Ethical Use of Generative AI

This standard defines the competencies required to promote and ensure the ethical use of Generative AI (GenAI) technologies within organisations. It focuses on identifying and addressing ethical concerns, establishing and implementing best practices, and fostering a culture of accountability, fairness, and transparency in GenAI adoption. The standard also includes the importance of evaluating the social, organisational and environmental impacts of GenAI technologies, ensuring their use aligns with ethical principles and organisational values. It emphasises the need to critically assess the broader implications of GenAI usage, including its impact on employees, automated customer service experiences, team culture, and staff morale. By ensuring these factors are considered, organisations can avoid unintended consequences and promote responsible innovation.

This standard is designed for professionals responsible for promoting ethical considerations and ensuring the responsible use of GenAI technologies within their organisations.

1. Evaluate potential ethical concerns associated with the implementation of generative AI (GenAI) tools, and their impact on employees, customers, and organisational culture.
2. Engage with stakeholders to discuss ethical challenges and implications related to GenAI applications, to include diverse perspectives.
3. Develop and communicate clear guidelines for the ethical use of GenAI, addressing issues including bias, accountability, transparency and the social impact of GenAI usage.
4. Convey ethical standards to team members and stakeholders, to promote a shared understanding of ethical practices.
5. Create training initiatives to build awareness of ethical GenAI usage.
6. Establish processes for monitoring and auditing GenAI applications to confirm compliance with ethical guidelines and identify areas for improvement.
7. Regularly assess GenAI outputs for potential biases, inaccuracies, and unintended consequences that could affect fairness, transparency and inclusivity.
8. Maintain detailed documentation of ethical evaluations, audits and bias checks in line with organisational requirements.
9. Create safe, accessible procedures that enable employees to raise ethical concerns related to GenAI.
10. Respond to ethical GenAI issues promptly and fairly in line with organisational escalation procedures.

1. Ethical principles related to GenAI, including fairness, accountability, and transparency.
2. The influence of ethical considerations in GenAI on organisational culture, employee morale, stakeholder confidence, and long-term trust-building.
3. The importance of data privacy, consent, and secure data handling in the governance of GenAI systems.
4. Approaches for balancing GenAI-driven automation with human judgement to maintain ethical, transparent, and equitable outcomes.
5. The societal impact of GenAI technologies, including potential risks and opportunities, and strategies for aligning applications with positive social and environmental goals.
6. The environmental impact of GenAI technologies, including energy consumption, carbon footprint, and resource usage, and strategies to minimise these impacts through sustainable GenAI practices.
7. Relevant regulations and standards governing ethical GenAI usage, sector-specific policies, and industry codes of conduct.
8. Organisational policies that support ethical GenAI practices.
9. Risk assessment frameworks for evaluating potential ethical and societal impacts of GenAI implementations.
10. Tools and techniques for monitoring and auditing compliance to ethical and regulatory standards in GenAI usage.
11. Methods for identifying, assessing, and mitigating biases in GenAI models and their outputs to maintain fairness and inclusivity.
12. Techniques for providing algorithmic transparency to enhance accountability in GenAI practices.
13. Approaches to embedding fairness and inclusivity in the design, development, and deployment of GenAI applications.
14. Organisational processes for documenting and auditing bias checks in GenAI implementations.
15. Approaches for effectively engaging stakeholders in discussions about ethical challenges and practices related to GenAI usage.
16. Techniques for effectively communicating ethical guidelines and expectations.
17. Methods for incorporating ethical and environmental principles into GenAI training programmes.
18. Organisational procedures for escalating and addressing ethical issues related to GenAI promptly and transparently.