Human-Centered Artificial Intelligence

Instructor: Carlos Toxtli Hernandez

Access provided by SR University

6 modules

Gain insight into a topic and learn the fundamentals.

17 reviews

Intermediate level

Some related experience required

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

6 modules

Gain insight into a topic and learn the fundamentals.

17 reviews

Intermediate level

Some related experience required

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

Skills you'll gain

Tools you'll learn

Generative AI

Details to know

Assessments

24 assignments

Taught in English

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There are 6 modules in this course

Human-Centered Artificial Intelligence (HCC-6600) offers a deep-dive exploration into the ever-evolving landscape of artificial intelligence (AI) with a specific focus on the human aspect of the technology. This course provides an opportunity for learners to grasp the core principles and practices of AI while remaining critically aware of its implications for humanity. This course is designed to offer a well-rounded perspective, blending elements from diverse fields such as computer science, cognitive science, ethics, and design thinking. The aim is to ensure that learners emerge with not just an understanding of how AI systems are created and function, but also how these systems can be designed to respect and prioritize human values and needs.

In this module's Welcome to the Course lesson, review the course syllabus, learning objectives, and resources available. Then get to know your peers by completing the Introduction Discussion. Module 1 includes lectures on Human-Centered Computing (HCC) and research methods in HCC. While watching the lectures, check your understanding with the Practice Quizzes. Use the feedback from the Practice Quizzes to complete the Module 1 Quiz.

What's included

13 videos4 readings4 assignments1 discussion prompt

13 videos Total 99 minutes

Welcome to the Course 8 minutes
Human-Centered Computing 5 minutes
HCC Perspectives 13 minutes
Computational Perspectives 10 minutes
User Centered Design 8 minutes
Prototyping 6 minutes
Experimental Settings 4 minutes
Research Methods in HCC 10 minutes
Experimental Methods 14 minutes
Content Analysis & Grounded Theory 7 minutes
Instruments and Measurements 5 minutes
Tools and Libraries for HCC Research 4 minutes
Closing Thoughts: Embracing the HCC Journey 4 minutes

4 readings Total 35 minutes

Course Outline 10 minutes
Overview of Course Learning Objectives 10 minutes
Learner Support Resources 10 minutes
Connecting Course Learning Objectives 5 minutes

4 assignments Total 90 minutes

Practice Quiz #1 10 minutes
Practice Quiz #2 10 minutes
Practice Quiz #3 10 minutes
Module 1 Quiz 60 minutes

1 discussion prompt Total 10 minutes

Introduction Discussion 10 minutes

Module 2 includes lectures on Artificial Intelligence (AI), Human-Centered Artificial Intelligence (HCAI), and research methods in HCAI. While watching the lectures, check your understanding with the Practice Quizzes. Use the feedback from the Practice Quizzes to complete the Module 2 Quiz.

What's included

17 videos1 reading4 assignments

17 videos Total 175 minutes

Introduction to Artificial Intelligence (AI) 13 minutes
Predicting Patterns and Values in Tabular Data 5 minutes
Predictions 8 minutes
Error Evaluation 7 minutes
Binary Classification Basics 4 minutes
Neural Networks 7 minutes
Convolutional Neural Networks (CNN) 8 minutes
Recurrent Neural Networks (RNN) 7 minutes
Transformers 15 minutes
Large Language Models 9 minutes
Machine Learning Approaches 23 minutes
Introduction to AI Research Methods 10 minutes
Training and Evaluation Metrics for AI Models 16 minutes
Evaluation Metrics: Confusion Matrix, Benchmarking, and Ablation Studies 5 minutes
Other Machine Learning Model Evaluations 19 minutes
Ensuring Reproducibility: Simulations and Controlled Experiments 7 minutes
Field Deployments 11 minutes

1 reading Total 10 minutes

Connecting Course Learning Objectives 10 minutes

4 assignments Total 90 minutes

Practice Quiz #1 10 minutes
Practice Quiz #2 10 minutes
Practice Quiz #3 10 minutes
Module 2 Quiz 60 minutes

Module 3 includes lectures on Human-Centered Artificial Intelligence (HCAI), research methods in HCAI, practical applications of HCAI, and the future of HCAI. While watching the lectures, check your understanding with the Practice Quizzes. Use the feedback from the Practice Quizzes to complete the Module 3 Quiz.

What's included

18 videos1 reading4 assignments

18 videos Total 100 minutes

Introduction to Human-Centered AI 4 minutes
HCC Perspectives in HCAI 6 minutes
Main Principles of HCAI 12 minutes
Reliable, Safe, and Trustworthy Systems 5 minutes
Methodologies in Human-Centered Computing 7 minutes
Challenges and Critiques in HCAI 3 minutes
Fairness, Bias, and Discrimination in AI 4 minutes
Research Methods in HCAI 6 minutes
Reliability and Robustness in AI Systems 5 minutes
Transparency and Explainability in AI 5 minutes
Accountability and Safety in HCAI 4 minutes
Human Oversight and Control 3 minutes
Wellbeing and Accessibility Research in AI 4 minutes
Instruments and Measurements in AI Research 7 minutes
Detailed Examples of Instrument Usage 14 minutes
Practical Application of HCAI 5 minutes
Research Directions in HCAI 3 minutes
Conclusion and Future Directions 5 minutes

1 reading Total 10 minutes

Connecting Course Learning Objectives 10 minutes

4 assignments Total 90 minutes

Practice Quiz #1 10 minutes
Practice Quiz #2 10 minutes
Practice Quiz #3 10 minutes
Module 3 Quiz 60 minutes

Module 4 includes lectures on collective intelligence, hybrid intelligence, and human-in-the-loop. While watching the lectures, check your understanding with the Practice Quizzes. Use the feedback from the Practice Quizzes to complete the Module 4 Quiz.

