The distinction you draw here seems important and underexplored. AI is genuinely valuable in that it reduces the cost of routine work, freeing up time and energy for new ideas. But when it comes to verificatory routine – the kind you describe, whose output becomes the foundation for further epistemic conclusions – this automation carries a specific risk.
The tasks that get delegated first are the ones people least want to do. Searching for sources, tracing chains of reasoning, cross-checking claims – these are the classic examples. It is psychologically easiest to hand off what you dislike, especially when the tool handles it faster and more smoothly. But this same monotonous routine is what builds an intuitive understanding of how these processes work from the inside – what looks suspicious, where errors tend to hide, when a source is too convenient to be genuine.
When a person stops doing this work, they lose not just the skill but the ability to validate what the algorithm produces. And precisely because the task is disliked, there is little motivation to maintain any kind of checking mode. The value of automation and its vulnerability turn out to be in the same place: the more readily a person delegates a task, the less capable they are of noticing when the algorithm gets it wrong.
Do you think maintaining deliberate checking habits is enough to offset this, or is the risk more structural?
The distinction you draw here seems important and underexplored. AI is genuinely valuable in that it reduces the cost of routine work, freeing up time and energy for new ideas. But when it comes to verificatory routine – the kind you describe, whose output becomes the foundation for further epistemic conclusions – this automation carries a specific risk.
The tasks that get delegated first are the ones people least want to do. Searching for sources, tracing chains of reasoning, cross-checking claims – these are the classic examples. It is psychologically easiest to hand off what you dislike, especially when the tool handles it faster and more smoothly. But this same monotonous routine is what builds an intuitive understanding of how these processes work from the inside – what looks suspicious, where errors tend to hide, when a source is too convenient to be genuine.
When a person stops doing this work, they lose not just the skill but the ability to validate what the algorithm produces. And precisely because the task is disliked, there is little motivation to maintain any kind of checking mode. The value of automation and its vulnerability turn out to be in the same place: the more readily a person delegates a task, the less capable they are of noticing when the algorithm gets it wrong.
Do you think maintaining deliberate checking habits is enough to offset this, or is the risk more structural?