| Inter-Pillar Relationships |
| Pillar: Societal Empowerment |
|
Sustainability vs. Transparency |
■ Neutral
|
Sustainability and transparency influence AI’s lifecycle but don’t directly conflict or reinforce, promoting governance synergy
(van Wynsberghe, 2021 )
|
Deploying sustainable AI while maintaining transparency in energy sourcing exemplifies balanced governance goals in AI systems
(van Wynsberghe, 2021 )
|
|
Human Oversight vs. Transparency |
■ Reinforcing
|
Human oversight and transparency collectively foster accountability, enhancing ethical governance in AI systems
(UNESCO, 2022 )
|
In AI-driven medical diagnostics, both drivers ensure user trust and effective oversight
(Ananny & Crawford, 2018 )
|
|
Transparency vs. Trustworthiness |
■ Reinforcing
|
Transparency enhances trustworthiness by clarifying AI operations, fostering informed user relationships
(Floridi et al., 2018 )
|
Transparent AI applications provide clear justifications for decisions, leading to higher user trust
(Floridi et al., 2018 )
|
| Cross-Pillar Relationships |
| Pillar: Ethical Safeguards vs. Societal Empowerment |
|
Fairness vs. Transparency |
■ Reinforcing
|
Transparency in AI increases fairness by allowing for the identification and correction of biases
(Ferrara, 2024 )
|
Transparent hiring algorithms enable fairness by revealing discriminatory patterns in recruitment practices
(Lu et al., 2024 )
|
|
Inclusiveness vs. Transparency |
■ Reinforcing
|
Both inclusiveness and transparency promote equitable access and understanding in AI, enhancing collaborative growth
(Buijsman, 2024 )
|
Diverse teams enhance transparency tools in AI systems, ensuring fair representation and increased public understanding
(Buijsman, 2024 )
|
|
Bias Mitigation vs. Transparency |
■ Reinforcing
|
Bias mitigation relies on transparency to ensure fair AI systems by revealing discriminatory patterns
(Ferrara, 2024 )
|
Transparent algorithms in recruitment help identify bias in decision processes, ensuring fair practices
(Ferrara, 2024 )
|
|
Accountability vs. Transparency |
■ Reinforcing
|
Transparency supports accountability by enabling oversight and verification of AI systems’ behavior
(Dubber et al., 2020 )
|
In algorithmic finance, transparency enables detailed audits for accountability, curbing unethical financial practices
(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 )
|
| Pillar: Operational Integrity vs. Societal Empowerment |
|
Governance vs. Transparency |
■ Reinforcing
|
Governance frameworks enhance transparency, mandating disclosure and open practices to ensure accountability in AI systems
(Bullock et al., 2024 )
|
Governance laws requiring transparent AI audits bolster accountability, fostering public trust in government-aligned AI use
(Batool et al., 2023 )
|
|
Robustness vs. Transparency |
■ Reinforcing
|
Robustness enhances transparency by providing consistent operations, reducing opaque behaviors
(Hamon et al., 2020 )
|
Greater AI robustness minimizes erratic outcomes, facilitating clearer system transparency
(Hamon et al., 2020 )
|
|
Interpretability vs. Transparency |
■ Reinforcing
|
Interpretability enhances transparency by providing insights into AI mechanisms, fortifying user understanding
(Lipton, 2016 )
|
Transparent models boost public trust, as stakeholders understand how AI decisions are made clearly
(Lipton, 2016 )
|
|
Explainability vs. Transparency |
■ Reinforcing
|
Both explainability and transparency enhance trust by making AI systems’ inner workings and decisions understandability essential for accountability
(Cheong, 2024 )
|
In healthcare AI, both drive accessible patient diagnosis explanations and transparent model algorithms
(Ananny & Crawford, 2018 )
|
|
Security vs. Transparency |
■ Tensioned
|
Security needs might impede transparency efforts, as disclosure could expose vulnerabilities
(Bullock et al., 2024 )
|
When AI transparency compromises security, it can lead to potential breaches, hindering open communications
(Bullock et al., 2024 )
|
|
Safety vs. Transparency |
■ Reinforcing
|
Transparency reinforces safety by enabling detection and mitigation of risks effectively
(Leslie, 2019 )
|
Clear documentation of AI processes ensures safety, enabling effective oversight and risk management
(Leslie, 2019 )
|
RAISEF
