A few months back, I was talking to a cousin who owns and manages a large farming operation in Alberta. Towards the end of the conversation, I said that I would like to talk more about how he was using AI on this farm. He looked at me kind of strangely and replied, “Ai is so passé.” The thought of AI being old technology seems strange, until I realized we weren’t talking about the same kind of AI!

Today it seems everyone is talking about artificial intelligence. While it is true that different forms of this type of AI have been around for decades, it is only recently with advancements in big data generating capabilities, analytics, and super-fast and reliable connectivity that the technology is gaining widespread adoption. The agricultural sector is no exception.

In a newly published article written by Vijaya Lakshmi in Communications of the Association for Information Systems, we uncover a variety of technical, social, ecological, and ethical issues that hinder the adoption and full use of AI-based agricultural decision support systems. We suggest that the roadblocks and challenges of AI can be overcome through conjoint learning – meaning that the human farmers’ experience and learning can help to improve machine learning and vice versa.