Understand the foundations of AI Ethics and observe some of the challenges of the ethical use of AI.

AI ethics: What's the buzz?

Guiding principle

What's covered by AI ethics?

Digging deeper: AI ethics principles

Identifying actions

AI principles unfolded

AI ethics: where's the line?

Striking a balance

CineLlama Navigator

Approaching AI Ethics

Unpack the core principles of AI Ethics and discover a promising technique, explainable AI (XAI), that can integrate these principles into many AI systems.

Unpacking the blackbox: Transparency

Transparent AI system

Options

Best practices

Inefficient practices

Transparency best practices

AI fairness: not just a dream

Tackling fairness issue

Techniques promoting fairness

Techniques not promoting fairness

Can we make things right?

Safeguarding AI: Accountability

Accountability common misconceptions

AI Production Team

AI Use Team

Who's responsible?

Explainable AI

How would you apply XAI?

SHAP

LIME

Decision Trees

The perfect match

Below the Surface: AI Ethics

Discover the value ethical frameworks present to organizations of all sizes and prepare yourself to tackle tomorow's ethical challenges with AI ethics by design.

Summaries Ethical frameworks

Framing success

When a plan comes together

The value of ethical AI

A proactive approach

Identify the stakeholders

The future of AI ethics

All part of the plan

Honing ethics by design

The Way Forward: AI Ethics

Course Glossary

This introductory course on AI ethics provides a comprehensive overview of ethical considerations in the fast-paced domain of artificial intelligence. The course spans industry, policy-making, academia, and society at large, covering principles of AI ethics, strategies to foster fair and equitable AI systems, approaches to minimize biases, and methods to address key issues and establish user trust. Throughout the course, you will learn about the core principles of ethical AI and expand your understanding of common challenges and opportunities in the field of AI ethics. Through hands-on exercises, you will build your skills to craft ethical AI by design. Begin Learning today!

The videos contain live transcripts you can reveal by clicking "Show transcript" at the bottom left of the videos.

The course glossary, promotional material and detailed learning objectives can be found on the right in the resources section.

To obtain CPE credits you need to complete the course and reach a score of 70% on the qualified assessment. You can navigate to the assessment by clicking on the CPE credits callout on the right.

<h2>Get an Overview of AI Ethics</h2> 
This introductory course on AI ethics provides a comprehensive overview of ethical considerations in the fast-paced domain of artificial intelligence. The course spans industry, policy-making, academia, and society at large, covering principles of AI ethics, strategies to foster fair and equitable AI systems, approaches to minimize biases, and methods to address key issues and establish user trust.
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<h2>Ethical Principles and Challenges</h2> 
Throughout the course, you will learn about the core principles of ethical AI and expand your understanding of common challenges and opportunities in the field of AI ethics. Through hands-on exercises, you will build your skills to craft ethical AI by design. Begin Learning today!

Explore AI ethics focusing on principles, fairness, bias reduction, and trust in AI design.

AI Ethics

AI İşletme Temelleri

AI Temelleri

Yapay Zeka Uygulamaları Geliştirme

AB Yapay Zeka Yasası Temelleri

Sorumlu Yapay Zeka Temelleri

Bloom AI decides to clearly document the data they use for training their AI models.

They engage an independent audit to verify their AI processes and models.

They commit to routinely sharing updates about changes to their AI systems to all their stakeholders.

Bloom AI opts to use opaque algorithms to boost the performance of their AI models.

Bloom AI decides to only disclose how their AI systems work to a select group of privileged clients.

Transparency best practices

AI Ethics

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