Identification rates for prohibited AI systems by stakeholder category (Phase 3)
| Prohibited practice (Art. 5) | Civil Society (n = 54) | Industry(n = 180) | CSO/ind. Ratio | Academia (n = 41) | Citizens (n = 22) | Public Auth. (n = 31) |
|---|---|---|---|---|---|---|
| Manipulation/deception (1)(a) | 63.0% | 14.4% | 4.4× | 36.6% | 40.9% | 22.6% |
| Exploitation of vulnerabilities (1)(b) | 59.3% | 10.6% | 5.6× | 26.8% | 27.3% | 16.1% |
| Social scoring (1)(c) | 40.7% | 16.1% | 2.5× | 26.8% | 40.9% | 12.9% |
| Crime risk prediction (1)(d) | 51.9% | 5.6% | 9.3× | 9.8% | 18.2% | 3.2% |
| Facial image scraping (1)(e) | 55.6% | 6.1% | 9.1× | 19.5% | 13.6% | 3.2% |
| Emotion recognition (1)(f) | 53.7% | 10.6% | 5.1× | 22.0% | 13.6% | 16.1% |
| Mean across prohibitions | 54.0% | 10.6% | 5.1× | 23.6% | 25.8% | 12.4% |
| Prohibited practice (Art. 5) | Civil Society ( | Industry( | CSO/ind. Ratio | Academia ( | Citizens ( | Public Auth. ( |
|---|---|---|---|---|---|---|
| Manipulation/deception (1)(a) | 63.0% | 14.4% | 4.4× | 36.6% | 40.9% | 22.6% |
| Exploitation of vulnerabilities (1)(b) | 59.3% | 10.6% | 5.6× | 26.8% | 27.3% | 16.1% |
| Social scoring (1)(c) | 40.7% | 16.1% | 2.5× | 26.8% | 40.9% | 12.9% |
| Crime risk prediction (1)(d) | 51.9% | 5.6% | 9.3× | 9.8% | 18.2% | 3.2% |
| Facial image scraping (1)(e) | 55.6% | 6.1% | 9.1× | 19.5% | 13.6% | 3.2% |
| Emotion recognition (1)(f) | 53.7% | 10.6% | 5.1× | 22.0% | 13.6% | 16.1% |
| Mean across prohibitions | 54.0% | 10.6% | 5.1× | 23.6% | 25.8% | 12.4% |
Identification rate = percentage of each stakeholder group answering “Yes.” n = 379 (raw CSV data). The mean ratio reported in the surrounding text (5.1×) is a simple arithmetic mean across the six prohibition categories
Sharing content requires targeting cookies to be enabled. Please update your cookie preferences to use this feature.