GenAI Fundamentals for UX Designers + Researchers

Name: GenAI Fundamentals for UX Designers + Researchers
Rating: 4.2 (1924 reviews)

Learn the key concepts and components to harness GenAI for UX design — and lead AI product innovation efforts.

Bestseller

Created byJoe Natoli

Last updated 10/2024

English

German [Auto],English [Auto],

What you'll learn

Learn core principles of responsible GenAI design that ensure our products serve all users equally + equitably.
Success factors unique to Machine Learning (ML) products that UX + Product Designers and their teams should adopt
Guidance on research to determine what kinds of problems are best solved by AI, and where human control should remain central.
Determining when AI features are appropriate for users — and when they aren't
Identifying when Automation (AI does the task for users) or Augmentation (help them do it better) is more appropriate.
Designing the reward function and appropriately considering the balance between false positives and false negatives.
Essential factors to consider when evaluating the reward function.
How to weigh necessary, unavoidable tradeoffs between precision and recall, which is key to shaping an AI user experience.
Designing for fairness and inclusion, from objectives to datasets to guidance on bias testing.
Designing for generative variability: how do we present multiple, varied outputs to users — and how do we guide them in selecting the best one?
Designing for multiple outputs: how do we help users filter and highlight differences between outputs?
Designing for imperfections: how do we empower users to manage + mitigate imperfections and designing with contextual sensitivity?
Designing for confidence: how do we design confidence scoring to properly evaluate output quality and increase user trust?
Rules and examples for applying confidence scores.
Designing for co-creation: how to we design co-creation processes where both the user and the AI can make adjustments?
Designing for generic controls: using "temperature" to control the number of outputs and the degree of variability in those outputs.
Designing for domain-specific controls, such as encoder-decoder models, semantic sliders and prompt engineering.
Designing for prompt engineering: enabling and guiding users to effectively use multiple types of conversational prompts.
Designing for exploration: incorporating flexibility, feedback, transparency and error handling/expectation management.
Designing for choice, feedback, transparency + safety: centering users as active, empowered participants in the creation process.
Designing for mental models: orienting users to generative variability, teaching effective use and teaching the AI about the user.
Designing for explanation, understanding + trust: providing clear rationales for outputs, using friction to curb over-reliance and showing imperfections.
Designing against harm: understanding the critical ways irresponsible AI design can harm people.
Designing against hazardous outputs: discrimination, exclusion, toxicity, misinformation, deep fakes, IP theft and more.
Mitigating harm with a Value-Sensitive Design (VSD) process, integrated with an Agile or Lean development process.

Course content

5 sections • 29 lectures • 2h 47m total length

Understanding the challenge: the UX of variability3:58
Explore the UX of generative AI variability, designing human-centered, trustworthy, safe, and ethical experiences that maximize productive use while mitigating risks.
Principles to adopt for UXers, Designers and Product Teams6:16
Adopt Google's AI principles to design socially beneficial, user-centered AI products; minimize bias, ensure safety and privacy, maintain accountability, uphold scientific excellence, and prevent harm.
Responsible best practices for Gen AI UX + Design5:16
Put users first with human-centered design and clear ai behavior, granting control and confident results. Test with diverse users, measure with multiple metrics, ensure data quality, and monitor after deployment.
Download the 164-page companion workbook!0:15

Who What + When: core areas of investigation3:51
Identify where user needs meet ai strengths, such as personalized recommendations and data analysis. Differentiate automation from assistance, automate tedious tasks while keeping human control and a transparent reward function.
When AI is appropriate for users (and when it's not)3:17
Decide when AI improves a product by weighing user benefit and risk, and apply AI for personalized recommendations, natural language understanding, and dynamic content while using rule-based methods when appropriate.
Automation vs. Assistance: determining when each is appropriate for users4:49
Assess when AI should automate tasks to save time, boost safety, and handle repetitive work. Learn when AI should assist to augment creativity while preserving user control and personal responsibility.
Designing the AI Reward Function5:42
Design and evaluate the AI reward function to balance false positives and false negatives, weigh precision and recall, and align outcomes with user needs through cross-functional collaboration.
Evaluating the AI Reward Function6:30
Design an inclusive AI reward function that promotes fairness, mitigates negative impact, and sustains long-term value through continuous feedback, monitoring, and iterative refinement.
Making Smart Tradeoffs: Precision vs. Recall4:57
Balance precision and recall to design trustworthy AI that fits your users and content, then continuously test and adjust the mix of high and low confidence results.
Addressing Fairness + Inclusion in AI4:46
learn how to design fair, inclusive ai by defining clear fairness objectives, using diverse training data, and testing for bias with real-world edge cases and broad performance metrics.

