| Inter-Pillar Relationships |
| Pillar: Ethical Safeguards |
|
Fairness vs. Privacy |
■ Tensioned
|
Tensions arise as fairness needs ample data, potentially conflicting with privacy expectations
(Cheong, 2024 )
|
Fair lending AI seeks demographic data for fairness, challenging privacy rights
(Cheong, 2024 )
|
|
Inclusiveness vs. Privacy |
■ Tensioned
|
Privacy-preserving techniques can limit data diversity, compromising inclusiveness
(d’Aliberti et al., 2024 )
|
Differential privacy in healthcare AI might obscure patterns relevant to minority groups
(d’Aliberti et al., 2024 )
|
|
Bias Mitigation vs. Privacy |
■ Tensioned
|
Bias mitigation can conflict with privacy when data diversity requires sensitive personal information
(Ferrara, 2024 )
|
Healthcare AI often struggles to balance privacy laws with the need for diverse training data
(Ferrara, 2024 )
|
|
Accountability vs. Privacy |
■ Tensioned
|
Accountability can conflict with privacy, as complete transparency might infringe on data protection norms
(Solove, 2025 )
|
Implementing exhaustive audit trails ensures accountability but could compromise individuals’ privacy in sensitive sectors
(Solove, 2025 )
|
| Cross-Pillar Relationships |
| Pillar: Ethical Safeguards vs. Operational Integrity |
|
Governance vs. Privacy |
■ Tensioned
|
Governance mandates can challenge privacy priorities, as regulations may require data access contrary to privacy safeguards
(Mittelstadt, 2019 )
|
Regulatory monitoring demands could infringe on personal privacy by requiring detailed data disclosures for compliance
(Solow-Niederman, 2022 )
|
|
Privacy vs. Robustness |
■ Tensioned
|
Achieving high privacy can sometimes challenge robustness by limiting data availability
(Hamon et al., 2020 )
|
Differential privacy techniques may decrease robustness, impacting AI model performance in varied conditions
(Hamon et al., 2020 )
|
|
Interpretability vs. Privacy |
■ Tensioned
|
Privacy constraints often limit model transparency, complicating interpretability
(Cheong, 2024 )
|
In healthcare, strict privacy laws can impede clear interpretability, affecting decisions on patient data
(Wachter & Mittelstadt, 2019 )
|
|
Explainability vs. Privacy |
■ Tensioned
|
Explainability can jeopardize privacy by revealing sensitive algorithm details
(Solove, 2025 )
|
Disclosing algorithm logic in healthcare AI might infringe patient data privacy
(Solove, 2025 )
|
|
Privacy vs. Security |
■ Reinforcing
|
Both privacy and security strive for safeguarding sensitive data, aligning objectives
(Hu et al., 2021 )
|
Using encryption methods, AI systems ensure privacy while maintaining security, protecting data integrity
(Hu et al., 2021 )
|
|
Privacy vs. Safety |
■ Tensioned
|
Balancing privacy protection with ensuring safety can cause ethical dilemmas in AI systems
(Bullock et al., 2024 )
|
AI in autonomous vehicles must handle data privacy while addressing safety features
(Bullock et al., 2024 )
|
| Pillar: Ethical Safeguards vs. Societal Empowerment |
|
Privacy vs. Sustainability |
■ Tensioned
|
Privacy demands limit data availability, hindering AI’s potential to achieve sustainability goals
(van Wynsberghe, 2021 )
|
Strict privacy laws restrict data collection necessary for AI to optimize urban energy use
(Bullock et al., 2024 )
|
|
Human Oversight vs. Privacy |
■ Tensioned
|
Human oversight might collide with privacy, requiring access to sensitive data for supervision
(Solove, 2025 )
|
AI deployment often requires human oversight conflicting with privacy norms to evaluate sensitive data algorithms
(Dubber et al., 2020 )
|
|
Privacy vs. Transparency |
■ Tensioned
|
High transparency can inadvertently compromise user privacy
(Cheong, 2024 )
|
Algorithm registries disclose data sources but risk exposing personal data
(Buijsman, 2024 )
|
|
Privacy vs. Trustworthiness |
■ Reinforcing
|
Privacy measures bolster trustworthiness by safeguarding data against misuse, fostering user confidence
(Lu et al., 2024 )
|
Adopting privacy-centric AI practices enhances trust by ensuring user data isn’t exploited deceptively
(Lu et al., 2024 )
|
RAISEF
