This eCourse consists of two modules. Module 1 provides a high-level overview of ethics, and in particular, AI ethics. Developments in data analysis and machine learning have led to a dramatic increase in the use of artificial intelligence by both private and public institutions. AI is involved in many industries and activities – banking and finance, industrial manufacturing, agriculture, marketing, social media, urban planning, healthcare, policing, and more. One of the most important challenges the AI community faces is to develop algorithms that can contribute to individual and social wellbeing.

Module 2 describes in detail the most important principles for AI ethics. AI ethics is a very new field, so there is no common framework similar to that for other areas of practical ethics. However, a number of AI ethics “codes” have been developed, along with some attempts to find commonalities among them.

On completion of this course, you will be able to:
- Identify how ethics differs to laws and why we need ethics
- Recognise the approaches to practicing ethical behaviour
- Recognise the differences between narrow and general AI, the different approaches to symbolic and neural networks, and the prevalence of AI
- Recognise the need for AI ethics to have a different framework to that of other areas of practical ethics
- Identify the classic principles of practical ethics and their application to AI ethics
- Recognise the key ethical principles that are specific to AI ethics

Module 1 - AI Ethics - An Introduction
Topic 1: Ethics Basics
Topic 2: Ethics in Practice
Topic 3: AI Ethics

Module 2 - AI Ethics - Key Principles
Topic 1: Practical Ethics
Topic 2: Classic Principles of Practical Ethics
Topic 3: Ethical Principles Specific to AI Ethics