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Human-Centered Artificial Intelligence

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Human-Centered Artificial Intelligence

Instructeur : Carlos Toxtli Hernandez

Inclus avec

6 modules

Obtenez un aperçu d'un sujet et apprenez les principes fondamentaux.

20 avis

niveau Intermédiaire

Certaines connaissances prérequises

Planning flexible

2 semaines à 10 heures une semaine

Apprenez à votre propre rythme

Préparer un diplôme

6 modules

Obtenez un aperçu d'un sujet et apprenez les principes fondamentaux.

20 avis

niveau Intermédiaire

Certaines connaissances prérequises

Planning flexible

2 semaines à 10 heures une semaine

Apprenez à votre propre rythme

Préparer un diplôme

Compétences que vous acquerrez

Catégorie : Human Machine Interfaces
Catégorie : Responsible AI
Catégorie : Human Computer Interaction
Catégorie : Model Evaluation
Catégorie : Artificial Intelligence and Machine Learning (AI/ML)
Catégorie : Data Ethics
Catégorie : Machine Learning Methods
Catégorie : Machine Learning
Catégorie : Ethical Standards And Conduct
Catégorie : Human Centered Design
Catégorie : Artificial Intelligence

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Catégorie : Generative AI

Détails à connaître

Évaluations

24 devoirs

Enseigné en Anglais

91%

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Il y a 6 modules dans ce cours

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.

Détails du module

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.

Inclus

13 vidéos4 lectures4 devoirs1 sujet de discussion

13 vidéosTotal 99 minutes

Welcome to the Course8 minutes
Human-Centered Computing5 minutes
HCC Perspectives13 minutes
Computational Perspectives10 minutes
User Centered Design8 minutes
Prototyping6 minutes
Experimental Settings4 minutes
Research Methods in HCC10 minutes
Experimental Methods14 minutes
Content Analysis & Grounded Theory7 minutes
Instruments and Measurements5 minutes
Tools and Libraries for HCC Research4 minutes
Closing Thoughts: Embracing the HCC Journey4 minutes

4 lecturesTotal 35 minutes

Course Outline10 minutes
Overview of Course Learning Objectives10 minutes
Learner Support Resources10 minutes
Connecting Course Learning Objectives5 minutes

4 devoirsTotal 90 minutes

Module 1 Quiz60 minutes
Practice Quiz #110 minutes
Practice Quiz #210 minutes
Practice Quiz #310 minutes

1 sujet de discussionTotal 10 minutes

Introduction Discussion10 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.

Inclus

17 vidéos1 lecture4 devoirs

17 vidéosTotal 175 minutes

Introduction to Artificial Intelligence (AI)13 minutes
Predicting Patterns and Values in Tabular Data5 minutes
Predictions8 minutes
Error Evaluation7 minutes
Binary Classification Basics4 minutes
Neural Networks7 minutes
Convolutional Neural Networks (CNN)8 minutes
Recurrent Neural Networks (RNN)7 minutes
Transformers15 minutes
Large Language Models9 minutes
Machine Learning Approaches23 minutes
Introduction to AI Research Methods10 minutes
Training and Evaluation Metrics for AI Models16 minutes
Evaluation Metrics: Confusion Matrix, Benchmarking, and Ablation Studies5 minutes
Other Machine Learning Model Evaluations19 minutes
Ensuring Reproducibility: Simulations and Controlled Experiments7 minutes
Field Deployments11 minutes

1 lectureTotal 10 minutes

Connecting Course Learning Objectives10 minutes

4 devoirsTotal 90 minutes

Module 2 Quiz60 minutes
Practice Quiz #110 minutes
Practice Quiz #210 minutes
Practice Quiz #310 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.

Inclus

18 vidéos1 lecture4 devoirs

18 vidéosTotal 100 minutes

Introduction to Human-Centered AI4 minutes
HCC Perspectives in HCAI6 minutes
Main Principles of HCAI12 minutes
Reliable, Safe, and Trustworthy Systems5 minutes
Methodologies in Human-Centered Computing7 minutes
Challenges and Critiques in HCAI3 minutes
Fairness, Bias, and Discrimination in AI4 minutes
Research Methods in HCAI6 minutes
Reliability and Robustness in AI Systems5 minutes
Transparency and Explainability in AI5 minutes
Accountability and Safety in HCAI4 minutes
Human Oversight and Control3 minutes
Wellbeing and Accessibility Research in AI4 minutes
Instruments and Measurements in AI Research7 minutes
Detailed Examples of Instrument Usage14 minutes
Practical Application of HCAI5 minutes
Research Directions in HCAI3 minutes
Conclusion and Future Directions5 minutes

1 lectureTotal 10 minutes

Connecting Course Learning Objectives10 minutes

4 devoirsTotal 90 minutes

Module 3 Quiz60 minutes
Practice Quiz #110 minutes
Practice Quiz #210 minutes
Practice Quiz #310 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.

