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Fundamentals to build Human Centered AI (HCAI) Systems

Posted By: lucky_aut
Fundamentals to build Human Centered AI (HCAI) Systems

Fundamentals to build Human Centered AI (HCAI) Systems
Published 4/2025
Duration: 42m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 600 MB
Genre: eLearning | Language: English

Master the principles and frameworks of ethical AI design to create responsible, human-centered intelligent systems

What you'll learn
- Identify and articulate the key principles of Human-Centered AI (HCAI) and distinguish it from traditional AI approaches
- Analyze real-world AI failures and explain how HCAI principles could have prevented them
- Apply established HCAI frameworks like Google PAIR, Shneiderman's model, and IDEO cards to evaluate existing AI systems
- Conduct a structured heuristic evaluation of AI experiences using human-centered design principles
- Design AI systems that balance transparency, agency, fairness, and efficiency through thoughtful trade-offs
- Create effective human-AI collaboration models that leverage the complementary strengths of both
- Develop strategies for implementing ethical AI review processes within organizations
- Construct a comprehensive HCAI blueprint for specific application domains like healthcare, finance, or education

Requirements
- No coding or technical background required
- Basic familiarity with AI concepts and tools is helpful but not necessary
- Experience with product development, design, or technology management is beneficial

Description
Human-Centered AI: Designing Responsible Intelligence is your comprehensive guide to building AI systems that truly work for people—not just algorithms and datasets. In this practical, hands-on course, you'll learn how to create AI experiences that are ethical, transparent, and genuinely enhance human capabilities.

AI is transforming every industry, but many systems aren't designed with humans at the center, leading to bias, confusion, and harm. This course equips you with the frameworks, tools, and practical skills to design better AI that earns trust and delivers real value to users.

Through a combination of real-world case studies, interactive exercises, and hands-on design challenges, you'll learn how to:

Evaluate AI systems using human-centered principles

Identify potential biases and ethical pitfalls before they cause harm

Design for effective human-AI collaboration

Create AI experiences that are transparent, controllable, and fair

Implement ethical review processes in your organization

Whether you're designing AI products, managing AI development teams, or making decisions about AI implementation, this course will give you the knowledge and tools to build AI that respects human needs, values, and agency.

What You'll Learn

Understand the core principles of Human-Centered AI and how they differ from traditional AI approaches

Analyze case studies of AI failures and identify how HCAI principles could have prevented them

Apply established frameworks like Google PAIR and Shneiderman's HCAI model to evaluate AI systems

Conduct structured heuristic evaluations of AI experiences using human-centered design principles

Design AI systems that balance transparency, agency, fairness, and efficiency through thoughtful trade-offs

Create effective human-AI collaboration models that leverage complementary strengths

Develop strategies for implementing ethical AI review processes within organizations

Construct a comprehensive HCAI blueprint for specific application domains

Requirements

No coding or technical background required

Basic familiarity with AI concepts and tools is helpful but not necessary

Experience with product development, design, or technology management is beneficial

Who This Course Is For

Product managers working with AI features or leading teams developing AI products

UX/UI designers integrating AI components into user interfaces and workflows

AI/ML engineers wanting to build more ethical and user-centered systems

Business leaders making strategic decisions about AI implementation

Researchers and strategists exploring responsible AI development

Ethics officers and compliance professionals ensuring responsible AI use

Design thinking practitioners applying their skills to AI-specific challenges

Technology professionals seeking to understand the human impact of AI

Course Structure

Module 1: What is Human-Centered AI?

Introduction to the core concepts of HCAI

Contrast between human-centered and traditional AI approaches

Analysis of famous AI failures and their human impact

Exploration of key HCAI principles: transparency, agency, fairness, and more

Module 2: Designing AI for Human Needs

Overview of practical HCAI frameworks (Google PAIR, Shneiderman, IDEO)

Methodology for evaluating AI experiences using human-centered principles

Live audit of real AI tools using HCAI checklists

Hands-on redesign workshop to improve AI systems

Module 3: Responsible Innovation & AI Futures

Exploration of effective human-AI collaboration models

Analysis of complex ethical dilemmas in AI design

Strategic templates for implementing ethical AI in organizations

Creation of an HCAI blueprint for real-world application domains

By the end of this course, you'll have the practical skills and ethical framework to design, evaluate, and implement AI systems that truly work for people, not just algorithms.

Who this course is for:
- Product managers who are working with AI features or overseeing teams developing AI products
- UX/UI designers integrating AI components into user interfaces and workflows
- AI/ML engineers looking to build more human-centered and ethically sound systems
- Business leaders making strategic decisions about AI implementation in their organizations
- Researchers and strategists exploring responsible AI development and governance
- Ethics officers and compliance professionals tasked with ensuring responsible AI use
- Design thinking practitioners wanting to apply their skills to AI-specific challenges
- Technology professionals seeking to understand the human impact of AI systems they build or use
More Info

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