Artificial Intelligence (AI) is a complex technology that is difficult to define. Responsible AI (RAI) is a subset of AI that meets specific criteria related to ethics, accountability, security, transparency, and fairness. These criteria must ensure that AI is developed, deployed, and used responsibly and ethically and considers human values and principles.
Industry, civil society, government bodies, and global entities have developed more than 200 principles to govern the responsible use of AI. These principles share some core tenets, easily remembered as HASTE:
- Human-centred, AI refers to AI that respects human rights and needs, including privacy and autonomy.
- Accountable AI means that individuals or teams are responsible for ensuring that AI does not cause harm.
- Safe and Secure AI refers to AI that is not vulnerable to cyber or physical security breaches or data leakage.
- Transparent and Explainable AI means that the workings of AI can be understood and communicated effectively.
- Ethical and Fair AI means that AI meets prevailing ethical and related standards.
These principles are aspirational and require a mixture of human processes and technical efforts to select, design, and monitor AI in a manner consistent with human, social, political, cultural, and legal values. The context of the application will determine what the principles mean and may require weighing certain principles more heavily than others.
It is essential to follow the AI life cycle to govern AI responsibly, which consists of four primary stages: use case selection, AI model development, deployment, and monitoring. At each stage, it is essential to consider the ethical implications of AI and to ensure that it meets the criteria of responsible AI.
Overall, responsible AI is crucial to ensure that AI is developed and used in a manner that is ethical, accountable, and transparent. Employing responsible AI practices will help to build trust and confidence in AI and its potential to benefit society.
Source: Lexology.com
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