We develop a taxonomical framework for classifying challenges to the possibility of consciousness in digital artificial intelligence systems. This framework allows us to identify the level of granularity at which a given challenge is intended (the levels we propose correspond to Marr's levels) and to disambiguate its degree of force: is it a challenge to computational functionalism that leaves the possibility of digital consciousness open (degree 1), a practical challenge to digital consciousness that suggests improbability without claiming impossibility (degree 2), or an argument claiming that digital consciousness is strictly impossible (degree 3)? We apply this framework to 14 prominent examples from the scientific and philosophical literature. Our aim is not to take a side in the debate, but to provide structure and a tool for disambiguating between challenges to computational functionalism and challenges to digital consciousness, as well as between different ways of parsing such challenges.

翻译：我们构建了一个分类学框架，用于对数字人工智能系统中意识可能性的挑战进行分类。该框架使我们能够识别特定挑战所针对的粒度级别（我们提出的级别对应于马尔的三层次理论），并澄清其论证力度：该挑战是针对计算功能主义但仍为数字意识保留可能性（力度1），还是提出数字意识虽非不可能但实际概率极低的实践性质疑（力度2），抑或是主张数字意识严格不可行的论证（力度3）？我们将此框架应用于科学和哲学文献中的14个典型案例。我们的目标并非在争论中站队，而是提供一种结构化工具，以区分针对计算功能主义的挑战与针对数字意识的挑战，并厘清解析此类挑战的不同方式。