding the fundamental relationship between human and computational behavior becomes crucial for management theory and practice. This paper examines three historical paradigms in human-computer behavioral conceptualization: computers as human-like, humans as computer-like, and the cybernetic equivalence perspective. Through analysis of seminal works (1940s-1970s), we demonstrate how these paradigms struggled with the fundamental incommensurability between deterministic computational systems and probabilistic human behavior. This historical analysis reveals why early human-computer interaction remained constrained to narrow, formal interfaces rather than natural engagement. However, modern AI systems, exhibiting characteristics previously exclusive to human cognition (such as ambiguity tolerance and contextual adaptation), suggest a paradigmatic shift. Understanding this historical trajectory and its underlying assumptions is crucial for theorizing about human-AI collaboration in contemporary organizations. We propose a new framework for understanding human-AI interaction in organizational contexts, emphasizing the convergence of previously distinct behavioral paradigms.
