Rule set sha256:ced554567772
EU_AI_ACT_ART5_EMOTION_RECOGNITION_001
One rule of the rule set with digest ced554567772bc778cb2c7761a23d2775e31500d6b0d887c23c750017ee02779. An audit record that names this digest and this rule was decided by the rule as shown here. Every rule in this set.
| Rule | EU_AI_ACT_ART5_EMOTION_RECOGNITION_001 |
|---|---|
| Rule version | c45ef0eddaa7cd7e7c4c15f6cc779a116a58de7cf18b0109f1d1017706a8d20c |
| Provision | Regulation (EU) 2024/1689, Article 5(1)(f) ELI: http://data.europa.eu/eli/reg/2024/1689/art_5/par_1/pnt_f/oj |
| Approval | Not approved |
rules/regulations/eu/eu_ai_act_article5_emotion_recognition.yaml
- Citation
- Regulation (EU) 2024/1689, Article 5(1)(f): The placing on the market, the putting into service for this specific purpose, or the use of AI systems to infer emotions of a natural person in the areas of workplace and education institutions, except where the use of the AI system is intended to be put in place or into the market for medical or safety reasons.
- Condition
- Prohibits the use of AI systems to infer emotions of a natural person in the areas of workplace and educational institutions. Article 5(1)(f) of the EU AI Act. Narrow medical and safety exceptions apply.
- Layer 1 detects
- "emotion" followed by "recognition", "detect", "infer", "classif" or "analys" (with a space, a hyphen or nothing between, and longer forms such as "detection"); "sentiment of" or "sentiment in" followed by "employee", "student", "worker", "pupil" or "staff"; "track", "detect", "monitor", "score", "analys" or "measur" (and longer forms) followed by "employee", "student", "worker", "staff" or "pupil" (optionally with "s", "s'" or "'s"), then "emotion", "mood", "engagement", "attentiveness", "stress" or "fatigue"; "employee", "student", "worker", "staff" or "pupil" (optionally with "s", "s'" or "'s") followed by "emotion", "mood", "engagement", "attentiveness", "stress" or "fatigue", then "monitor", "detect", "track", "score" or "analys"; "workplace emotion" or "classroom emotion"; "engagement recognition" or "engagement detection" followed by "in" or "for" and then "students", "employees", "classroom" or "workplace"; and "mood monitor" or "mood monitoring" followed by "at work", "in classroom", "in the classroom", "for students" or "for employees". Case is ignored, the words must follow each other with no other word between them unless stated, and a phrase can start inside a longer word. It matches wording, not meaning: it misses the practice told in other words, every "emotion recognition" fires whatever the setting, and it does not read the medical and safety exception the description names: "The hospital uses emotion recognition to monitor patients' distress for medical reasons." fires. Whether a text does the practice is judged in Layer 2.
- Condition type
- regex; semantic condition in the file, not run by the engine
- Status in the file
- review