The ethics of artificial intelligence is the technology-specific component of the ethics of technology. It is sometimes separated into human ethics and machine ethics. Human ethics is concerned with the moral behaviour of humans when they design, create, use, and treat artificially intelligent systems. It also covers the possibility of a singularity brought on by superintelligent AI.

Given the widespread adoption of AI, we must learn about and discuss the ethical concerns and hazards associated with this technology. To that goal, some of the world's finest educational establishments have launched AI ethics programmes. In this section, we present the top picks:

Ethics of Artificial Intelligence - Coursera

This course examines the challenges that AI has produced, exacerbated, or transformed. It provides an opportunity to reflect on AI's ethical, social, and cultural effects by concentrating on concerns encountered by AI practitioners and citizens, institutions, and societies. The course examines these subjects by analysing case studies and examples within the context of the most critical ethical frameworks.

Artificial Intelligence Ethics Certification - Udemy

The AI, Ethics Certification course teaches excellent and evil in the context of the artificial intelligence industry, assuming such a thing exists. This three-part programme begins with the question, "What is ethics?" We will cover its history, various philosophies, corporate ethics, and the five most general principles. Second, ethics as it relates directly to AI, including interviews with founders from around the world. They will compare often mentioned governance and leadership concepts to the five traditional pillars. Then, they develop a structure for your ethics roadmap. The objective is to increase trust between you, your product or service, industry professionals, and the general public.

Ethics in AI and Data Science - edx

To get the best outcomes while also being responsible corporate citizens and data professionals, business leaders and data professionals today need AI frameworks and methodologies. While businesses and institutions embrace AI principles and the vocabulary of ethics, trust, and accountability has entered emerging technologies, AI, and data science, there still needs to be more clarity over when and why it is required. In addition to providing practical solutions to the ethical, business, and leadership problems and challenges that arise when working in AI and Data Science, this course introduces some of the principles and frameworks that put ethics and responsibility into practice in the data analytics profession.

Data Ethics, AI and Responsible Innovation (MOOC) - The University of Edinburgh

The course examines the social, political, legal, and ethical challenges with data-driven innovation, AI, and ML systems. It is funded by The Data Lab and the Data-Driven Innovation programme. Case studies on fairness, bias, data reuse, and data privacy and protection, among other topics, will be covered in the course.

The course examines how data-driven applications and AI have social repercussions. The instruments necessary to reduce injustice, advance justice, and protect and enhance human autonomy and well-being are also covered.

Ethics of AI - LSE

The three-week online masterclass on AI ethics examines AI technologies' ethical opportunities and problems. Throughout this course, you will apply moral ideas to actual situations to better understand and resolve ethical issues, such as inequality, fairness, and transparency. Learn how we can use AI technologies in various business settings, such as hiring and employee supervision, and what this might mean for problems in your organisation, like discrimination and power imbalances.

Ethics of AI - University of Helsinki

This online course from the University of Helsinki is for anyone interested in the ethical aspects of artificial intelligence and who wants to learn what can and cannot be done to develop AI in an ethically sustainable manner. Practical exercises will teach students how to combine ethical concepts and theories with AI.