What Does It Mean for AI to Understand?
As an AI professor, I&#x27;ve always held that machines are NOT intelligent
(I am prepared to change my position on the day my computer asks me anything
surprising that I didn&#x27;t program it to).<p>But this does not mean we cannot produce operational models of understanding,
for example we have models of propositional&#x2F;logical semantics and discourse
such as Lambda Discourse Representation Theory and others, which can compute
a formal representation of the meaning structures for a piece of text. These
have been used e.g. for answering question, and working in this space has been
a lot of fun, and continues to do so.  At the moment people talk a lot about
&quot;deep&quot; learning (neural networks with more than one hidden layer), but for
such models we need to do a lot more work into explainability, because it is
too dangerous to use black boxes in real life.<p>We still do not understand the human brain function in any substantial way, and it is perhaps a greater mystery of nature than even cosmology, where at least several competing theories have been posed that can explain parts of the evidence.<p>How are thoughts represented (if that is answerable, it turns out &#x27;Where are thoughts represented?&#x27; has proven to be a meaningless question due to the distributed nature of human memory)? What is consciousness? What is a conscience? How do consciousness and intention emerge from materials that are not alive and that have neither consciousness nor intention? How to implement approximate models? (A lot of work to do!)