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Detect and Mitigate Ethical Risks

Approx. 20 hours to complete

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Course Summary

This course teaches how to detect and mitigate ethical risks in various situations, including business, technology, and personal life. It covers topics such as moral decision-making, ethical leadership, and social responsibility.

Key Learning Points

Learn to identify and address ethical dilemmas in different contexts
Develop skills in ethical reasoning and decision-making
Explore case studies and real-life examples of ethical issues and solutions

Job Positions & Salaries of people who have taken this course might have

Ethics Officer
- USA: $70,000 - $150,000
Corporate Social Responsibility Manager
- USA: $60,000 - $130,000
Technology Ethics Consultant
- USA: $80,000 - $200,000

Learning Outcomes

Understand ethical principles and frameworks
Develop critical thinking and ethical reasoning skills
Apply ethical concepts and strategies to real-life situations

Prerequisites or good to have knowledge before taking this course

Basic knowledge of ethics and philosophy
Interest in social and moral issues

Course Difficulty Level

Intermediate

Course Format

Online self-paced course
Video lectures and case studies
Interactive quizzes and assignments

Similar Courses

Ethical Leadership
Corporate Social Responsibility
Technology Ethics

Related Education Paths

Related Books

Description

Data-driven technologies like AI, when designed with ethics in mind, benefit both the business and society at large. But it’s not enough to say you will “be ethical” and expect it to happen. We need tools and techniques to help us assess gaps in our ethical behaviors and to identify and stop threats to our ethical goals. We also need to know where and how to improve our ethical processes across development lifecycles. What we need is a way to manage ethical risk. This third course in the Certified Ethical Emerging Technologist (CEET) professional certificate is designed for learners seeking to detect and mitigate ethical risks in the design, development, and deployment of data-driven technologies. Students will learn the fundamentals of ethical risk analysis, sources of risk, and how to manage different types of risk. Throughout the course, learners will learn strategies for identifying and mitigating risks.

Knowledge

Summarize common sources of ethical risks.
Detect and mitigate ethical risks.
Evaluate risk identification and mitigation strategies within the lifecycle.
Analyze a sample AI model and create a plan to mitigate any identified risks.

Outline

Ethical Risk Analysis Fundamentals
Detect and Mitigate Ethical Risks Course Introduction
CEET Specialization Introduction
Course Welcome & Success Tips
The Importance of Managing Risks
Risk Management Process
Risk Identification
Risk Analysis
Risk Mitigation
Types of Ethical Risk
Distributions
Central Tendency
Variance and Standard Deviation
Skewness and Kurtosis
Correlation
Probability
Machine Learning Outcomes
Cost Functions
Reliability
Goodhart's Law
Overview
Risk Management Frameworks
Classification Metrics
Analyzing Ethical Risks

Manage Privacy Risks
The Importance of Managing Privacy Risks
Private Data
First-Party vs. Third-Party Data
Secondary Use of Data
Combined Data Sources
Identify Personally Identifiable Information (PII)
Model Personas
Track Customer Data
Meet Compliance Requirements
Intent and Consent
Minimize Private Data Sharing
Give the User Choices
Minimize Private Data Collection
Reinforce Trust
Anonymization and Pseudonymization
Homomorphic Encryption
Zero-Knowledge Protocols
Parity Introduction
Incorporate Privacy Risk Management in the Lifecycle
Overview
Data Protection Policies
Privacy Legislation Sources
Managing Privacy Risks

Manage Accountability Risks
The Importance of Managing Accountability Risks
Use of Third-Party Components
Automation Bias
Extrajudicial Judgment
Lack of Guiding Principles
Recognize Black Box Algorithms
Assess the Organization's Governance Structure
Document and Distribute Company Policies
Document Design Processes
Document Auditing Processes
Responsibility Assignment Matrix (RAM/RACI)
Pilot Testing
Collaboration with Data Sharing Partners
Algorithmic Impact Assessment (AIA)
Data Visualization
Dashboard Reporting
Incorporate Accountability Risk Management in the Lifecycle
Overview
Managing Accountability Risks Quiz

Manage Transparency and Explainability Risks
The Importance of Managing Transparency and Explainability Risks
Black Box Systems
Self-Learning Models
Third-Party Integration
Intellectual Property Rights
Shadow Banning
Explainable AI
Identify Algorithmic Decisions
Deconstruct Specific Decisions
Explain How Systems Work
Help Users Seeking Explanations
Keep Humans in the Loop
Ensure Proper Data Disclosure
Be Upfront About Training Data Inadequacies
SHAP and Alibi
ELI5, LIME, and What-If
Overview
Incorporate Transparency and Explainability Risk Management in the Lifecycle
Managing Transparency and Explainability Risks Quiz

Manage Fairness and Non-Discrimination Risks
The Importance of Managing Fairness and Non-Discrimination Risks
Implicit Bias
Sampling Bias
Reinforcement Bias
Temporal Bias
Overfitting to Training Data
Edge Cases and Outliers
Analytical Techniques
Analyze Models in Different Environments
Persona Modeling
Inclusive Design and Foreseeability
STEEPV Analysis
Perform User Testing
Gather Input from External Stakeholders
Bias and Safety Bounties
AI Fairness 360
Radioactive Data Tracing
Incorporate Fairness and Non-Discrimination Risk Management in the Lifecycle
Overview
Pattern Matching vs. Bias
AI Fairness 360 Demo
Managing Fairness and Non-Discrimination Risks

Manage Safety and Security Risks
The Importance of Managing Safety and Security Risks
Abnormal System Behavior
Adversarial Machine Learning
Bad Actors
Groupthink and Biases
Cyber Attacks
Quantitative Risk Analysis
Evaluate Training Data and Models
Threat Intelligence
Threat Modeling
Penetration Testing
Forensic Analysis
Ensure Critical AI Systems Follow Rigorous Standards
Establish Baseline System Behavior
Designate Rapid Response Teams
Protect the Security of Data in Storage
Protect the Security of Data in Transit
Threat and Risk Libraries
Threat Modeling and Analysis Tools
Attack Simulation Tools
Vulnerability Scoring Tools
Security Information and Event Management (SIEM)
Incorporate Safety and Security Risk Management in the Lifecycle
Overview
Managing Safety and Security Risks Quiz

Apply What You've Learned

Summary of User Reviews

Learn how to detect and mitigate ethical risks with this course on Coursera. Students have given this course positive reviews, praising its informative content and engaging instructors. However, some users have also mentioned concerns about the course's difficulty and lack of practical application.

Key Aspect Users Liked About This Course

informative content

Pros from User Reviews

Engaging and knowledgeable instructors
In-depth coverage of ethical risks
Great for beginners in the field

Cons from User Reviews

Challenging assignments
Lack of practical application
Some technical issues with the platform

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