Defining “Human-in-the-Loop”

Human-in-the-loop (HITL) is the inclusion of people in an AI-based, or automated, workflow. Instead of viewing automation as a replacement for human beings and human-based work, HITL approaches it as a collaboration between humans and machines working alongside one another. Specifically, the technology handles tasks involving speed, scale, and repetition, while the human(s) deal with ambiguity, context, values, accountability, and exceptions (Stryker, n.d.).

The Problem with Standard “Human-in-the-Loop” Thinking in Education

Students will often do the minimum possible without motivation/incentive to do otherwise. This is not because they are bad people or trying to be deliberately sneaky, but rather because they are constantly making time- and resource-based decisions. Which assignments/classes should be given priority when there is not enough time to complete everything? College students today are busy balancing studies, family responsibilities, job/work, and many other competing priorities. The danger with HITL in education is that we assume students will use the technology only for speed, scale, and repetitive tasks, but will certainly wrestle with the accountability, context, and exception portions themselves. However, what happens when students rely on AI for everything? I think we are seeing the consequences of that currently playing out.

Challenging AI

So, what can be done to ensure humans maintain control of critical decision-making, and in our context, ensuring students actually learn? Humans’ ability to question an answer, aka “human judgment,” may be the answer. Consider what Stricker (2026) says, “Part of our job has always been to cultivate the capacity to notice when you are being steered: to ask who framed the question, what was left out, and why one answer carries more weight than another.” In other words, business education must now prepare graduates not only in the realm of domain expertise, but also with problem framing, critical judgment, context/ethics, and accountability.

Pro Tips for Maintaining Your Human Advantage

Continuing with the themes from above, here are a few specific classroom strategies for maintaining your human advantage in business education:

  1. Interrogate the framing – For example, asking AI about a company layoff situation may frame it as an organizational cost decision until students deliberately reframe it as an HR or business capability decision.

  2. Read the actual source – Try treating the assignment/task as professional due diligence for business students rather than a simple deliverable.

  3. Be wrong in front of someone – Particularly in oral defense or discussion-based scenarios, student panelists should be rewarded/incentivized to probe for faulty assumptions.

Reflection Questions:

  1. Where might students be approving AI-assisted work rather than actually judging it?

  2. When students prompt AI for help, who is framing the question — the student or the system? What is one assignment that could require them to frame the problem themselves before the tool opens?

  3. Can you think of one task where students should have to defend their reasoning out loud – "be wrong in front of someone" – instead of only submitting a polished deliverable?