Course Description
These lessons on Modern Artificial Intelligence Development will cover the history and background of artificial intelligence and the fundamental aspects and concepts of artificial intelligence, including how AI works as a decision system. We’ll also explore how AI is used in everyday life, machine learning as an automated system that learns from information, and the unique considerations about big data used in AI systems.
Humankind has been fascinated with the creation of artificial intelligence since ancient times, and modern artificial intelligence has become an area of intense interest in terms of research and development. With the growth in technology and advances made in computer science, computers have evolved from simple calculators to sophisticated machines. We'll consider AI systems from four paradigms: cognitive modeling, laws of thought, Turing's test, and rational agents. We'll see how the differences between them impact how we build and analyze the AI system, and ultimately, how that impacts ethics and accountability.
With increasing interactions with AI systems, there are more and more issues around ethics and accountability. You will learn about the ethical and legal issues that surround AI, and the role of AI in society.
What You'll Learn
- Describe the history and background of artificial intelligence
- Differentiate between the four paradigms of AI: cognitive modeling, laws of thought, Turing's test, and rational agents
- Recognize the role of AI in critical systems and the implications of AI for critical systems
- Explain how AI works as a decision system and how machine learning learns from information
- Examine the unique considerations of big data used in AI systems
- Identify the ethical and legal issues surrounding AI and the role of AI in society
Key Takeaways
- AI can be understood through four paradigms - cognitive modeling, laws of thought, Turing's test, and rational agents - and the differences between them affect how AI systems are built and analyzed.
- The choice of AI paradigm ultimately impacts questions of ethics and accountability.
- Machine learning is an automated system that learns from information, and big data raises unique considerations when used in AI systems.
- Increasing interactions with AI systems raise growing issues around ethics and accountability.
- The course addresses the ethical and legal issues surrounding AI and the role of AI in society.
Frequently Asked Questions
What topics does this course cover?
It covers the history and background of artificial intelligence, fundamental concepts of AI including how AI works as a decision system, machine learning, big data, AI in everyday life, AI in critical systems, and the risks, ethical, and legal issues surrounding AI.
What are the four paradigms of AI discussed in this course?
The course considers AI systems from four paradigms: cognitive modeling, laws of thought, Turing's test, and rational agents, and examines how their differences impact how AI systems are built, analyzed, and held accountable.
What skills will I gain from this course?
The course covers skills including AI/ML inference, applications of artificial intelligence, artificial intelligence systems, artificial intelligence development, and computational intelligence.
Does this course address the ethics of AI?
Yes. It explores the ethical and legal issues that surround AI, the role of AI in society, and how the differences between AI paradigms impact ethics and accountability.
What lessons are included?
The lessons are: What is Artificial Intelligence?; Decision systems as AI; Machine Learning; Big Data; AI in everyday life; AI in critical systems; and Risks and Consequences of Artificial Intelligence.
