Principles

Minimise risks of harms

Challenge Instances Gathering personal digital data requires consideration of its management, potential for reidentification, and issues around (dis)aggregation Outcome fairness and bias in the outputs of models It is not clear what the impact of AI use will be on psychological and emotional wellbeing As AI is anthropomorphised and used to display synthetic affective capacity, it is not clear what impact this will have on human interactions and affect Incidental findings

Challenges Respect for diversity, non-discrimination, and fairness

Overarching Focus

Overarching Principles Beneficence

Sources National Statement on Ethical Conduct in Human Research

Strategies Questions to consider regarding re-identification and issues of justice in IP Questions to consider regarding re-identification and disciplinary methodological norms Questions to consider in assessing risk of harms Principle of Discriminatory non-harm for fairness, key considerations for data fairness Principle of Discriminatory non-harm for fairness, key considerations for design fairness Principle of Discriminatory non-harm for fairness, key considerations for outcome fairness Principle of Discriminatory non-harm for fairness, key considerations for implementation fairness Questions to consider in key stages of AI and machine learning based research, regarding data collection Questions to consider in key stages of AI and machine learning based research, regarding project data governance Questions to consider in SoTL research method selection Questions to consider in SoTL research dissemination Guiding questions for educators regarding Privacy and Data Governance of AI in Education Considerations in assessing trustworthy AI - Resilience to attack and security Considerations in assessing trustworthy AI - Fallback plan and general safety Considerations in assessing trustworthy AI - Accuracy Considerations in assessing trustworthy AI - Reliability and reproducibility Considerations in assessing trustworthy AI - Unfair bias avoidance Considerations in assessing trustworthy AI - Accessibility and universal design Considerations in assessing trustworthy AI - Minimising and reporting negative impacts Considerations in assessing trustworthy AI - Documenting trade-offs

Child Of Beneficence

Created At 2023-05-18T14:25:20.000Z

Title Minimise risks of harms