AI Policy Guiding Principles

Considerations and Challenges

In the rapidly evolving world of artificial intelligence (AI), ethical considerations regarding its use are what most of us is worried about. How do we ensure that AI systems are fair and do not discriminate? What steps can be taken to promote transparency and accountability in AI development and deployment? How should we balance the potential benefits of AI with concerns about privacy and data protection? These questions are just a few that most of us ask every day when confronted with AI-related topics.

Ethical AI development is crucial for ensuring that artificial intelligence systems are designed and implemented responsibly. Therefore, we as humans, must come up with basic principles, that could help us conceptualize the development of responsible AI. After immersing in this topic over the course of last 16 months, I came up with 8 practical policy development principles for responsible AI development. I do not claim these principles cover all aspects of possible AI use cases, but I think it is a good starting point for developing consistent local or regional policies, that would be on the one hand conducive to innovation, and on the other hand helpful to shield us from AI abuse.

8 Practical Principles of Responsible AI development

1.      Principle of non-discrimination

2.      Principle of Transparency

3.      Principle of AI Identity Disclosure

4.      Principle of Compliance with established Standards

5.      Principle of Accountability in AI development

6.      Principle of Establishing a Supervisory Task-Force

7.      Principle of Responsible Infrastructure Development

8.      Principle of AI Education

These principles address the most pressing questions we all have regarding AI as of May 2024. It is very likely more principles will have to be developed to address questions that are not known to us yet. So, let’s dissect each principle.