The dominant approach at the time were Expert Systems. This used a lot of carefully crafted data and manually curated facts that the inference engine can use. It also fit in a MUCH smaller footprint compared to conventional neural networks. But you also don't get real language processing, reasoning beyond the target problem domain, and stuff like that - it's laser focused and built on very small amounts of data. Much of the research from back then centers on using Lisp and Prolog of all things, so BASIC isn't a big stretch.