论文标题
AI失败：对基本问题的审查
AI Failures: A Review of Underlying Issues
论文作者
论文摘要
人工智能（AI）系统未能提供一致，令人满意的性能的实例是Legion。我们调查为什么会发生AI失败。我们仅处理AI安全性更广阔领域的狭窄子集。由于概念化，设计和部署的缺陷，我们专注于AI失败。其他AI安全问题，例如隐私与安全或便利性之间的权衡，不良行为者黑客入侵AI系统，以创建为有害人类有害的AI部署AI的混乱或坏演员，并且不在我们的讨论范围内。我们发现，由于AI系统设计中的遗漏和佣金错误以及未能对输入信息进行适当的解释，AI系统由于遗漏和佣金错误而失败。此外，即使AI软件中没有明显的缺陷，AI系统也可能会失败，因为硬件无法在环境之间具有良好的性能。最终，在实际上要求它提供道德判断的情况下，AI系统很可能会失败 - AI不具备的能力。我们观察到一些措施的权衡，以减轻AI失败的子集并提供一些建议。
Instances of Artificial Intelligence (AI) systems failing to deliver consistent, satisfactory performance are legion. We investigate why AI failures occur. We address only a narrow subset of the broader field of AI Safety. We focus on AI failures on account of flaws in conceptualization, design and deployment. Other AI Safety issues like trade-offs between privacy and security or convenience, bad actors hacking into AI systems to create mayhem or bad actors deploying AI for purposes harmful to humanity and are out of scope of our discussion. We find that AI systems fail on account of omission and commission errors in the design of the AI system, as well as upon failure to develop an appropriate interpretation of input information. Moreover, even when there is no significant flaw in the AI software, an AI system may fail because the hardware is incapable of robust performance across environments. Finally an AI system is quite likely to fail in situations where, in effect, it is called upon to deliver moral judgments -- a capability AI does not possess. We observe certain trade-offs in measures to mitigate a subset of AI failures and provide some recommendations.
