Certified Ethical Emerging Technologist (CEET)
Mutually reinforcing innovations in computing and engineering are catapulting advances in technological production. From blockchain and artificial intelligence (AI) to gene editing and the Internet of Things (IoT), these advances come with tremendous opportunities for improvement in productivity, efficiency, and human well-being. But as scandals increasingly demonstrate, these advances also introduce new and serious risks of conflict and harm.
Training at a glance
Level
Beginner
Duration
3 Days
Experience
3 years; Data Science
Average Salary
$122,000
Labs
No
Level
Beginner
Duration
3 Days
Experience
3 years: Data Science
Average Salary
$122,000
Labs
No
Training Details
Technology professionals now face growing demands to identify and mitigate ethical risks to human rights and the environment, as well as to navigate ethical tradeoffs between qualities such as privacy and accuracy, fairness and utility, and safety and accountability. This course provides the tools to identify and manage common ethical risks in the development of emerging data-driven technologies. It distills ethical theory, public regulations, and industry best practices into concrete skills and guidelines needed for the responsible development of digital products and services. By following the course's
practical, problems-based approach, learners will become adept at applying theories, principles, frameworks, and techniques in their own roles and organizations.
In this course, you will incorporate ethics into data-driven technologies such as AI, IoT, and data science.
You will:
- Describe general concepts, theories, and challenges related to ethics and emerging technologies
- Identify ethical risks
- Practice ethical reasoning
- Identify and mitigate safety and security risks
- Identify and mitigate privacy risks
- Identify and mitigate fairness and bias risks
- Identify and mitigate transparency and explainability risks
- Identify and mitigate accountability risks
- Build an ethical organization
- Develop ethical systems in technology-focused organizations
- Topic A: What’s at Stake
- Topic B: Ethics and Why It Matters
- Topic C: Ethical Decision-Making in Practice
- Topic D: Causes of Ethical Failures
Lesson 2: Identifying Ethical Risks
- Topic A: Ethical Reason
- Topic B: Stumbling Blocks for Ethical Reasoning
- Topic C: Identify Ethical Risks in Product Development
- Topic D: Tools for Identifying Ethical Risks
- Topic E: Use Regulations, Standards, and Human Rights to Identify Ethical Risks
Lesson 3: Ethical Reasoning in Practice
- Topic A: Ethical Theories
- Topic B: Use Ethical Decision-Making Frameworks
- Topic C: Select Options for Action
- Topic D: Avoid Problems in Ethical Decision-Making
Lesson 4: Identifying and Mitigating Security Risks
- Topic A: What Is Security?
- Topic B: Identify Security Risks
- Topic C: Security Tradeoffs
- Topic D: Mitigate Security Risks
Lesson 5: Identifying and Mitigating Privacy Risks
- Topic A: What Is Privacy?
- Topic B: Identify Privacy Risks
- Topic C: Privacy Tradeoffs
- Topic D: Mitigate Privacy Risks
Lesson 6: Identifying and Mitigating Fairness and Bias Risks
- Topic A: What Are Fairness and Bias?
- Topic B: Identify Bias Risks
- Topic C: Fairness Tradeoffs
- Topic D: Mitigate Bias Risks
Lesson 7: Identifying and Mitigating Transparency and Explainability Risks
- Topic A: What Are Transparency and Explainability?
- Topic B: Identify Transparency and Explainability Risks
- Topic C: Transparency and Explainability Tradeoffs
- Topic D: Mitigate Transparency and Explainability Risks
Lesson 8: Identifying and Mitigating Accountability Risks
- Topic A: What Is Accountability?
- Topic B: Identify Accountability Risks
- Topic C: Accountability Tradeoffs
- Topic D: Mitigate Accountability Risks
Lesson 9: Building an Ethical Organization
- Topic A: What Are Ethical Organizations?
- Topic B: Organizational Purpose
- Topic C: Ethics Awareness
- Topic D: Develop Professional Ethics within Organizations
Lesson 10: Developing Ethical Systems in Technology-Focused Organizations
- Topic A: Policy and Compliance
- Topic B: Metrics and Monitoring
- Topic C: Communication and Stakeholder Engagement
- Topic D: Ethical Leadership
This course is designed for technology leaders, solution developers, project managers, organizational decision makers, and other individuals seeking to demonstrate a vendor-neutral, cross-industry understanding of ethics in emerging data-driven technologies, such as AI, robotics, IoT, and data science.
This course is also designed for professionals who want to pursue the CertNexus Certification Exam CET-110: Certified Ethical Emerging Technologies.
To ensure your success in this course, you should have at least a high-level understanding of fundamental AI concepts, including, but not limited to: machine learning, supervised learning, unsupervised learning, artificial neural networks, computer vision, and natural language processing. You can obtain this level of knowledge by taking the CertNexus AIBIZ™ (Exam AIZ-110) course.
You should also have experience working with databases and a high-level programming language such as Python, Java, or C/C++. You can obtain this level of skills and knowledge by taking the following:
Logical Operations or comparable course
- Database Design: A Modern Approach
- Python® Programming: Introduction
- Python® Programming: Advanced
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