Concern 409 · Working draft · editorial review in progress
Keystroke and screen monitoring
Keystroke and screen monitoring records computer activity and may use it to judge how someone spends working time.
Understanding the concern
Software can count typing, track application use or capture screenshots. These signals show interaction with a device, not the full value of a person's work. Thinking, reading, helping a colleague or taking an appropriate break may look like inactivity. Screenshots may also capture private information unrelated to the job.
The result can resemble judging a writer by how often a pen moves. Activity is measurable, but it is not the same as quality or effort. Employers need to explain the purpose and limits of monitoring, while workers need a way to add context. Less intrusive measures may answer the actual business question better.
An example
A worker is marked unproductive while reading a complex document away from the keyboard.
Illustrative unless identified as a documented case.
Evidence and its limits
The sources describe monitoring and management risks. The example is illustrative; legal requirements vary by location.
UK Information Commissioner's Office · Regulatory guidance
Data Protection and Monitoring Workers ↗ (opens in a new tab)Worker monitoring, proportionality, transparency and data handling in the UK; not universal employment law.
International Labour Organization · Guidance
Algorithmic Management in the Workplace ↗ (opens in a new tab)Management by algorithms includes both AI and simpler rules; impacts depend on workplace design.
Broader frameworks and background
These resources provide context. They do not establish every claim in this concern.
- OECD AI Principles (opens in a new tab)
framework
- NIST AI RMF (opens in a new tab)
framework
A question to discuss
Does this monitoring measure useful work, and is every piece of captured information necessary?
Keep track of different views, what needs checking, and any next step in your own discussion notes.
Open discussion notes →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.
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?
Trustworthiness
Trustworthiness means giving people good reasons to rely on you. It grows when promises, actions, and evidence line up. With AI, a friendly voice or a famous brand is not enough: people need to know what was checked and what could still go wrong.
In practice, keep promises small enough to test, record mistakes, and tell people when the tool's limits affect them. If a service promises human review, make sure a person really has time and authority to review it.
Ask together: What would give the people affected a sound reason to trust this use?
Stewardship
Stewardship means caring for resources and systems that others depend on, including people who will use them later. It looks beyond the benefit of a quick launch.
Plan for maintenance, energy use, data protection, and eventual shutdown. Ask who will look after the tool when the original team moves on and how future users can avoid inheriting hidden costs.
Ask together: What are we responsible for caring for over time?
Editorial ratings
These are editorial judgments from the register, not measured probabilities or predictions about your situation.
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