AI interviewing - the evaluator retains responsibility#

Autocoding#

The work of the AI coder and clustering algorithms are not error-free. The coding of individual high-stakes causal links should be checked. In particular, there is a danger of accepting inaccurate results which look plausible.

This approach does not nurture substantive, large-scale theory-building of the kind expected, for example in grounded theory (Glaser & Strauss, 1967). However, it can do smaller-scale theory-building in the sense of capturing theories implicit in individuals’ responses.

This pipeline relieves researchers of much of the work involved in coding but it is not fully autonomous. The human evaluator is responsible for applying the techniques in a trustworthy way and for drawing valid conclusions.