近視的 ポリシー is a term used in various fields such as economics, 公共政策, and 人工知能 to describe a decision-making approach that prioritizes immediate benefits over sustainable, long-term consequences. This approach can lead to decisions that are advantageous in the short run but detrimental in the long run.
経済の文脈では、近視的な政策は、一時的に経済成長を促進するための財政措置（例：減税や政府支出の増加）として現れることがありますが、将来的な予算赤字やインフレの可能性を考慮しません。同様に、環境政策においては、自然資源を短期的な利益最大化のために搾取し、長期的な生態系や資源の利用可能性への影響を無視することがあります。
人工知能において、近視的な方針は 強化学習 scenarios where an agent is designed to maximize immediate rewards without taking into account the broader implications of its actions. For instance, an AI programmed to maximize short-term profits in a trading environment might engage in risky behaviors that could lead to significant losses down the line.
Myopic policies are often criticized for their lack of foresight and potential to create cycles of boom and bust. Policymakers and decision-makers are encouraged to adopt a more holistic view, considering the long-term effects of their actions to ensure a balanced approach to growth and sustainability.