AI in ECU Research: Ethical AI Use

The topics covered include:

Transparency: Transparency involves clear communication about how AI systems are developed, how they function, and how decisions are made. Researchers must ensure that their AI models and methodologies are understandable and accessible to others, promoting accountability and trust.

Lawfulness: Adhering to legal standards and regulations is crucial when using AI in research. This includes compliance with data protection laws, intellectual property rights, and other relevant legal frameworks to ensure that AI applications are lawful and ethically sound.

Fairness and Bias Mitigation: AI systems must be designed and implemented to promote fairness and avoid discrimination. Researchers should actively work to identify and mitigate biases in their AI models, ensuring that outcomes are equitable and do not disproportionately affect any group.

Proportionality: The principle of proportionality requires that the benefits of using AI in research outweigh the potential risks and harms. Researchers should carefully consider the impact of their AI applications and strive to achieve a balance between innovation and ethical responsibility.

Data Privacy and Security: Protecting the privacy and security of data is a fundamental ethical obligation. Researchers must implement measures to safeguard sensitive information, ensuring that data is collected, stored, and used in a manner that respects individuals' privacy rights and maintains data integrity.