Do you believe Semantics and how we use language, more important or less important than ethics? in the world of AI and is semantics relevant? Is meaning more important than understanding?
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I think they both play crucial roles and I do not think one or the other is more or less important. Semantics is vital for technical functioning of AI. Ethics is there to make sure our AI systems are used responsibly, fair and respectful to human values.
Semantics makes sure our AI systems can generate human-like responses. Can it accurately interpret user queries and provide relevant answers? If we do not have proper semantics, our AI system might misinterpret the context or intent behind a query, leading to incorrect or irrelevant responses.
Ethical considerations help prevent biases and promote the responsible use of AI technology.
While semantics is vital for the technical functioning of AI, ethics is equally important to ensure that AI systems are used responsibly and beneficially. Both aspects are intertwined and essential.
Appreciate the question, and cuts to something we often overlook. In short, ethics can’t stand without semantics.
If we misread intent, we act on assumptions, even the best policies or frameworks will fall short when they’re built on misunderstood meaning.
Semantics is not a layer we can gloss over. It’s how we know what people are really asking, understanding, and expecting. It’s the difference between hearing and understanding. Without it, we will erode trust, drift then suddenly, we managing outcomes we never intended to.
That’s why I would argue, you start with semantics over ethics. Because when we lose clarity then ethics becomes the noise. Having ethics over semantics, would be like a dog chasing its tail. Semantics carries meaning, ethics governs structure and effect.
I believe ethics/responsibility is foundational and somewhat orthogonal to semantics. One could argue though that if the audience does not understand, meaning is irrelevant. So ... ethics is the gatekeeper, meaning is a necessary element of the statement, and understanding is a final stage requirement for the human user to provide a suitable response to you. Simply speaking, yes, how you say it is very important and often more important than what you say.
Semantics is relevant in the sense that if people mean different things and use the same or similar terms, AI won't catch it. That presents a serious ethical fracture (e.g. biased data) in anything resulting from it.
Personally I am pushing an intiative to define colums. IT everywhere skips this critical metadata as a rule (build and rot start immediately). The business is frustrated about the lack of transparency and understanding of their own data as it runs through applications. This information significantly improves AI readiness...but guess what? That means the business is resolving what their data means and seeing logical data falicies across the estate! Language matters. It's already resulted in major changes in the way we work.
Ethics underlies all this. We want to prevent bias and insure that all are fairly served. I spent a year preaching data ethics to get where I am now with semantics.