A Proposal of Revision of Floridi's Conjecture

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Auteur principal: Messina, Alberto
Format: Recurso digital
Publié: Zenodo 2025
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_version_ 1866901766630539264
author Messina, Alberto
author_facet Messina, Alberto
contents <p><span lang="EN-US">In response to Luciano Floridi’s conjecture on a fundamental trade‑off between certainty and scope in symbolic and generative AI (<a href="https://link.springer.com/article/10.1007/s13347-025-00927-z">Floridi, 2025</a>), we identify formal issues in the original definitions—specifically, the conflation of probabilistic and order‑theoretic notions in model correctness (C) and the opaque use of cumulative Kolmogorov complexity for mapping scope (S). Retaining all original philosophical foundations and motivations, we (i) introduce an Epistemic Certainty Level that replaces a mixed supremum–probability measure with a coherent expectation over indicator functions on output space’s equivalence classes; (ii) substitute cumulative Kolmogorov complexity with Shannon joint entropy to better quantify input/output mapping scope and make it more tractable computationally-wise.</span></p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_18060311
institution Zenodo
language
publishDate 2025
publisher Zenodo
record_format zenodo
spellingShingle A Proposal of Revision of Floridi's Conjecture
Messina, Alberto
Artificial Intelligence
Quality control
Benchmarking/methods
<p><span lang="EN-US">In response to Luciano Floridi’s conjecture on a fundamental trade‑off between certainty and scope in symbolic and generative AI (<a href="https://link.springer.com/article/10.1007/s13347-025-00927-z">Floridi, 2025</a>), we identify formal issues in the original definitions—specifically, the conflation of probabilistic and order‑theoretic notions in model correctness (C) and the opaque use of cumulative Kolmogorov complexity for mapping scope (S). Retaining all original philosophical foundations and motivations, we (i) introduce an Epistemic Certainty Level that replaces a mixed supremum–probability measure with a coherent expectation over indicator functions on output space’s equivalence classes; (ii) substitute cumulative Kolmogorov complexity with Shannon joint entropy to better quantify input/output mapping scope and make it more tractable computationally-wise.</span></p>
title A Proposal of Revision of Floridi's Conjecture
topic Artificial Intelligence
Quality control
Benchmarking/methods
url https://doi.org/10.5281/zenodo.18060311