
Lesson · 4 min Stretch
Who Answers for the Machine?
In one line When a system decides, someone must still be able to explain the decision and correct it.
More decisions are made, or shaped, by software: who gets a loan, which posts are shown, which patients are flagged. When something goes wrong, it is tempting to say the system did it. But a system has no one to blame, thank or ask for reasons.
Philosophers call this a responsibility gap: harm occurs, yet no person seems clearly answerable. Closing it needs a named owner for each system, a way to explain a decision in plain terms, and a way for a person affected to appeal.
None of this says that machines are bad. It says that using a tool does not remove the duty to answer for how it is used. A good test is simple: if the decision is wrong, who will you ask, and can they change it?
The loan app

Ruth applies for a small business loan through an app and is refused in a minute. The screen says only, “Not eligible.” She calls the bank, and the clerk says the system decides.
Ruth asks who owns the system. The clerk finds a manager, who looks at the record and finds that the app misread her income. The decision is reversed, and the bank adds a plain-language reason and an appeal link to every refusal.
Try this today For one automated decision you meet, find who could explain it to you and who could reverse it.
Cite or share this lesson
A plain reference you can paste into notes or an essay:
Quest2Reason. “Who Answers for the Machine?.” https://quest2reason.com/learn/lesson/who-answers-for-the-machine. Accessed 13 November 2026.
Sources
- Stanford Encyclopedia of Philosophy, “Ethics of Artificial Intelligence and Robotics” — Covers accountability, transparency and bias in automated decision systems.
- Wikipedia, “Ethics of artificial intelligence” — Overview of debates on responsibility and fairness in AI.
- Andreas Matthias, “The Responsibility Gap: Ascribing Responsibility for the Actions of Learning Automata” (Ethics and Information Technology, 2004) — The paper that named the gap: harm from a learning machine with no person clearly answerable.
