A scoping review and empirical analysis produce a six-category taxonomy of factors driving AI non-development and abandonment, showing that practical issues like resource limits and organizational dynamics often outweigh ethical concerns in real decisions.
A unified framework of five principles for AI in society
3 Pith papers cite this work, alongside 771 external citations. Polarity classification is still indexing.
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A thermodynamic-inspired information-geometric framework defines a composite LLM stability score that outperforms a utility-entropy baseline by 0.0299 on average across 80 observations, with gains increasing at higher entropy.
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To Build or Not to Build? Factors that Lead to Non-Development or Abandonment of AI Systems
A scoping review and empirical analysis produce a six-category taxonomy of factors driving AI non-development and abandonment, showing that practical issues like resource limits and organizational dynamics often outweigh ethical concerns in real decisions.
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