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The emergence of large-language models (LLMs) that excel at code generationand commercial products such as GitHub's Copilot has sparked interest inhuman-AI pair programming (referred to as "pAIr programming") where an AIsystem collaborates with a human programmer. While traditional pair programmingbetween humans has been extensively studied, it remains uncertain whether itsfindings can be applied to human-AI pair programming. We compare human-humanand human-AI pair programming, exploring their similarities and differences ininteraction, measures, benefits, and challenges. We find that the effectivenessof both approaches is mixed in the literature (though the measures used forpAIr programming are not as comprehensive). We summarize moderating factors onthe success of human-human pair programming, which provides opportunities forpAIr programming research. For example, mismatched expertise makes pairprogramming less productive, therefore well-designed AI programming assistantsmay adapt to differences in expertise levels.

Is AI the better programming partner? Human-Human Pair Programming vs. Human-AI pAIr Programming