Guardrails for artificial intelligence (AI) are critical in ensuring safety and trust in AI systems, according to Chris Butler, Director of AI at Philosophie. He outlines a three-pronged approach to guardrails: first, understanding the problem space, then setting the constraints, and finally, monitoring the system. Understanding the problem space involves identifying the stakeholders, understanding their needs, and defining the system’s purpose.
Setting constraints is about defining the system’s behaviour, including the acceptable and unacceptable actions it can take. It also involves identifying the risks and mitigating them. The third guardrail, monitoring, involves tracking the system’s performance and making adjustments as needed.
Butler also highlights the importance of transparency in AI systems. He suggests that AI systems should be able to explain their decisions in a way that humans can understand. This will help to build trust and acceptance among users.
Butler further discusses the ethical considerations in AI, including the potential for bias and discrimination. He suggests that AI developers should strive for fairness and avoid creating systems that reinforce existing social inequalities.
In conclusion, Butler emphasises that developing guardrails for AI is a complex process that requires a multidisciplinary approach. It’s not just about the technology, but also about understanding the social and ethical implications of AI.
Go to source article: https://www.infoq.com/presentations/guardrails-ai/