Intro to Data & AI Ethics

Data and AI Ethics are topics that most data leaders and professionals don’t learn in school, or on the job.But as the volume of data grows and the impact of ML & AI algorithms continues to increase, understanding the ethical implications of our work – and how to prevent & mitigate ethical lapses – is more important than ever.We’ll start this course by defining AI and Data ethics before moving on to what it means to be an ethical steward of data.From there, we’ll dive into the types of bias that can be present in your data and how it can propagate into analyses and algorithms in a way that can not only raise ethical questions, but also negatively impact your company’s bottom line.Next, we’ll dive into the world of modern AI models, and the unique risks and ethical concerns posed by powerful generative AI tools. We’ll use case studies to highlight real-life controversies, discuss how to mitigate the risk of ethical lapses, and use thought exercises to help you develop the skills to anticipate, identify, and mitigate the risk of ethical lapses in your day-to-day work.COURSE OUTLINE:Data Ethics 101Introduce the fundamental concepts of ethics, and discuss how data ethics differs from legal frameworks regulating dataEthical Data StewardshipUnderstand how to be an effective steward of data, and review the ethical implications of collecting and managing sensitive dataData & Algorithmic BiasLearn how to detect and mitigate common forms of bias, including sampling, selection, algorithmic and confirmation biasAI Ethics & ImpactDive into the world of AI and explore