Health, Pace and Burnout: Occupational Safety Under Algorithmic Direction

All courses / AI Boss / Module 3 / Chapter 14

Learning objectives

After the lesson the participant can:

Explain with the strain models where algorithmic direction is predicted to harm health.
Assess the strength and limits of the evidence on algorithmically set pace and injury.
Explain why a software-set work-rate is a working method the employer must assess and consult on.
Write health and rest constraints as hard constraints with sources and tests.

Key concepts

Unhealthy workload: As the Swedish Work Environment Authority defines it: demands that more than temporarily exceed resources, becoming unhealthy when the imbalance is long-lasting and recovery is insufficient.
Hard and soft constraints: By default everything with a legal or agreed source is hard; preferences are soft and breached only with a recorded reason. A constraint without a source is negotiated away by the first person who finds it inconvenient.
Feasibility condition: A hard constraint the optimiser cannot trade for output. The contract requires this in place of a penalty term, because enough output always outweighs a penalty.
Seeded breaches: Known breaches inserted on every change to confirm that the constraint tests catch them; WRA-NR-HC-01 seeds 12 per release.
Care designed in, not delegated: The duty of care stays with the line manager, the safety representative and the committee that approves the limits, while the system contributes enforcement and detection at Level 1 Assisted.

Interactive exercises

Do them here and get feedback at once. Choose a card and then where it belongs, or drag it.

Interactive exercise 1 · Match

The employer's duty, instrument by instrument

Match each legal instrument with what Chapter 14 reports that it requires. These are organisational implications, not legal advice.

Interactive exercise 2 · Scenario

A queue that sets the pace

Apply the chapter's reasoning on M5 Care to the situation below, which follows Hansa Mutual's example.

Teaching plan

15 min	The teacher presents the demand-control and effort-reward models and has participants predict the effect of three design choices: shorter planned times, a fixed visit order, a removed colleague.
10 min	Evidence review: what the warehouse analyses, the EU-OSHA findings and the schedule studies measured, who produced them and what the chapter says lifts them above a claim.
15 min	Staged debate in four steps; the class names the three conditions both sides accept and the verdict's labels.
25 min	Exercise: groups write constraints with source, class and test for one optimiser, with strain indicators and a manual fallback.
10 min	Debrief on Hansa Mutual: why declining to delegate care removes the instrument that would show the risk, and how AIDR-0685 answers with a team-level indicator and a cap.

Discussion

The route contested in CNT-NR-0001 complied with every working-time rule and still could not be worked. What does that say about the limits of legal constraints as a measure of safe pace?
The case for calm says a system that checks every pair of shifts overlooks a rest rule less easily than a manager drafting by hand. What must also be true for that advantage to protect health?
Section 7 of chapter 2 of AFS 2023:2 requires that workers know which tasks to prioritise when time does not suffice and whom to turn to. How would you test a dispatch system against it?

Written exercise

Exercise · 25 minutes

Health constraints as tests

For one system that performs M1 Direction, such as ShiftWise routes in home care or the allocation rules of a claims queue, write at least four health and rest constraints. For each give the rule, its source (law, collective agreement, risk assessment or a rule agreed with representatives), its class as hard or soft, its owner and a one-sentence description of the test that would run on every draft plan before it reaches the approving manager. Add the breaches you would seed on each release, the monthly team-level strain indicators and their recipients, who may invoke the manual fallback and how often it is tested, and which changes require assessment and consultation beforehand.

Deliverable: A constraint table in the form of WRA-NR-HC-01 revision 2 with source, class, owner and test, plus seeded breaches, strain indicators, stop path and change triggers.

Your work

Self-test

Choose an answer to see whether it is right, or open the answer below each question.

Which hard constraint did revision 2 of WRA-NR-HC-01 add after the contestation CNT-NR-0001?
Show the answer
D. Travel time between visits of at least routed time plus 5 minutes, with a minimum of 10 minutes
The contested route left no time to travel between two visits. The revised assessment made travel time a hard constraint written as a test, so a breaching route cannot reach the approving manager; AIDR-0605 records the decision.
Why does the chapter's practical guide require that hard constraints be feasibility conditions and not penalty terms?
Show the answer
A. Because enough output always outweighs a penalty
A penalty is weighed against output in the objective, so the optimiser will cross the limit when the gain is large enough. A feasibility condition is a limit the system cannot trade for output.
How does the chapter's verdict label the claim that AI agents assigning office work raise burnout?
Show the answer
C. Speculation until measured
Harm from algorithmically set pace is observable in warehouse work and expected in sectors such as home care and claims queues; for office agents theory predicts it where they raise demands and remove control, and the opposite where they remove drudgery.