- All
- Accessibility/Inclusion
- Artificial Intelligence (AI/ML)
- Cybersecurity
- Medicine/Health
- Neuroscience
- Other Topics
- Power & Energy
- Robotics
- Sustainability/Environment
- Teaching Ethics
- Transportation

AI Standards: Best Practices for Ethical Systems
Factors that relate to transparency in systems, the difference in outcomes that those factors can create, as well as practical techniques that can be applied to encourage a greater quality of transparency in consistent and rigorous ethical systems are explored in this course. Topics include factors that tend to drive or inhibit the quality of transparency in systems, small differences that may lead to major differences over time, and practical steps towards implementing more consistent and rigorous ethical systems.

AI Standards: Configuring Systems for Privacy
The goals of this course are to familiarize the software engineer with key elements and concepts that can enhance privacy capabilities and safeguards in the software engineering and development process. Practical techniques are used to help the learner understand how to harness the assessment process to enhance privacy requirements and privacy-related controls. By the end of this course, you will understand how privacy assessments integrate into software engineering and software development models with an emphasis on fundamentals.

AI Standards: Organizational Transparency
In this course, a variety of elements are reviewed that can support or detract from achieving a goal of transparency at an organizational level. Ethical systems cannot be created in isolation of the organizational structures of the people creating them. Therefore, the elements that relate to organizational transparency are at least as important as those within technical systems.

AI Standards: Roadmap for Ethical and Responsible Digital Environments
The purpose of this 4-course series is to provide instructions for a comprehensive approach to creating ethical and responsible digital ecosystems. Because ethical transparency is critical to an organization’s success, it must be included in digital environments.

AI Standards: System Design Considerations for Data Privacy
This course focuses on design considerations and how the use of data and the data lifecycle play a fundamental role in privacy design. The goals of the course include exploring how software engineers ensure that privacy engineering requirements are satisfied within the contexts of use, end-user, third-parties, and potential re-purposing of the application or service developed. The course provides practical tips and guides as techniques the software engineer or developer can use to become versant in privacy design.

Artificial Intelligence and Ethics in Design: Responsible Innovation
European regulations require that ethics specifications be met when designing artificial intelligence (AI) systems. Ignoring these regulations can result in hefty financial fines. In this 5-course program, learn what engineers need to know when designing artificial intelligence systems.

Blockchain Governance and Human Rights
This module provides ways to think about how the architecture of blockchain technologies shapes governance processes and the forging and maintenance of a legal system. Similar to the Internet, blockchain technologies challenge our ideas about the relation between technology, governance, and the rule of law. Blockchain-based systems could potentially impact human rights provisions such as the right to nationality and to privacy.