In several articles here at CBV360, we have consistently and unwaveringly advocated for responsible AI use, as we recognize it as, first and foremost, being a powerful and useful technology, but also potentially exploitable in the wrong hands. Over the next few years, AI will become indispensable to our society and businesses–AI use will likely become akin to having internet access! If you have any doubts, see our article here about the AI Frontier. As such, the AI rules of development, deployment and engagement (DDE) need to be established today, not tomorrow.
Courtesy of ChatGPT, we have identified the following ten best practices “AI Rule Book” that we hope industry will endorse for the safe, ethical and responsible use of AI in our society–today and into the future. The irony of course is that these rules are AI generated, but ultimately this is what the future will look like–us (humans) taking AI or machine generated information and making sense of it: Choosing to accept or reject the findings, but more importantly, making the decision whether or not they suit our purpose and align with our values.
It is not about having a closed mind when it comes on to computing, AI or machine learning, if so there would not be e-commerce or online banking, which are now engrained into our everyday lives. An open-minded approach to technology entails leveraging available technologies to ensure we have current, unbiased and the most useful information to inform our decisions. We have entered an era where knowledge and information no longer represent power or value. These are now derived (or perceived) by how knowledge and information are leveraged to create new, innovative products and services–think Apple, Google, Amazon and Tesla!
AI Rule Book
These practices are intended to promote responsible and beneficial use of AI technology, fostering trust, fairness, and accountability in AI systems deployed in society.
- Transparency: Promote transparency by clearly communicating the presence and use of AI systems to users, ensuring they understand how their data is collected, processed, and utilized.
- Privacy Protection: Respect and protect individuals’ privacy by implementing robust data protection measures and obtaining informed consent before collecting and processing personal information.
- Bias Mitigation: Take proactive steps to identify and mitigate biases in AI systems, ensuring fairness and preventing discrimination against individuals based on their race, gender, ethnicity, or other protected characteristics.
- Explainability: Strive for explainable AI systems that can provide understandable explanations for their outputs and decisions, allowing users to comprehend the reasoning behind AI-generated results.
- Accountability: Establish accountability frameworks that clearly define roles, responsibilities, and liability for AI systems, ensuring that developers, operators, and users are held accountable for any potential harms caused by AI technology.
- Robust Security: Implement strong security measures to protect AI systems from unauthorized access, data breaches, and malicious attacks, safeguarding both user data and the integrity of AI models.
- Human Oversight: Ensure human oversight and control in critical decision-making processes facilitated by AI systems, with the ability to override or intervene when necessary to prevent undue reliance or potential harm.
- User Empowerment: Empower users with control over their data, enabling them to access, modify, delete, or consent to the use of their personal information in AI systems.
- Ethical Design: Incorporate ethical considerations into the design and development of AI systems, integrating ethical principles such as beneficence, non-maleficence, and respect for autonomy to guide their operation and impact.
- Continuous Monitoring and Evaluation: Regularly monitor and evaluate the performance and impact of AI systems to identify and address any unintended consequences, biases, or potential risks, and to ensure ongoing compliance with ethical standards.