Mundane legal work often only maximizes billable hours without training young lawyers effectively, leading to reduced job satisfaction. AI may replace this grunt work, eliminating unproductive training practices. Current theories, such as Recognition-Primed Decision Making developed by Kahneman and Klein, suggest that experienced lawyers develop intuitive skills through pattern recognition. These skills can inform decisions and may imply that future lawyers trained differently could still perform well or better than current lawyers, provided they are exposed to meaningful training opportunities.
Much of the mundane work young lawyers were expected to do didn't train them to do much of anything other than maximize billable hours, and it was depressing.
The recent research by Daniel Kahneman and Gary Klein looks at the unconscious recognition of patterns a person has previously seen and experienced, which can inform problem-solving.
Recognition-Primed Decision Making suggests that experienced professionals can often 'sense' issues without conscious reasoning, impacting how we view legal training.
While future on-the-job training may differ, it could lead to younger lawyers ultimately being as capable, if not better, than current practitioners.
#legal-training #artificial-intelligence #recognition-primed-decision-making #job-satisfaction #young-lawyers
Collection
[
|
...
]