Perception Lie Paradox: Mathematically Proved Uncertainty about Humans Perception Similarity
This addresses a foundational problem in philosophy and AI regarding perception and communication, but it is incremental as it builds on existing skeptical views with a mathematical formalization.
The paper tackles the paradox of whether agents can judge if they have the same perception, finding that agreement in communication requires perception correspondence rather than identical perception, which introduces uncertainty in such judgments and extends to comparing intelligence across different agents like machines and humans.
Agents' judgment depends on perception and previous knowledge. Assuming that previous knowledge depends on perception, we can say that judgment depends on perception. So, if judgment depends on perception, can agents judge that they have the same perception? In few words, this is the addressed paradox through this document. While illustrating on the paradox, it's found that to reach agreement in communication, it's not necessary for parties to have the same perception however the necessity is to have perception correspondence. The attempted solution to this paradox reveals a potential uncertainty in judging the matter thus supporting the skeptical view of the problem. Moreover, relating perception to intelligence, the same uncertainty is inherited by judging the level of intelligence of an agent compared to others not necessarily from the same kind (e.g. machine intelligence compared to human intelligence). Using a proposed simple mathematical model for perception and action, a tool is developed to construct scenarios, and the problem is addressed mathematically such that conclusions are drawn systematically based on mathematically defined properties. When it comes to formalization, philosophical arguments and views become more visible and explicit.