Trust and Ethics in AI: A Business Approach

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Trust and Ethics in AI: A Business Approach

Instructor: Wiley-Expert Edge Course Instructors

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12 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

8 hours to complete

Flexible schedule

Learn at your own pace

12 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

8 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Understand the key principles of trustworthy AI in business
Implement strategies for building fair and impartial AI systems
Explore best practices for ensuring transparency and explainability in AI

Skills you'll gain

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There are 12 modules in this course

Based on the best-selling book, Trustworthy AI, by Beena Ammanath. This course equips professionals with the knowledge and tools to build and implement ethical AI systems. It explores the core principles of trustworthy AI, including fairness, transparency, and reliability, and provides practical strategies for integrating these values into business operations. Designed for those navigating the intersection of technology and ethics, it offers actionable insights for responsible AI development.

The course covers essential concepts such as fairness, transparency, and the importance of building reliable AI systems that align with ethical guidelines. You'll also discover real-world applications and strategies for integrating these principles into your organization’s AI practices. By the end, you will have gained knowledge on the responsible use of AI and tools for ensuring AI systems are built with trust in mind. What sets this course apart is its focus on applying ethical principles directly to business practices. You’ll gain both theoretical understanding and practical insights to help implement ethical AI practices in real-world scenarios. With real-life case studies and expert-led discussions, this course will equip you to tackle the evolving challenges in AI ethics. This course is designed for business leaders, AI professionals, and technology managers who wish to ensure the ethical development of AI within their organizations. A basic understanding of AI and business processes will help, but deep technical expertise is not required. Copyright © 2022 by John Wiley & Sons, Inc. All rights reserved. Published by John Wiley & Sons, Inc., Hoboken, New Jersey.

In this section, we explore AI as mathematical models, not thinking entities, and examine their roles in data science and real-world applications.

What's included

2 videos2 readings1 assignment

In this section, we examine sources of bias in AI systems, evaluate fairness in deployment, and implement ethical practices to ensure equitable and compliant AI applications.

What's included

1 video5 readings1 assignment

In this section, we explore strategies for ensuring AI robustness and reliability in dynamic environments. Key concepts include testing frameworks, data drift analysis, and continuous learning systems.

What's included

1 video4 readings1 assignment

1 video Total 1 minute

Robust and Reliable - Overview Video 1 minute

4 readings Total 40 minutes

Introduction 10 minutes
The Challenge of Generalizable Deep Learning 10 minutes
Meeting the Long Tail in Reliability Engineering 10 minutes
Put Your AI to the Test on Robustness and Reliability 10 minutes

1 assignment Total 10 minutes

AI System Reliability and Robustness 10 minutes

In this section, we examine transparency in AI, focusing on accountability and stakeholder trust.

What's included

1 video3 readings1 assignment

In this section, we explore AI explainability, focusing on frameworks, black box analysis, and transparent reporting to build trust and ensure compliance in business applications.

What's included

1 video4 readings1 assignment

In this section, we explore AI security vulnerabilities, risks of system compromise, and secure deployment practices to ensure safe and trustworthy AI implementation.

What's included

1 video3 readings1 assignment

In this section, we explore integrating safety into AI design, analyzing human values, and optimizing objectives to ensure ethical outcomes and prevent harm.

What's included

1 video4 readings1 assignment

In this section, we examine privacy in AI, focusing on data collection methods, regulatory compliance, and informed consent to ensure ethical and trustworthy AI systems.

What's included

1 video4 readings1 assignment

1 video Total 1 minute

Privacy - Overview Video 1 minute

4 readings Total 40 minutes

Introduction 10 minutes
The Friction Between AI Power and Privacy 10 minutes
Beyond Anonymization or Pseudonymization 10 minutes
California Consumer Privacy Act (CCPA) and California Privacy Rights Act (CPRA) 10 minutes

1 assignment Total 10 minutes

Privacy in the Digital Age 10 minutes

In this section, we explore AI accountability challenges, emphasizing ethical responsibility, transparent decision-making, and frameworks to ensure trust and compliance in AI-driven procurement systems.

What's included

1 video3 readings1 assignment

In this section, we examine evaluating AI systems for ethical alignment, implementing responsible deployment frameworks, and assessing impacts on stakeholder trust.

What's included

1 video3 readings1 assignment

In this section, we explore implementing trust dimensions in AI strategies, analyzing trust factors across use cases, and designing consistent governance frameworks for responsible AI deployment.

What's included

1 video2 readings1 assignment

In this section, we explore building trustworthy AI through structured governance, emphasizing fair, reliable, and transparent systems aligned with human values and future regulations.

What's included

1 video1 reading1 assignment

Instructor

Wiley-Expert Edge Course Instructors

John Wiley & Sons

33 Courses 1,222 learners

Offered by

John Wiley & Sons

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