AIdeation: short- or long-term objectives?

While current AI systems are heralded as collaborators, they are fundamentally short-sighted – optimised for providing instant and complete responses, without ever saying no (unless for safety reasons). What are the consequences of this dynamic?  That is, the rapid rise of AI chatbots promises immediate and effective help with reasoning-intensive tasks such as studying, writing, coding, and brainstorming. But what happens to users’ own abilities when the AI is not available? A study* provides causal evidence for two key consequences of AI assistance: reduced persistence and impairment of unassisted performance. Across a variety of tasks, including mathematical reasoning and reading comprehension, the research finds that although AI assistance improves performance in the short-term, people perform significantly worse without AI and are more likely to give up. Notably, these effects emerge after only brief interactions with AI (∼10 minutes). These findings are particularly concerning because persistence is foundational to skill acquisition and is one of the strongest predictors of long-term learning. The study posits that persistence is reduced because AI conditions people to expect immediate answers, thereby denying them the experience of working through challenges on their own. These results suggest the need for AI model development to prioritize scaffolding long-term competence alongside immediate task completion. *https://arxiv.org/pdf/2604.04721