ENROLL TODAY AND START BUILDING YOUR ETHICAL INTELLIGENCE
ETHICS IS NOT AN OPTION IF YOU WANT TO BE SUCCESSFUL IN TECH.
It is not only required, but demanded by employers, consumers, and employees alike. The question now is how do you properly address the ethical aspects of AI and Big Data, while avoiding the issue of ethics washing, in order to meet this new demand? Simple, you start by educating yourself on the issues at hand, so that you can learn how to utilize ethics not as a tech blocker, but as a tool for long-term innovation.
THIS COURSE IS FOR:
COMPUTER PROGRAMMERS & DATA SCIENTISTS
STAND OUT FROM THE CROWD.
Whether you want to take your CV to the next level, or show initiative with your current employer, this is an investment in your skillset. If you come from a technical background and are looking to get ahead in the current competitive job market, then this course is for you.
LEAD WITH CONFIDENCE.
The first step to successfully implementing ethics is to understand what you are dealing with in the first place. If you are a manager in tech who cares about developing business and tech ethically to meet growing consumer and employee demands, then this course is for you.
WHAT THE COURSE INCLUDES:
A comprehensive immersion into AI and Big Data Ethics, this course is designed specially to establish an ethical literacy in technologybacked by an in-depth understanding of contemporary research. This course consists of six lessons, with each lesson focusing on an integral aspect of AI Ethics and structured to bring you the understanding and knowledge you need in order to embed ethics into your business and tech practices.
- Six lessons covering the major themes and important topics in Tech Ethics
- Engaging video lectures two to five minutes in length, designed to fit into your busy schedule
- Interactive assignments and quizzes to put your understanding to the test
- Further reading resources to ensure comprehension and information retention
- Access to the EI's exclusive community on AI Ethics
- Certification of completion
Still deciding whether or not to enroll? Reach out to us at [email protected]
We are happy to answer any questions or concerns you may have about the course.
- Welcome - Course Introduction (7:21)
- Instructor Introductions (3:43)
- 1. Lesson One Introduction (2:15)
- 2. Why does Ethics matter? (5:24)
- 2.1 Ethics as a Risk Mitigator (2:39)
- 2.2 Ethics as a Competitive Edge (4:53)
- 3. Understanding Ethical Frameworks (3:15)
- 3.1 Virtue Ethics (4:22)
- 3.2 Duty Ethics (3:22)
- 3.3 Consequential Ethics (4:20)
- 4. Ethical Framework Thought Experiment (2:49)
- 4.1 Quiz
- 5. Technical Thought Experiment (1:41)
- 5.1 Quiz
- 6. Closing Remarks (4:19)
- 7. Assignment
- 8. Further Reading
- 1. Lesson Two Introduction (3:41)
- 2. What "Eliminating Bias" Really Means (6:29)
- 3. Why Does Eliminating Negative Bias Matter: Principle of Discriminatory Non-Harm (3:04)
- 4. Identifying Bias and its Harms (5:22)
- 4.1 Allocation versus Representation Harm (4:49)
- 4.2 The Five Types of Harm (11:05)
- 5. Quiz - Identifying Harm
- 6. The Importance of Fairness (2:08)
- 6.1 Measuring Fairness; Technical (7:44)
- 6.2 Measuring Fairness; Non-technical (3:26)
- 7. Best Practices for Implementing Fairness (5:54)
- 8. Quiz - Identifying Best Practices
- 9. Closing remarks (2:27)
- 10. Assignment
- 11. Further Reading
- 1. Lesson Three Introduction (1:43)
- 2. Data as a Commodity (4:28)
- 3. Redefining Privacy in the Era of Tech (4:17)
- 4. GDPR and the Attempt to Regain Privacy (5:06)
- 5. Data Lifecycle: Pinpointing Privacy Risks (6:33)
- 6. Quiz
- 7. The "Sunlight Test" (3:15)
- 8. Closing remarks (2:12)
- 9. Assignment
- 10. Further Reading
- 1. Lesson Four Introduction (1:22)
- 2. Moral Responsibility: The Origin of Accountability (4:29)
- 3. The Accountability Gap (6:59)
- 4. Mind the Gap: Consequences of a Lack of Accountability (3:16)
- 5. Closing the Gap (1:22)
- 5.1 Anticipatory vs Remedial Accountability (3:27)
- 5.2 Internal vs External Auditing (3:36)
- 6. Quiz
- 7. Why Accountability and Sustainability Go Hand in Hand (2:24)
- 8. Sustainability and AI: Environmental Impact (1:49)
- 9. Stakeholder Impact Assessment (3:14)
- 10. Closing Remarks (1:14)
- 11. Assignment
- 12. Further Reading
- 1. Lesson Five Introduction (1:29)
- 2. In Tech We Trust (1:52)
- 2.1 What it Means to Trust (1:46)
- 2.2 Trusting an AI System (1:54)
- 3. How Transparency Helps Secure Trust (1:53)
- 3.1 Outcome Transparency (1:57)
- 3.2 Process Transparency (2:55)
- 4. Quiz
- 5. The Origin of the Black Box (3:55)
- 6. Explainability and AI Safety (2:59)
- 7. Looking into the Black Box: Technical (6:09)
- 8. Looking into the Black Box: Non-technical (3:06)
- 9. Closing Remarks (2:16)
- 10. Assignment
- 11. Further Reading
- 1. Lesson Six Introduction
- 2.1. European Union: Ethics Guidelines for Trustworthy AI
- 2. Impact of International Policies on AI Ethics
- 2.2. United Kingdom: The Guide to Using AI in the Public Sector
- 2.3. China: Beijing AI Principles
- 2.4. United States: American AI Initiative
- 3. Commonalities Between Policies
- 4. Key Differences
- 5. Quiz
- 6. The One Thing AI Ethics Policies Can't Solve
- 7. Closing Remarks
Olivia is an AI Ethicist who works with tech entrepreneurs to understand the importance of ethics in AI development and usage. Olivia believes that artificial intelligence offers unheard of opportunities for innovation in technology but which can only be realized through responsible and ethical practices. Olivia is originally from the Bay Area, where she started her career working in digital marketing for startups. Olivia holds an MSc in Philosophy from the University of Edinburgh, her dissertation concentration on moral responsibility and self-driving cars, a BA in Philosophy and Entrepreneurship from Baylor University, and currently sits on the Advisory Board of Tech Scotland Advocates.
Andrew has a long career in software engineering, most recently consulting for several high profile organizations in the sports technology space. He is also a working on a PhD in philosophy at York in Toronto, and was recently awarded a SSHRC doctoral fellowship. His research interests include issues at the intersection of cognition, tech ethics, and political epistemology.
FREQUENTLY ASKED QUESTIONS
When does the course start and finish?
The course starts when you enroll and finishes when you complete all six lessons - it is a completely self-paced online course.
How long do I have access to the course?
After enrolling, you have unlimited access to this course for as long as you like — across any and all devices you own.
What if I am unhappy with the course?
If you are unsatisfied with your purchase, contact us in the first 30 days and we will give you a full refund.
Will I get a grade or certificate?
No grades will be given in this course but you will receive a certificate of completion once you finish all the lessons.
Student discount available upon request
Email us at [email protected] using your school email and with a picture of your current school ID for more information.