1. Defining Responsible AI
Welcome! I'm Esther, and I will be your instructor for this course on understanding how to make sure artificial intelligence is used in a responsible way.
2. Responsible AI (RAI)
OK, let's start with the basics. What do we mean by 'Responsible AI'? Responsible AI (or RAI) refers to the practice of designing, developing, and deploying artificial intelligence with an awareness of its ethical implications and societal impacts. It's about ensuring that AI systems are fair, transparent, accountable, and respecting user privacy and human rights. Responsible AI is not just about the technology itself but also about the values and principles that guide its use.
3. AI domains
Now, you might wonder, why is the responsible use of AI so important? The answer lies in the transformative power of AI. With its ability to process and learn from vast amounts of data, AI is revolutionizing industries, from healthcare to finance, education to transportation. Take a close look at this overview of all the domains affected by AI.
4. Why vital?
However, with great power comes great responsibility. AI systems can inadvertently perpetuate biases, invade privacy, or be used unethically. For example, AI can have issues recognizing black and colored people, can have negative outcomes based on gender, and can exclude people based on their postal code or age.
It could invade privacy by putting different anonymized data together and then putting one and two together, lifting anonymity based on these so-called “proxies”. AI could also tell you how to build weapons of mass destruction. Thus, embracing Responsible AI is essential to mitigate these risks, ensuring that AI benefits society as a whole and does no harm.
5. AI Principles
So, what are these key principles that underpin Responsible AI?
They are largely based on the guidelines set forth by the Organisation for Economic Co-operation and Development, the OECD, and which are widely accepted globally.
The OECD is an intergovernmental organization with 38 member countries, founded in 1961, and offers a wealth of knowledge on policy and AI through their OECD.AI policy observatory.
These principles include:
Transparency and explainability: users should understand how and why AI systems make decisions.
Fairness and non-discrimination: AI should be free from biases and discrimination. Promote inclusiveness and equity and consider humanity's diversity. And it should promote human-centered values.
Robustness and safety: AI systems must be secure, robust, and operate safely under all conditions.
Privacy and data governance: AI should respect privacy rights and ensure the secure handling of data.
Accountability: There must be clear accountability for AI systems and their outcomes. In the end, we simply cannot blame the AI.
Inclusive growth and sustainable development: AI should help bridge the digital divide and be built in the most sustainable way with respect for people and planet.
Understanding these principles is one thing; applying them is another. Throughout this course, we'll delve into each of these principles in detail, exploring their nuances and how they can be effectively implemented in AI systems.
6. Responsible versus ethical
But before we conclude, let's clarify how Responsible AI differs from AI Ethics. While both fields significantly overlap, there are distinct aspects to each. AI Ethics is broader, encompassing philosophical questions and ethical dilemmas related to AI. It probes into the impact of AI on human behavior, societal norms, and moral considerations.
On the other hand, Responsible AI focuses more on implementing these ethical considerations. Putting theory into action. What sets Responsible AI apart is its reliance on clear metrics and established frameworks to guide the ethical development and use of AI systems.
7. Summary
These metrics and frameworks aren't theoretical; they are tools organizations, developers, and deployers can use to measure and ensure their AI systems align with ethical standards. And that is precisely what you will be learning about in this course.
As we wrap up this video, remember that Responsible AI is not just a technical requirement; it's a commitment to ensuring that AI advances human values and societal well-being. It's about creating AI that works for everyone, respecting our diversity and humanity. Next in this course, we'll continue to unravel the layers of Responsible AI, equipping you with the knowledge and tools to not just understand, but also actively contribute to this field.
8. Let's practice!
Thank you for your attention. I look forward to continuing this journey with you in the upcoming videos. Before we move on, let's try some exercises to reinforce these ideas and get a clear feel of what is responsible and what is not.