Designing for Generative Variability3:59
Explore generative variability in UX design by presenting multiple outputs for the same input. Guide users to compare options and understand AI's probabilistic outputs to encourage exploration.
Designing for Multiple Outputs5:56
Explore how to design tools that manage multiple outputs from generative ai, using versioning, curation, annotation, and visualization to filter, compare, and select the best or diverse results.
Designing for Imperfections7:14
Design for imperfect generative outputs by empowering users with editing, multiple outputs, and adaptive feedback, while communicating uncertainty and contextual sensitivity to build trust.
Designing for Confidence: Evaluation + Scoring5:53
Explore how confidence scores in generative AI inform UX design, evaluation, and trust at scale, with guidelines for visuals, explanations, drill-down, and user feedback.
Applying Confidence Scores: Rules + Examples9:30
Align confidence scores with NLU, ASR, sentiment analysis, and TTS to improve transparent AI decisions and user trust in UX design, and apply thresholds that reveal all considered intents.
Designing for Co-Creation7:46
Designing for Generic Controls3:46
Explore human centered ai by using generic controls to manage the number and variability of outputs, with temperature guiding creativity toward precision.
Designing for Domain-Specific Controls3:29
Explore domain-specific controls in generative AI, including encoder-decoder models, semantic sliders, and prompt engineering, using Cococo's AI steering tools to boost user trust, control, and ownership in creative outputs.
Designing for Prompt Engineering4:20
Explore prompt engineering basics for GenAI with Google best practices, including role, context, constraints, and examples, and master direct, few-shot, and multi-shot prompts for UX design.
Designing for Exploration6:00
Design for exploration in ai-driven user experience design by embracing variability, offering multiple outputs, flexible interface with adaptable cards and filters, and clear feedback to build trust.
Designing for Choice, Feedback, Transparency + Safety8:04
Empower users with curated options and progressive disclosure to explore AI outputs without overwhelming. Build for feedback, transparency, and safe exploration to keep users in control of generative AI experiences.
Designing for Mental Models5:43
Design for mental models in generative AI by revealing generative variability, guiding users with in-context explanations and examples, and aligning AI behavior with user expectations and trust.
Designing for Explanation, Understanding + Trust9:45
Explore designing explanations for generative ai apps to build trust and understanding for ux designers and researchers, including xai and human-centered ai, with in-context guidance and continuous learning.

Types of Harm + Designing Responsibly7:01
Explore the risks of generative AI, including identity denial, freedom interference, and cultural erasure, and learn responsible, human-centered design practices to mitigate harm and ensure ethical, compliant solutions.
Hazardous Model Outputs9:31
Learn the ethical and safety risks of large language models, including discrimination, information hazards, privacy leaks, and misinformation. Explore design strategies for transparency, consent, and copyright-aware, user-safe AI experiences.
Designing for Misuse7:08
Mitigating Harm with Value-Sensitive Design (VSD)8:38
Apply Value Sensitive Design to mitigate harms in generative AI by identifying key values of users, analyzing context of use, and iterating designs to uphold privacy, fairness, and inclusivity.

Requirements

None. GenAI is stil extremely new to the world of UX, so this fundamentals course is meant to get you on solid ground fast, no matter your experience.

Description

Protect and grow your career: Learn to design GenAI-enabled products

The UX and Product design landscape is evolving—and AI is leading the charge. If you're a designer, UXer, or product developer, you can't afford to be left behind. Generative AI is not just a buzzword; it's becoming the backbone of the next generation of user experiences. And without a deep understanding of how to design AI-powered products, your skill set risks becoming obsolete.

This course is for you if you want to:

Stay relevant in an industry that’s rapidly integrating AI into every aspect of product development and feature sets.
Be the asset your employer relies on—not the UXer or designer left off key projects because you lack the necessary skills.
Lead the future of UX and design rather than have it dictated to you by engineers and product managers.

Why you must start learning the fundamentals of GenAI product design now

AI isn’t just an optional add-on anymore. It’s the next fundamental shift in product design—just like when UX and UI became indispensable. Here’s the reality:

Employers want designers who understand how to design user-centered GenAI experiences that are useful, usable, valuable, and trustworthy. Without this skill, your job security and opportunities will shrink.
Product improvement initiatives and AI integration projects are happening in every major company, from simple voice and chatbot interfaces to workflow-based conversational experiences. The people who know how to design these experiences are the ones who will be chosen for leadership roles.
AI is the new frontier in UX and product design. Just as front-end coding knowledge became essential for UXers, understanding emerging design trends for GenAI — and how to design and evaluate AI-enabled products — is the next career progression.

