Why Explainable AI Actually Matters

This article by a newly minted PhD who spent years studying artificial butter in the early twentieth century somehow managed to make it one of the sharpest commentaries on modern artificial intelligence (AI) that I have seen in a while. On the surface, butter and algorithms do not seem like obvious companions. Look a little closer and suddenly the parallels start stacking up like toast at breakfast. This interesting, humorous but ironic article came to our attention from Algorithm Watch in their article, “What artificial butter tells us about Artificial Intelligence.”

Back then, artificial butter was born out of necessity, power imbalances and technological wizardry that turned raw inputs into something that looked and tasted close enough to the real thing. It was cheaper, more accessible and for many people, the only viable option. Critics panicked. Culture was under threat. Nations worried about moral decay. Machines were sold that promised to detect fake butter and absolutely did not work.

Fast forward a century and swap margarine for large language models (LLMs). We are watching systems trained on the labor of people with limited alternatives produce text, images and answers that look convincingly human. Not better than the real thing, just cheaper and easier to access. People are not turning to AI because it is their first choice. They are turning to it because it is available, affordable and often the least bad option in a system that has already failed them.

The author made an uncomfortable but accurate point. Many users know these systems are deeply flawed. Students know chatbots do not teach them much. Professionals know the output can be shallow or outright wrong. But they also know that shallow output is sometimes exactly what institutions reward. In that sense, AI is not breaking the system. It is reflecting it back to us with unsettling clarity.

Where the article becomes especially useful for today’s conversations is in what it implies about responsibility. When artificial butter became unavoidable, governments stepped in. They regulated it, renamed it and tried to impose some order on a technology that people were not going to abandon on their own. The author jokingly suggests that perhaps AI deserves the same treatment, right down to a rebrand. MargAIrne is funny because it lands uncomfortably close to the truth.

Here is where explainable AI enters the room, clears its throat and asks for a little attention. The real danger is not that AI produces artificial outputs. We have always lived with substitutes. The danger is that these systems increasingly influence decisions without anyone being able to clearly explain how or why a particular result was produced. Butter substitutes did not decide who got healthcare, loans, parole or information. AI systems do.

Explainable AI is not about making models feel warm and fuzzy or adding a compliance checkbox. It is about accountability in a world where automated systems shape real outcomes. If an AI system gives medical advice, recommends a policy decision or determines access to resources, we need to understand its reasoning, its limits and its failure modes. Otherwise we are back to selling fake butter detectors that do not work and pretending that makes us safer.

The butter analogy also reminds us of something else. Artificial substitutes tend to become invisible over time. Margarine is now just another item in the dairy aisle. AI risks becoming the same kind of background presence, quietly embedded everywhere, quietly shaping norms, quietly rewriting expectations. That is precisely why explainability matters now, not later.

When artificial systems become the default, transparency is the only thing standing between convenience and quiet harm. If we are going to live in a world full of AI, the least we can ask is that it explain itself.

Melody K. Smith

Data Harmony is an award-winning semantic suite that leverages explainable AI.

Sponsored by Access Innovations, the intelligence and the technology behind world-class explainable AI solutions.