We discuss the adequacy of tests for intelligent systems and practical problems raised by their implementation. We propose the replacement test as the ability of a system to replace successfully another system performing a task in a given context. We show how it can characterize salient aspects of human intelligence that cannot be taken into account by the Turing test. We argue that building intelligent systems passing the replacement test involves a series of technical problems that are outside the scope of current AI. We present a framework for implementing the proposed test and validating the properties of the intelligent systems. We discuss the inherent limitations of intelligent system validation and advocate new theoretical foundations for extending existing rigorous test methods. We suggest that the replacement test, based on the complementarity of skills between human and machine, can lead to a multitude of intelligence concepts reflecting the ability to combine data-based and symbolic knowledge to varying degrees.

翻译：我们探讨了智能系统测试的充分性及其在实际应用中所引发的实践问题。提出了替代测试，即系统在特定情境下成功替代另一系统执行任务的能力。论证了该测试如何表征图灵测试无法涵盖的人类智能的关键方面。我们认为，构建通过替代测试的智能系统涉及一系列超出当前人工智能范畴的技术难题。提出了实施该测试并验证智能系统特性的框架。讨论了智能系统验证的固有局限性，倡导为扩展现有严谨测试方法建立新的理论基础。基于人类与机器技能互补性，我们建议替代测试能衍生出多种智能概念，这些概念反映了不同程度地融合基于数据的知识与符号知识的能力。