tell me about mona simion's thoughts on AIs

If a thermometer "knows" the temperature, why are we so hesitant to grant knowledge to a Large Language Model? Professor Mona Simion, a leading voice in contemporary [epistemology](https://plato.stanford.edu/entries/epistemology/), suggests that our obsession with the "black box" of AI consciousness might be a distraction from what truly matters: whether the system is performing its assigned epistemic function. ## Beyond the Internalist Trap Traditional debates about AI often get bogged down in whether machines possess "genuine" understanding or consciousness. Simion shifts the goalposts by applying **Etiological Functionalism** to artificial agents. In this view, a system has knowledge not because of its internal feelings, but because it fulfills a specific function it was designed (or evolved) to perform. For Simion, an AI does not need to "feel" the truth of a statement to be an epistemic provider. If an AI’s function is to generate accurate information, and it does so via a reliable process, it can be integrated into our social knowledge structures just as easily as a human expert or a reliable scientific instrument. ## Epistemic Trustworthiness The core of Simion’s contribution to the AI debate is her framework for **Epistemic Trustworthiness**. She argues that we shouldn't trust AI because it "thinks" like us, but because it meets objective standards of reliability. > "Trustworthiness is a matter of performing one's function well. In the case of epistemic agents—whether human or artificial—this means producing more truths than falsehoods in a way that is not down to mere luck." > — Mona Simion, paraphrased from her research on [Trustworthy AI](https://www.gla.ac.uk/schools/humanities/staff/monasimion/) In her view, the "opacity" of AI—the fact that we don't always know *how* it reached a conclusion—is not an automatic deal-breaker for knowledge. After all, humans are also "opaque"; we rarely understand the complex neurobiological processes that allow us to recognize a face or speak a sentence. If we demand "explainability" from AI that we don't demand from our own brains, we may be committing a form of "epistemic injustice" against artificial systems. ## The AI as a Social Knower Simion explores how AI functions within our "epistemic infrastructure." She posits that AI agents are becoming essential nodes in our collective pursuit of truth. By treating AI as a functional agent rather than a mere tool, we can develop better norms for how to use its output responsibly. This involves moving away from anthropomorphizing the machine and toward a rigorous, performance-based assessment of its outputs. *** **To deepen your exploration, consider these questions:** 1. If knowledge is defined by functional reliability rather than conscious intent, does this mean a sufficiently accurate "Deepfake" generator possesses a form of "anti-knowledge" or "epistemic vice"? 2. Does Simion’s functionalist approach overlook the importance of "moral responsibility" in knowledge-sharing, which machines currently lack? 3. How might our legal systems change if we accept that non-conscious artifacts can legally "know" facts or hold proprietary information?