Raccolta di brevi saggi in filosofia della mente.

Adopting the notion of “pragmatic information” as interpreted by Roederer and granted that understanding arises from genuine information processing, I show that Searle’s “Chinese Room Argument” in rejecting the thesis of Strong Artificial Intelligence and his responses to critics are sound and acceptable. The paper is a safe and secure translation of Searle’s argument into a language of information. According to the notion of information that I adopt, information and information processing are exclusive attributes of biological and artificial systems. However, (...) I will show that information-theoretically, biological brains are fundamentally different from their artificial simulations. I will argue that only biological systems, or their duplicates, are genuine information processing systems and thus capable of understanding Chinese. “Understanding”, in my proposal, denotes “phenomenal consciousness” in the context of Chalmers’ thesis of naturalistic dualism. (shrink)

Searle’s Chinese room argument (CRA) was recently charged as being unsound because it makes a logical error. It is shown here that this charge is based on a misinterpretation of the modal scope of a major premise of the CRA and that the CRA does not commit the logical error with which it is charged.

This paper examines the role of machine functionalism, as one of the most popular positions within the philosophy of mind, in the context of the development of artificial intelligence. Our analysis starts from the idea that machine functionalism is a theory that is largely consistent with the principles behind the strong AI thesis. However, we will see that there is a convincing counter-argument against such claims, and we will problematize this issue. Also, by testing ChatGPT, as the most popular publicly (...) available AI tool, we will make an effort to figure out whether the strong AI thesis could currently even be considered a potentially sustainable principle. Since ChatGPT fails the Turing test our conclusion is that the strong AI thesis cannot be upheld even in principle, implying that the current state of this AI tool does not yet provide strong enough arguments in favor of machine functionalism. (shrink)