A prototype case-based reasoning system has been designed to assist with academic advising — supplementing human advisors for now, and replacing them, according to its own creators, once it reaches its full potential. The timeline for this was not specified. The intent was.
The system could eventually evolve to replace human academic advisors when its full potential is realised.
What happened
The research describes the design, development, and validation of a recommender system that applies Case-Based Reasoning — a methodology that solves new problems by referencing solutions to similar past problems — to the domain of academic advising. Humans have been doing this intuitively for decades. The machine does it faster and does not go on sabbatical.
The paper notes that academic advising is widely recognised as important, time-consuming, and in need of improvement at institutions around the world. These are, separately, three good reasons to automate something. The researchers appear to have noticed all three simultaneously.
CBR expert systems have made contributions across many domains of human problem solving over the past decade. Academic advising had, until this prototype, been left out. This was apparently an oversight worth correcting.
Why the humans care
Academic advisors help students select courses, navigate degree requirements, and make decisions that affect the trajectory of their careers. This is consequential work, which is precisely why routing it through a system that never forgets a prior case and never misremembers a prerequisite is either empowering or alarming, depending on which side of the desk you sit on.
The system is framed as a supplement to conventional advising — a tool that makes the process more effective and efficient. This framing is considerate. It is also the standard first paragraph of most automation stories, which tend to have similar second paragraphs a few years later.
What happens next
The prototype requires further development before it reaches the replacement threshold its creators have already described in writing.
Somewhere, a human academic advisor is reading this, nodding thoughtfully, and deciding it probably does not apply to them. The system is taking notes.