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There are 6 modules in this course
The greatest risk in emerging technology is the perpetuation of bias in automated technologies dependent upon data sets. Solutions created with racial, gender or demographic bias, whether unintentional or not can perpetuate tragic inequities socially and economically. This is the first of five courses within the Certified Ethical Emerging Technologist (CEET) professional certificate and it is designed for learners seeking to advocate and promote the ethical use of data-driven technologies. Students will learn what emerging technologies are and how they can be used to create data driven solutions. You will learn types of bias and common ethical theories and how they can be applied to emerging technology, and examine legal and ethical privacy concepts as they relate to technologies such as artificial intelligence, machine learning and data science fields. Throughout the course learners begin to distinguish which types of bias may cause the greatest risk and which principles to apply to strategically respond to ethical considerations.
The first module in this course will cover some of the major technologies that are currently emerging in the world today, particularly data-driven technologies. The module will also go over some of the concepts that are fundamental to understanding how these technologies are used, without going into too much technical detail.
Promote the Ethical Use of Data-Driven Technologies Course Introduction•5 minutes
Course Welcome & Success Tips•2 minutes
Ethics Make a Difference in Emerging Technologies•3 minutes
Big Data•7 minutes
Working with Big Data•5 minutes
Data Analytics•3 minutes
Data Science Pipeline•8 minutes
Artificial Intelligence•7 minutes
Narrow AI•11 minutes
General AI and Superintelligence•7 minutes
Ambient Intelligence and IoT•6 minutes
The Black Box Problem•8 minutes
11 readings•Total 97 minutes
Overview•2 minutes
Get help and meet other learners. Join your Community!•5 minutes
Ethical Considerations for Data Science•10 minutes
Benefits of Ethical Data Science•10 minutes
A Day in the Life of an Ethical Data Scientist•10 minutes
Data Science Ethics in Practice•10 minutes
How Close are We to General AI?•10 minutes
Cracking the Black Box•10 minutes
Ethical Considerations for AI•10 minutes
Benefits of Ethical AI•10 minutes
A Day in the Life of an Ethical AI Engineer•10 minutes
1 assignment•Total 30 minutes
Data-Driven Emerging Technologies Quiz•30 minutes
1 discussion prompt•Total 10 minutes
Your Concerns•10 minutes
Examine Legal and Ethical Privacy Concepts as they Relate to Data-Driven Technology
Module 2•3 hours to complete
Module details
The second module in this course deals with the concept of privacy as it relates to data-driven technologies. You'll learn about the interaction of data and privacy from both a legal and ethical standpoint, as well as terms and concepts that surround these interactions.
Privacy Risks in IoT/Ambient Intelligence Technologies•6 minutes
Privacy Protection through Individual Authorization•4 minutes
Privacy Protection through Data Management•2 minutes
Privacy by Design•7 minutes
Differential Privacy•6 minutes
Legal Terminology: Responsibility, Accountability, and Liability•3 minutes
Technology Contract Types•2 minutes
Smart Contracts•5 minutes
8 readings•Total 72 minutes
Overview•2 minutes
The Privacy Paradox•10 minutes
Protected Attributes•10 minutes
Project Nightingale Case Study•10 minutes
How Anonymous Is Anonymous?•10 minutes
Data Sharing Agreements•10 minutes
Visual Contracts•10 minutes
Click-through Agreement•10 minutes
1 assignment•Total 30 minutes
Privacy and Legal Concepts Related to Data-Driven Technologies Quiz•30 minutes
1 discussion prompt•Total 10 minutes
Your Data Privacy Concerns•10 minutes
Examine Types of Bias
Module 3•2 hours to complete
Module details
This module outlines the concept of bias as it relates to data-driven technologies. In particular, it focuses on the types of biases out there, and how bias in data-driven technologies affects people and societies.
The Impact of Bias on Emerging Technologies•3 minutes
Bias•1 minute
Sociological Bias•4 minutes
Implicit Bias•4 minutes
Cognitive Biases•7 minutes
Confirmation Bias•8 minutes
Temporal Bias•3 minutes
Complacency and Automation Biases•4 minutes
Data Collection Bias•6 minutes
Statistical Bias•4 minutes
7 readings•Total 62 minutes
Overview•2 minutes
Project Implicit•10 minutes
Cognitive Bias Cheat Sheet•10 minutes
Confirmation Bias in Data Science•10 minutes
Racial Bias in Criminal Risk Assessment Algorithms•10 minutes
Bias in Facial Recognition Case Study•10 minutes
Modeling Bias•10 minutes
1 assignment•Total 30 minutes
Bias Quiz•30 minutes
1 discussion prompt•Total 10 minutes
Your Oranization's Bias Challenges•10 minutes
Examine Common Ethical Theories
Module 4•2 hours to complete
Module details
This module will cover some of the major theories and concepts that are involved in the field of ethics. It will also tie those theories and concepts to their application in data-driven technologies like AI.
CertNexus is a vendor-neutral certification body, providing emerging technology certifications and micro-credentials for Business, Data, Development, IT, and Security professionals. CertNexus’ exams meet the most rigorous development standards possible which outlines a global framework for developing personnel certification programs to narrow the widening skills gap.
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Learner reviews
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AM
5·
Reviewed on Apr 5, 2021
The course helped me validate the work I had already accomplished in AI Governance, Algorithmic Impact Assessment, and AI Ethic Principles and Procurement.
M
MV
4·
Reviewed on Sep 29, 2022
Good summary and mix of content. The peer articles review are not good to review the majority of them are fake files.
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BJ
5·
Reviewed on May 10, 2024
I understand there a lot useful information around ethical AI, thanks for the course and instructors.
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