So what’s new? This is where the jargon gets thick. AI folks refer to cognitive computing, symbolic AI, rule-based algorithms, machine learning, and deep learning. The layperson might see these as interchangeable. They are not. The battle across methods — old school, new school, or combinations of these — is where regulators, politicians and the general public will need to focus their attention. This will not be trivial given the lack of understanding of the complicated systems being developed.
Generative AI methodologies have been around for more than 30 years. The famous CoverStory methodology co-authored by MIT’s John DC Little in 1990 stands out as a breakthrough application for business. The method added an authoring layer on top of an algorithm layer that leveraged scanner data. It was created to produce news for marketing managers by discovering algorithmically, among other things, competitor actions and sending a memo on ideas on how to respond.
From such early applications came companies such as Narrative Science, which created financial news for businesses using natural language generation. Research reports, weather reports, crossword puzzle books, games, short videos and a slew of other formats have used generative methodologies to create content.
