AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
TL;DR
It is argued that the ‘mission’ of mechanistic interpretability should be re-framed as the project of experimentally interacting with LLMs in order to study the behaviors and internal processes that emerge in virtue of these interactions.
The aim of interpretability shifts the aim of interpretability from finding human concepts inside models toward discovering and characterizing the representational structures that are native to the models themselves and might affect their behaviour in unpredictable ways.
It is argued that consciousness is a sine qua non for understanding which is absent in the understanding of AI systems and that the age of AI demands a reformulation of the notion of understanding itself.
As AI systems are increasingly deployed in high-stakes domains, regulatory and societal demands for transparency and interpretability continue to grow. While classical Explainable AI (XAI) methods produce structured technical artifacts (e.g., feature attributions and counterfactual examples), these remain difficult to...
Explainable artificial intelligence (XAI) encompasses methods that draw on different sources of information and address different explanatory needs. A common framework is needed to describe how this information becomes evidence and is communicated as an explanation for a particular recipient. We propose the General Fra...
The artifactual stance is introduced, which describes human–AI interaction in terms of their design and affordances, rather than potential intentional attitudes, and reframes puzzles about AI reference, the persistence of supposed interlocutors, and responsibility for AI-generated text.
It is argued that generative AI can degrade research by eroding the very practices through which scholarly judgement is formed, and defended because it rests on four sources and warrants of research that cannot be automated: tacit knowledge, personal commitment, socialisation and deep reading.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.