If you don’t understand AI-enabled design, you won’t be part of these key projects. Your value will diminish—both to your current employer and in the eyes of potential future employers.

What you’ll learn in this course

Master the fundamentals of designing AI-powered products
- Learn the principles that guide effective, responsible design for AI. I’ll teach you the fundamental principles and approaches behind experiences that blend the power of AI with intuitive, human-centered design. From initial investigation and research to designing features, functionality and evaluation metrics to gauge usability and measure trust, I'll tackle all the core areas you need to know about.
- Why it matters: AI is about more than automation. It’s about delivering useful and valuable user experiences that meet both user needs and business goals.
Create ethical, trustworthy AI-driven products
- I’ll show you how to build AI products that users trust—and that won’t perpetuate bias or misinformation. You’ll learn the ethical considerations you need to think through and how to design with fairness and transparency in mind.
- Why it matters: Building trust is crucial in AI. Companies are investing in AI solutions that don’t just work but are ethical and inclusive. Your ability to design these systems will set you apart.
Understand the basics of designing for key GenAI attributes like generative variability and tradeoffs between precision and recall.
- Generative variability is the heart of GenAI. I'll walk you through two critical questions we, as UXers and designers, have to answer: (1) how do we present multiple, varied outputs to users and (2) how do we guide them in selecting the best one?
- As a UX or product designer, one of the key decisions you’ll face when working with AI systems is how to balance precision and recall. I'll dig intot both concepts and walk you through how to design that balance appropriately.
- Why it matters: Generative variability is the heart of GenAI, and designing for it requires an approach that's very different from the products we typically tackle. In particular, precision and recall define how accurate and thorough your AI’s results will be — and getting the balance right directly impacts UX and user trust.
Turn AI into a business asset for your clients or employers
- Design AI systems that do more than just function—they deliver real business value. I’ll teach you how to align AI-driven products with business objectives, ensuring that the user experience drives results.
- Why it matters: Your ability to create AI-enabled products that solve real business challenges will make you a valuable asset to your employer.
Be a leader in AI-enabled UX and product design
- As AI continues to reshape the design industry, you’ll be equipped to lead AI-focused design projects, taking your career to the next level. No more waiting on engineers to explain AI to you. You’ll be the one leading the collaborative charge to determine how AI best fits into product design.
- Why it matters: Leaders in this field don’t wait for opportunities—they create them. Position yourself as a forward-thinking designer who is driving AI adoption and innovation.

Who this course is for:

New UX and Product Designers: If you’re starting out and want to make your career trajectory more stable and secure, this course will give you the foundation to be an asset to your employer from day one.
Experienced UXers, Product Designers and Product Developers: If you’re already working in the industry and want to stay competitive and lead the next wave of innovation, this course will teach you how to begin integrating AI product design into your current design skill set — and to have informed, productive conversations with software engineers and data scientists on GenAI projects.

I've included a massive GenAI UX workbook you can use on real-world projects.

You can download and use this 164-page companion workbook to use both as practice and to help you through the process of designing for GenAI in your daily work as well. Use the guidance and 89 exercises across 22 mission-critical topics in GenAI design for any real-world GenAI projects that come your way — the exercises here are designed to help you through the process, from concept to execution.

Who this course is for:

New UX and Product Designers: If you’re starting out and want to make your career trajectory more stable and secure, this course will give you the foundation to be an asset to your employer from day one.
Experienced UXers, Product Designers and Product Developers: If you’re already working in the industry and want to stay competitive and lead the next wave of innovation, this course will teach you how to begin integrating AI product design into your current design skill set — and to have informed, productive conversations with software engineers and data scientists on GenAI projects.
UX Researchers, UX Writers, Product Managers and anyone wondering what they need to know in order to play a role in designing GenAI-driven products.
Practitioners of all kinds who are new to the world of GenAI — and don't know where to start learning about it.

GenAI Fundamentals for UX Designers + Researchers

What you'll learn

Explore related topics

Course content

Principles, Practices + Possibilities4 lectures • 16min

Context of Use: Investigation + Research7 lectures • 34min

Design principles for Gen AI models + apps13 lectures • 1hr 21min

Designing Against Harms4 lectures • 32min

The Future of Gen AI UX is Yours (No, Really)1 lecture • 4min

Requirements

Description

Who this course is for: