Caution and Flexibility

This dilemma left Emma in a difficult position: should she prioritise epistemic responsibility by focusing on the caution and reliability of strictly fact-checked responses, or should she embrace some form of pragmatism by designing the AI to allow more flexibility, adapting to users’ needs by prioritising practical usefulness over rigid accuracy? She found herself reflecting on the balance between these two philosophical perspectives.

Pragmatism posed a thought-provoking counterpoint to epistemic responsibility, inviting Emma to consider whether her AI should aim not just to be factual but also to be practically beneficial in various contexts. If she prioritises flexibility, she can offer users an AI that met them where they were, providing ideas, exploring options, and assisting with tasks in a fluid, adaptable way. But she also knows that this adaptability carries the risk of generating speculative, potentially misleading responses.

As Emma sat back, weighing these competing priorities, the question lingered: should the AI serve users with a clear adherence to verified truth, or should it follow the principle of practical usefulness, embracing flexibility even if it sometimes sacrificed factual accuracy? This choice could shape how users engaged with the AI and, perhaps more importantly, how they came to think about the very nature of truth in their interactions with it.