Walk through the steps involved in designing responsible AI and to making responsible decisions. Along the way, check your learning with included challenge and solution sets.
- [Narrator] I've always been amazed with how quickly technology's increasing. Recently, more and more people have been asking about what is good or responsible AI, but it's hard to find an actual definition, and while we have a gut feeling about what responsible means, it's hard to put it into practice, and even harder to actually find a solid technical explanation of what that means. With new research and new developments coming out all the time, this course is an overview into responsible AI. First, we'll talk about some definitions, what responsible and AI actually mean, and how they fit together. Next, we'll have a look at what is not responsible AI and the effects it can have. Then we'll talk about the model and decision design process in an organization, and how it can change with a responsible lens. Finally, we'll talk about the global and local policies that are influencing how automated decisions are created. Through this course, we will be using case studies and examples to explain how these processes work, and we'll work through some thought exercises to further your understanding. My name is Martin Kemka, and I've worked as an analyst for over 15 years, working on developing automated decision systems for different organizations around the world. I've had a firsthand look at moving models from research to production, and what kind of thinking is required to bring responsible decisions to life. Join me for this LinkedIn Learning course as we dive into the dynamic and ever-changing world of responsible decision systems.