Ai Ethics And Governance: Concepts And Applications

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Ai Ethics And Governance: Concepts And Applications
Published 1/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 536.93 MB | Duration: 2h 46m
Designing, Deploying, and Governing Ethical AI Systems | Responsible AI Deployments for the Real World​

What you'll learn
Need for ethics and governance in AI
What are the different frameworks for AI Ethics
How to implement AI Ethics framework in your organization
What are FEAT metricss
What is explainable AI
What are the different types of bias
How sampling drives many issues in ethics and governance areas
Requirements
Basic knowledge of AI will be advantageous
Few years of working in an organization would also be advantageous
Description
AI Ethics and Governance: Concepts and ApplicationsImagine a self driving car misreading a road sign, causing a collision or a loan application system that routinely rejects applicants from certain backgrounds due to biased training data. From facial recognition software leading to wrongful detentions, to AI based diagnoses that overlook critical symptoms, the stakes are high when AI goes wrong. These real world examples highlight why ethics must be integral to any AI initiative.In this course, you'll first explore predictive AI versus generative AI and see how each poses distinct risks and ethical considerations. We'll compare weak AI versus strong AI. You'll also delve into the major model families (regression, tree based methods, neural networks, and more) and learn how to evaluate their performance using accuracy metrics such as precision, recall, or mean squared error.From an ethics perspective, we'll show why fair and transparent AI design is vital. Through case studies and best practices, you'll discover how to mitigate bias, protect user privacy, and address accountability. We'll also unpack governance frameworks from Singapore, the World Economic Forum, the Organization for Economic Cooperation and Development, European Union and others complete with practical questionnaires that spotlight potential pitfalls in AI deployment. By the end, you'll have the knowledge and tools to ensure your AI projects uphold public trust and safeguard the well being of everyone they affect. Best of all, this course is led by an industry veteran who brings a wealth of corporate and technical experience especially around managing AI deployments in real world settings. Through his first hand insights, you'll gain practical guidance on navigating common pitfalls, championing ethical decision making, and ensuring that AI solutions deliver true, sustainable impact.
CxO's,AI Ethics and Governance Enthusiasts,Data Scientists,Machine Learning Engineers,IT Professionals,Students
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[0dayddl]

Ai Ethics And Governance: Concepts And Applications
Published 1/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 536.93 MB | Duration: 2h 46m​

Designing, Deploying, and Governing Ethical AI Systems | Responsible AI Deployments for the Real World

What you'll learn

Need for ethics and governance in AI

What are the different frameworks for AI Ethics

How to implement AI Ethics framework in your organization

What are FEAT metricss

What is explainable AI

What are the different types of bias

How sampling drives many issues in ethics and governance areas

Requirements

Basic knowledge of AI will be advantageous

Few years of working in an organization would also be advantageous

Description

AI Ethics and Governance: Concepts and ApplicationsImagine a self driving car misreading a road sign, causing a collision or a loan application system that routinely rejects applicants from certain backgrounds due to biased training data. From facial recognition software leading to wrongful detentions, to AI based diagnoses that overlook critical symptoms, the stakes are high when AI goes wrong. These real world examples highlight why ethics must be integral to any AI initiative.In this course, you'll first explore predictive AI versus generative AI and see how each poses distinct risks and ethical considerations. We'll compare weak AI versus strong AI. You'll also delve into the major model families (regression, tree based methods, neural networks, and more) and learn how to evaluate their performance using accuracy metrics such as precision, recall, or mean squared error.From an ethics perspective, we'll show why fair and transparent AI design is vital. Through case studies and best practices, you'll discover how to mitigate bias, protect user privacy, and address accountability. We'll also unpack governance frameworks from Singapore, the World Economic Forum, the Organization for Economic Cooperation and Development, European Union and others complete with practical questionnaires that spotlight potential pitfalls in AI deployment. By the end, you'll have the knowledge and tools to ensure your AI projects uphold public trust and safeguard the well being of everyone they affect. Best of all, this course is led by an industry veteran who brings a wealth of corporate and technical experience especially around managing AI deployments in real world settings. Through his first hand insights, you'll gain practical guidance on navigating common pitfalls, championing ethical decision making, and ensuring that AI solutions deliver true, sustainable impact.

Overview

Section 1: Introduction

Lecture 1 Introduction

Section 2: Understand AI

Lecture 2 Strong AI vs Weak AI

Lecture 3 Gen-AI and Predictive AI

Lecture 4 Types of Algorithms

Lecture 5 How algorithms work

Lecture 6 How neural networks operate

Lecture 7 Different types of algorithms

Lecture 8 Accuracy of algorithms

Lecture 9 AI Lifecycle

Section 3: Explainable AI (XAI)

Lecture 10 Introduction to XAI

Lecture 11 Types of AI Models from Explainability Perspective

Lecture 12 Types of Explainability Techniques

Section 4: AI Ethics and Governance: Setting the context

Lecture 13 Need for AI Ethics and Governance

Lecture 14 Building Blocks of AI Ethics

Lecture 15 Metrics for AI Ethics

Section 5: AI Ethics and Governance Framework: Singapore

Lecture 16 Introduction to Singapore Framework

Lecture 17 Questionaire

Lecture 18 Veritas Tooklit

Lecture 19 FEAT principles

Section 6: World Economic Forum (WEF) : AI Toolkit & Model Governance

Lecture 20 Introduction

Lecture 21 Implementing WEF Governance

Lecture 22 WEF Best Practices

Section 7: European Commission's Ethics Guidelines for Trustworthy AI

Lecture 23 Introduction to Trustworthy AI

Lecture 24 Questionnaire for Trustworthy AI

Section 8: IEEE's Ethically Aligned Design

Lecture 25 Introduction to IEEE's Ethically Aligned Design

Lecture 26 IEEE Key Chapters

Lecture 27 P7001

Lecture 28 P7002

Lecture 29 P7003

Section 9: Other AI Ethics and Governance Frameworks

Lecture 30 OECD

CxO's,AI Ethics and Governance Enthusiasts,Data Scientists,Machine Learning Engineers,IT Professionals,Students

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