Ethical Ai Decision Making, Insights For Leaders & Others !

[LeeAndro]

Published 4/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.97 GB | Duration: 2h 0m​

Insights into Ethical Decision Making, creating or using AI (Artificial Intelligence), for Leaders and everyone else !

What you'll learn
The Basics of AI (non technical), how it works, the 3 Components of AI, and the 5 Foundational Ethical Principles of AI
Relevant Concepts from Psychology and Philosophy, for Ethical Decision Making with AI
Several Real World AI Case Studies, which highlight the many ways AI can go wrong
Learnings from all of the above, for Ethical Decision Making, with AI, both when Developing and Using AI
Some tips and tricks to use GenAI Tools more effectively

Requirements
None at all, except a curiosity to learn and understand !

Description
Artificial Intelligence, or AI, and Generative AI, are all the rage these days. Everyone's talking about revolutionary tools like ChatGPT, GPT-4, Perplexity, Gemini, CoPilot, etc.The technology behind AI is complex and amazing. But whats probably even more complex, and nuanced, is creating and using AI for Ethical Decisions, and using the right data to train the AI correctly. And thats what you will learn from this Course. I am well aware of the technical basics of AI, having spent nearly 2 decades Leading and Managing Multiple Global Projects in the Software Industry.But my expertise, and passion, lie in the area of Decision Making, Ethics, and Leadership Psychology.So, this Course isn't about the technical nitty-gritty of AI. Although I will be explaining the basics of AI, how it works etc. in simple terms. My focus will be in my areas of expertise, Decision Making and Ethics.I will be looking at AI, from an Ethical Decision Making point of view. To help Leaders drive the creation, and use, of AI responsibly ! This Course is primarily for Leaders, but everyone can enjoy it, and learn something new from it !There will be several examples and Case Studies, as well as a few Practice Exercises and Quizzes, to help you learn better from the Course.I have used ChatGPT4 (GPT4, the paid version) in a very limited way, for this Course, specifically to identify the right Case Studies and Research findings in my Course content.

Overview
Section 1: INTRODUCTIONS

Lecture 1 Course Introduction and Structure

Lecture 2 Course Navigation Tips

Lecture 3 An Introductory Case Study

Section 2: AI : SOME BASIC CONCEPTS

Lecture 4 What is AI

Lecture 5 The 3 Components of AI

Lecture 6 The 5 Foundational Ethical Principles of AI

Section 3: SOME RELEVANT PSYCHOLOGY AND PHILOSOPHY CONCEPTS

Lecture 7 Why do we need this, and Introduction to The Trolley Problem

Lecture 8 The Trolley Problem, continued ...

Lecture 9 Human Moral Foundations

Lecture 10 Our Systems of Thinking, Part 1

Lecture 11 Our Systems of Thinking, Part 2

Lecture 12 UX and HCI Concepts

Section 4: WHEN AI GOES WRONG : REAL WORLD AI CASE STUDIES, INSIGHTS, and LEARNINGS

Lecture 13 Section Introduction, and Case Study 1

Lecture 14 Case Study 2

Lecture 15 Let's look at the Real World Data, Part 1

Lecture 16 Let's look at the Real World Data, Part 2

Lecture 17 How do we fix these Data Problems Part 1

Lecture 18 How do we fix these Data Problems Part 2

Lecture 19 How do we fix these Data Problems Part 3

Lecture 20 How do we fix these Data Problems Part 4

Lecture 21 Case Study 3

Lecture 22 Case Study 4

Section 5: CONCLUSION, LESSONS, AND APPLICATIONS

Lecture 23 Summary and Lessons, Part 1

Lecture 24 Summary and Lessons, Part 2

Section 6: GEN-AI EXTRA SECTION

Lecture 25 Some Do's and Donts, for Content Generation using GenAI

Lecture 26 Some Simple Suggestions for Better Content Generation using GenAI Tools

Lecture 27 How to download your UDEMY CERTIFICATE

Leaders, involved in Driving Initiatives for the Creation, Implementation, and Use of AI Systems,Anyone involved in Initiatives for the Creation, Implementation, and Use of AI Systems or Programs/Tools,Anyone interested in gaining insights into the many ways AI can go wrong, and how we can avoid those pitfalls



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