Concern 705 · Working draft · editorial review in progress

Right-to-explanation for workers

A worker explanation gap exists when someone cannot understand how an automated system influenced their pay, tasks or evaluation.

Understanding the concern

Knowing that AI is used is only a start. A worker may need to know which records mattered, how errors can be corrected and who is responsible for the result. A vague statement that 'the system decided' leaves little basis for responding, even if the decision was made partly by a manager.

Some legal frameworks provide information and review rights in defined settings, but their scope and implementation vary. An explanation should work like a useful receipt: enough detail to understand the outcome and identify a mistake. It need not expose every line of software to be meaningful, but it should describe the actual reasons that affected the person.

An example

A worker receives a lower performance rating but is told only that it came from an automated assessment.

Illustrative unless identified as a documented case.

Words in plain English

AI
Software that learns patterns from examples or uses rules to perform tasks such as recognizing images or generating text. It can make mistakes and does not understand every situation as a person would.

Evidence and its limits

EU data-protection and platform-work provisions have conditions and implementation details. They are not a universal unconditional right to every algorithm's source code.

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Broader frameworks and background

These resources provide context. They do not establish every claim in this concern.

A question to discuss

What explanation would let the worker identify an error and make a meaningful response?

Keep track of different views, what needs checking, and any next step in your own discussion notes.

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Principles for the conversation

Before you finish · reflect together

Virtues and principles to consider

Virtues are qualities we practice in how we treat people and make choices. They are not scores for judging someone. Use these ideas to explore what a thoughtful response could look like.

Seeing potential

Seeing potential means recognizing people's capacity to learn, contribute, and grow. It resists reducing someone to a score or to the tasks a machine can perform faster.

Use tools to support people's development. Give learners time, feedback, and real opportunities to practice. A prediction about someone's performance should not close off their future.

Ask together: How could this help people develop abilities they value?

Solidarity

Solidarity means standing with people whose lives are affected, especially when they have less power to protect their interests. It turns concern into a willingness to share responsibility.

Include affected people in decisions and support practical remedies when something goes wrong. Do not leave the cost of learning or repair entirely with those who were harmed.

Ask together: What would it mean to stand with the people carrying the greatest burden?

Dignity

Dignity means recognizing each person's worth regardless of usefulness, status, or a system's score. People deserve respect and a voice in matters that affect them.

Explain important decisions, avoid humiliating treatment, and keep room for a person's story. Do not treat a prediction as a complete account of who someone is.

Ask together: Does this use treat each person as someone whose experience matters?

Editorial ratings

These are editorial judgments from the register, not measured probabilities or predictions about your situation.

Severity
Serious · 3/5
Likelihood
Documented at scale · 5/5
Time horizon
Now
Register risk score
15
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