📝 SummarXiv

Abstract

Rapid computational developments - particularly the proliferation of artificial intelligence (AI) - increasingly shape social scientific research while raising new questions about in-depth qualitative methods such as ethnography and interviewing. Building on classic debates about using computers to analyze qualitative data, we revisit longstanding concerns and assess possibilities and dangers in an era of automation, AI chatbots, and 'big data.' We first historicize developments by revisiting classical and emergent concerns about qualitative analysis with computers. We then introduce a typology of contemporary modes of engagement - streamlining workflows, scaling up projects, hybrid analytical approaches, and the sociology of computation - alongside rejection of computational analyses. We illustrate these approaches with detailed workflow examples from a large-scale ethnographic study and guidance for solo researchers. We argue for a pragmatic sociological approach that moves beyond dualisms of technological optimism versus rejection to show how computational tools - simultaneously dangerous and generative - can be adapted to support longstanding qualitative aims when used carefully in ways aligned with core methodological commitments.