Inclus

18 vidéos1 lecture4 devoirs

18 vidéosTotal 147 minutes

Introduction to Collective Intelligence7 minutes
Benefits and Challenges of Collective Intelligence7 minutes
Crowdsourcing and Collective Intelligence7 minutes
Prediction Markets and Swarm Intelligence8 minutes
Human-AI Collective Intelligence6 minutes
Biases and Ethics in Collective Intelligence7 minutes
Collective Intelligence in Organizations9 minutes
Evaluation of Collective Intelligence8 minutes
Collective Intelligence Platforms and Case Studies10 minutes
Introduction to Hybrid Intelligence10 minutes
Human-AI Division of Labor and Interaction Design10 minutes
Adjustable Autonomy and Mixed-Initiative Interaction7 minutes
Algorithmic Mediation5 minutes
Augmenting Human Capabilities8 minutes
Risks and Ethics of Human-AI Collaboration7 minutes
Applications of Hybrid Intelligence5 minutes
Guided Examples of Collective Intelligence8 minutes
Guided Examples of Hybrid Intelligence19 minutes

1 lectureTotal 10 minutes

Connecting Course Learning Objectives10 minutes

4 devoirsTotal 90 minutes

Module 4 Quiz60 minutes
Practice Quiz #110 minutes
Practice Quiz #210 minutes
Practice Quiz #310 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.

Inclus

17 vidéos1 lecture4 devoirs

17 vidéosTotal 89 minutes

Introduction to Algorithmic Bias4 minutes
Sampling and Selection Bias9 minutes
Data Collection and Representation Biases7 minutes
Aggregation and Time-Related Biases8 minutes
Measurements and Evaluation Biases7 minutes
Model and Algorithm Biases10 minutes
Measuring and Mitigating Algorithmic Bias2 minutes
Fairness-Aware Machine Learning3 minutes
Introduction to Fairness3 minutes
Pre-, In-, Post-Processing Approaches for Fairness5 minutes
Considerations for Algorithmic Fairness4 minutes
Sector-Specific Algorithmic Bias and Future Research Directions4 minutes
Implementing and Evaluating Fairness Metrics and Mitigation Techniques2 minutes
Analyzing and Addressing Bias in Natural Language Processing5 minutes
Case Study: Fair Housing Loan Approval4 minutes
Practical Frameworks and Tools for Ensuring Fairness in AI6 minutes
Fair AI Lifecycle Project: Fair Credit Scoring System8 minutes

1 lectureTotal 10 minutes

Connecting Course Learning Objectives10 minutes

4 devoirsTotal 90 minutes

Module 5 Quiz60 minutes
Practice Quiz #110 minutes
Practice Quiz #210 minutes
Practice Quiz #310 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.

Inclus

9 vidéos4 lectures4 devoirs

9 vidéosTotal 48 minutes

Introduction to AI Alignment6 minutes
Aligning AI with Human Values: Challenges, Theory, and Learning Techniques5 minutes
Reinforcement Learning and Human Feedback: Exploring RLHF Mechanisms6 minutes
Online Learning for Alignment, Value, Locking, and Constitutional AI (RLAIF)5 minutes
Middleware for Alignment: Case Studies on AI Assistants and Social Media6 minutes
Oversight Mechanisms: Alignment Progress Metrics and International Cooperation6 minutes
AI Ethics5 minutes
Moral Deskilling, Ethics Washing, and Moral Overload4 minutes
Ethical Risk Assessment and Technical Solutions3 minutes

4 lecturesTotal 25 minutes

Connecting Course Learning Objectives10 minutes
Course Feedback & Ratings5 minutes
Preview the Complete, For-Credit Course5 minutes
Earn Your MS in CS with Clemson5 minutes

4 devoirsTotal 90 minutes

Module 6 Quiz60 minutes
Practice Quiz #110 minutes
Practice Quiz #210 minutes
Practice Quiz #310 minutes

Préparer un diplôme

Ce site cours fait partie du (des) programme(s) diplômant(s) suivant(s) proposé(s) par Clemson University. Si vous êtes admis et que vous vous inscrivez, les cours que vous avez suivis peuvent compter pour l'apprentissage de votre diplôme et vos progrès peuvent être transférés avec vous.¹

Instructeur

Évaluations de l’enseignant

(10 évaluations)

Carlos Toxtli Hernandez

Clemson University

1 Cours1 303 apprenants

Offert par

Clemson University

Avis des étudiants

5 stars
55 %
4 stars
20 %
3 stars
0 %
2 stars
0 %
1 star
25 %

Affichage de 3 sur 20

Révisé le 23 mars 2026

Very relevant in today's world. Simple explanations with practical examples.

Révisé le 4 juil. 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.

Voir plus d’avis