Examples

The catalogues serve as a tool to locate and learn about specific content included in the PIO Model. This catalogue contains the legal standards on which the PIO Model questions are based. It also lists texts of other typologies that contain recommendations regarding the ethical use of AI.

Traceability and representativeness

Model PIO question

UK Department for Work and Pensions
1.3.2
Age (H)
1.3.3
Municipal Data Office (H)
1.3.4
Sepsis model, health system
1.3.1

Communication protocols

Model PIO question

Digital mailbox (H)
1.4.1
Ethics Committee (H)
1.4.3
Incident (H)
1.4.4

Inclusion and diversity

Model PIO question

Allenghey, family screening
2.1.2
System design (H)
2.1.3
Gameface Project
2.1.9
Passport issued by the United Kingdom
2.1.1
Electronic voting (H)
2.1.10

Identification and mitigation of bias

Model PIO question

GRADE algorithm
2.2.1
ForHumanity Audit
2.2.4
Biased output warning (H)
2.2.10
Google Fitbit
2.2.6
Various demographic group (H)
2.2.5
Ethics and diversity expert
2.2.3
Predefined rules and limits (H)
2.2.8
Review of data (H)
2.2.11
Random Undersampling or Random Undersampling
2.2.2

Operation of the system

Model PIO question

Audit (H)
3.1.4
Google search engine
3.1.3
Tay , Chatbot de Microsoft
3.1.1
Protected data (H)
3.1.5

Traceability for risk management

Model PIO question

Social assistance (H)
3.2.4
CV selection
3.2.1
Telephone scam
3.2.8
Chest injuries
3.2.9
Protocol (H)
3.2.2
Risilinc
3.2.3
Autonomous vehicle (H)
3.2.7
Social networks (H)
3.2.5

Security mechanisms

Model PIO question

Tay, Chatbot de Microsoft
3.3.2
Citizenship data (H)
3.3.1
Google Translate
3.3.4
Traffic network (H)
3.3.3

Protection against attacks

Model PIO question

Visual works (H)
3.4.2
Firewall, security system
3.4.1

Control

Model PIO question

Dismissal Mr.Diallo
4.1.4
Specialised training
4.1.1
MasterCard
4.1.2
Responsible person (H)
4.1.5
Continuous monitoring protocol (H)
4.1.6 
Manual review (H)
4.1.3

Accountability

Model PIO question

Ethics Committee
4.2.3
Transparency Portal (H)
4.2.4
Civil Liability
4.2.1

Protection figures

Model PIO question

Liability insurance (H)
4.3.3
Cambridge Analytica
4.3.1

Capacity of the IA

Model PIO question

Mapfre
4.4.1
Kitchen Robot (H)
4.4.2

Promoting a culture of ethics and responsibility

Model PIO question

Control of the use of HR & Welfare (H)
4.5.4
AI Accountability Institute
4.5.1
Ethics Officer
4.5.2

Protection of privacy

Model PIO question

Access to sensitive information (H)
5.1.9
Ring and Alexia
5.1.7
Consent to the use of data (H) en l’ús de dades (H)
5.1.6
Deletion of personal data (H)
5.1.4
Random identifiers (H)
5.1.10
Biomedical identification
5.1.8
Facial images
5.1.5
Meta, non-compliance with Data Protection Law
5.1.2
Persons with functional diversity (H)
5.1.11
Ring, Amazon's subsidiary in video surveillance cameras
5.1.1
VEIL system. AI, health data
5.1.3

Data governance

Model PIO question

ADP, anonymiser of payrolls
5.2.8
K-means clustering, unsupervised learning algorithm
5.2.7 
Less sensitive data (H)
5.2.6

Impact on users' capacities

Model PIO question

Personal Assistant (H)
6.1.1
BlenderBot3, conversational robot
6.1.6
Colon cancer
6.1.3
ChatGPT (H)
6.1.4
Coffee Meets Bagel
6.1.2
Adaptive AI
6.1.7
Scope Charity
6.1.5

Perception of the system

Model PIO question

Adaptability (H)
6.2.7
Transparent algorithms (H)
6.2.2
Autonomy (H)
6.2.4
Risk assessment (H)
6.2.6
Filter one.com
6.2.8
Emmi, Mediamarkt's virtual assistant.
6.2.1
Monitoring of AI systems
6.2.5
Control and modification of AI decisions
6.2.3

Sustainable development

Model PIO question

Social access
7.1.3  
Labour Summit
7.1.7
Delivery of products
7.1.1
International Labour Organisation
7.1.4
IKI Project
7.1.2
Treatment of persons involved in data labelling(H)
7.1.5
Stable Diffusion
7.1.6

Legal catalog and recommendations

Legal standards on which the questions in the PIO Model have been based.

See Legal Catalog
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