Jonathan Zittain uses the term "intellectual debt" to describe an approach to scientific discovery that begins with answers—uncovered through trial and error—and then seeks to establish explanations for them. He argues that intellectual debt is growing with increased reliance on artificial intelligence and machine learning to find correlative answers to questions in the absence of a theoretical framework to underpin them.
- AI and machine learning obscure our understanding of why things work - Zittain suggests that AI and machine learning can identify inexplicable patterns and correlations
- Abductive reasoning infers explanation from observation - Does abductive reasoning accrue intellectual debt, as well? It seeks to infer an explanation from observed details.
Zittrain, Jonathan. “The Hidden Costs of Automated Thinking.” The New Yorker, July 23, 2019. https://www.newyorker.com/tech/annals-of-technology/the-hidden-costs-of-automated-thinking.