On the relevance of logic for AI: misunderstandings in social media, and the promise of neuro-symbolic learning

Artificial Intelligence (AI) is widely acknowledged as a new kind of science that will bring about (and is already enabling) the next technological revolution. Virtually every week, exciting reports come our way about the use of AI for drug discovery, game playing, stock trading and law enforcement. And virtually all of these are mostly concerned with a very narrow technological capability, that of predicting future instances based on past instances. Although it is now recognized that this type of statistical associations is limited in its ability to understand the world and model its knowledge, there is still a lot of criticism and hesitancy about the use of symbolic logic to accomplish or assist in a broader vision for AI. In this article, we look at some of the assumptions held and circulated in social media about logic and point out that there are deep misunderstandings. By arguing that symbolic logic is more flexible than believed by non-experts, we make a case for Neuro-Symbolic AI offering the best of both worlds.