Eka’s Weekly Roundup (22 September 2023)

Issue 47 l Principles for Responsible AI

Sep 22, 2023

Earlier this week, Camilla attended a panel on Responsible AI hosted by Local Globe. We synthesise the main points from the panel and provide context for developments in the development of responsible AI.

What we mean when we talk about responsibility 🗞️

We’ve written about the potential of AI in the past as potentially being the next platform shift. Its applications span various domains, from healthcare and finance to transportation and entertainment. But building it fairly and equitably has become more and more important as its influence grows. Responsible AI, or the practice of developing and deploying AI systems in an ethical and accountable manner, is increasingly top of mind for developers. We explore the concept of responsible AI, its importance, and the key principles that underpin its ethical use.

Understanding Responsible AI

Responsible AI, also known as ethical AI or AI ethics, refers to the set of practices and principles that guide the development, deployment, and use of AI systems in ways that prioritize human well-being and societal benefit while minimizing harm.

The Importance of Responsible AI

Ethical Considerations: The development of AI systems should be guided by ethical principles that respect human rights, dignity, and autonomy. In 2021, OpenAI chose not to pursue military applications for its AI technology, emphasizing the importance of ethical considerations in AI development. Though more recently, OpenAI hasn’t been open (😊) about whether The Pentagon has been allowed to use GPT.
Legal and Regulatory Compliance: Many countries are enacting laws and regulations to govern AI technologies. The European Union's Artificial Intelligence Act aims to establish a comprehensive regulatory framework for AI, emphasizing the need for legal compliance.
Mitigating Bias and Discrimination: AI systems can inherit biases from the data they are trained on. A study published in the Proceedings of the National Academy of Sciences found evidence of racial bias in healthcare algorithms, reinforcing the urgency of addressing bias in AI for fair outcomes.

Key Principles of Responsible AI

Transparency: Developers should be transparent about how AI systems make decisions.

Fairness: AI systems must be designed to provide equitable outcomes for all users, regardless of their race, gender, age, or other characteristics.

Accountability: There should be clear lines of accountability for AI systems.

Privacy: Privacy is a fundamental human right. The General Data Protection Regulation (GDPR) in Europe sets strict rules for the handling of personal data and imposes fines for non-compliance.

Human Oversight: While AI can automate many tasks, human oversight is essential. The U.S. Department of Transportation requires that autonomous vehicles have a "kill switch" or human override feature to ensure safety, and MHRA regulation decides on higher levels of classification for more independent systems.

As AI continues to shape our world, the responsible development and deployment of these technologies are vital to ensure that they benefit humanity and do not harm vulnerable populations or perpetuate biases.