What's included

18 videos1 reading4 assignments

18 videos Total 147 minutes

Introduction to Collective Intelligence 7 minutes
Benefits and Challenges of Collective Intelligence 7 minutes
Crowdsourcing and Collective Intelligence 7 minutes
Prediction Markets and Swarm Intelligence 8 minutes
Human-AI Collective Intelligence 6 minutes
Biases and Ethics in Collective Intelligence 7 minutes
Collective Intelligence in Organizations 9 minutes
Evaluation of Collective Intelligence 8 minutes
Collective Intelligence Platforms and Case Studies 10 minutes
Introduction to Hybrid Intelligence 10 minutes
Human-AI Division of Labor and Interaction Design 10 minutes
Adjustable Autonomy and Mixed-Initiative Interaction 7 minutes
Algorithmic Mediation 5 minutes
Augmenting Human Capabilities 8 minutes
Risks and Ethics of Human-AI Collaboration 7 minutes
Applications of Hybrid Intelligence 5 minutes
Guided Examples of Collective Intelligence 8 minutes
Guided Examples of Hybrid Intelligence 19 minutes

1 reading Total 10 minutes

Connecting Course Learning Objectives 10 minutes

4 assignments Total 90 minutes

Practice Quiz #1 10 minutes
Practice Quiz #2 10 minutes
Practice Quiz #3 10 minutes
Module 4 Quiz 60 minutes

Module 5 includes lectures on algorithmic bias and AI fairness. While watching the lectures, check your understanding with the Practice Quizzes. Use the feedback from the Practice Quizzes to complete the Module 5 Quiz.

What's included

17 videos1 reading4 assignments

17 videos Total 89 minutes

Introduction to Algorithmic Bias 4 minutes
Sampling and Selection Bias 9 minutes
Data Collection and Representation Biases 7 minutes
Aggregation and Time-Related Biases 8 minutes
Measurements and Evaluation Biases 7 minutes
Model and Algorithm Biases 10 minutes
Measuring and Mitigating Algorithmic Bias 2 minutes
Fairness-Aware Machine Learning 3 minutes
Introduction to Fairness 3 minutes
Pre-, In-, Post-Processing Approaches for Fairness 5 minutes
Considerations for Algorithmic Fairness 4 minutes
Sector-Specific Algorithmic Bias and Future Research Directions 4 minutes
Implementing and Evaluating Fairness Metrics and Mitigation Techniques 2 minutes
Analyzing and Addressing Bias in Natural Language Processing 5 minutes
Case Study: Fair Housing Loan Approval 4 minutes
Practical Frameworks and Tools for Ensuring Fairness in AI 6 minutes
Fair AI Lifecycle Project: Fair Credit Scoring System 8 minutes

1 reading Total 10 minutes

Connecting Course Learning Objectives 10 minutes

4 assignments Total 90 minutes

Practice Quiz #1 10 minutes
Practice Quiz #2 10 minutes
Practice Quiz #3 10 minutes
Module 5 Quiz 60 minutes

Module 6 includes lectures on AI alignment and AI ethics. While watching the lectures, check your understanding with the Practice Quizzes. Use the feedback from the Practice Quizzes to complete the Module 6 Quiz.

What's included

9 videos4 readings4 assignments

9 videos Total 48 minutes

Introduction to AI Alignment 6 minutes
Aligning AI with Human Values: Challenges, Theory, and Learning Techniques 5 minutes
Reinforcement Learning and Human Feedback: Exploring RLHF Mechanisms 6 minutes
Online Learning for Alignment, Value, Locking, and Constitutional AI (RLAIF) 5 minutes
Middleware for Alignment: Case Studies on AI Assistants and Social Media 6 minutes
Oversight Mechanisms: Alignment Progress Metrics and International Cooperation 6 minutes
AI Ethics 5 minutes
Moral Deskilling, Ethics Washing, and Moral Overload 4 minutes
Ethical Risk Assessment and Technical Solutions 3 minutes

4 readings Total 25 minutes

Connecting Course Learning Objectives 10 minutes
Course Feedback & Ratings 5 minutes
Preview the Complete, For-Credit Course 5 minutes
Earn Your MS in CS with Clemson 5 minutes

4 assignments Total 90 minutes

Practice Quiz #1 10 minutes
Practice Quiz #2 10 minutes
Practice Quiz #3 10 minutes
Module 6 Quiz 60 minutes

Build toward a degree

This course is part of the following degree program(s) offered by Clemson University. If you are admitted and enroll, your completed coursework may count toward your degree learning and your progress can transfer with you.¹

Instructor

Instructor ratings

(8 ratings)

Carlos Toxtli Hernandez

Clemson University

1 Course 1,154 learners

Offered by

Clemson University

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Reviewed on Jul 4, 2025

Very interesting and thorougly developed content. I found it difficult to understand the speaker but the transcripts helped a lot. I definitely recommend this course.

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