Third-party cyber evaluations involving OpenAI models
openai.com·13h ago
AI Research
arXiv CS.AI·Jul 2·5 min read
Unexplainability of Artificial Intelligence Judgments and Functional Implementation in Kant's Perspective
TL;DR
Artificial intelligence (AI) often lacks transparency in its decision-making processes, raising ethical concerns. This paper explores the implications of Kant's philosophy on AI's unexplainability and its functional implementation.
✦ Why It Matters
Engineers should consider integrating ethical frameworks like Kantian ethics into AI development processes to enhance accountability.
Key Takeaways
- Assess AI systems against Kant's judgment criteria.
- Investigate the implications of AI's uncertainty in decision-making.
- Critique the use of Softmax in AI for accurate judgments.
- Ensure clear criteria for functional implementation in AI applications.
How It Works
The study applies Kant's four logical forms—quantity, quality, relation, and modality—to analyze AI judgments. It reveals that the Softmax function, which normalizes outputs into probabilities, distorts AI's decision-making process by framing judgments as possibilities rather than certainties.