INTRO TO AI PRODUCT DESIGN

Today begins your AI career. Explore the course structure and available paths to get the most out of it. Learn the AI landscape shaping the current and future job market, and choose your winning capstone project.

• Instructor Introduction
• Course objectives, expectations & flow
• The AI Landscape Today: Impacts on You
• The Mindset Needed to Succeed in AI
• Create Your AI Companion: Leveraging Your Myers-Briggs Style for Innovation
• AI Job Market & Capstone Selecting
• Q & A

Demystify the AI buzzwords: Start with the essentials and analyze their user implications and benefits.

• State of AI: Technological Progress
• Experience-driven framework to technology literacy
• Technology literacy needed for AI product design
• In-demand industry areas
• Case Study & Simulation: It's not all about GenAI

Continue to demystify all the AI buzzwords: Moving to the next level to analyze their user implications and benefits.

• Technology literacy needed for AI product design:
  • Deep Learning
  • Recurrent Neural Networks (RNN)
  • Large Language Model (LLM)
• How these newer concepts build on what we learned in Class 01
• In-demand industry areas
• Case Study & Simulation: Conflicts between customer/end-user expectations and products with different AI technologies involved.

Explore the upcoming and arising to analyze their user implications and benefits.

• Top AI Trends & Upcoming
• In-demand industry areas
• UX Impact Radar Technology literacy needed to be ready for AI product design
• Case Study & Simulation: Conflicts between customer/end-user expectations and products with different AI technologies involved.
• Case Study: GenAI weakness
• Video Demo Real-world augmenting examples (Devin, Rabbit (LAM) & Hume)

Set up your product for success by choosing an appropriate use case and taking an outcome-driven approach.

• Key nuances in the product development lifecycle for AI products
• Outcome-drive approach plays an essential role in AI product design
• Select high ROI use cases contextualized for your industry
• Product objectives: Setting clear & measurable AI product goals
• Adherence to relevant regulations & policies
• Case Study: Gartner’s AI business use case prism
• Case Study & Simulation: A real-world example showcasing how GenAI can expand an existing product's capabilities.

Assignment 1: Choose an AI business use case to kickstart your AI product design career. Identify 3-5 real-world products in that area to serve as role models (both good and bad). Apply your AI knowledge to analyze the use case and examples, listing user benefits and implications.

Distinguish how to build AI experiences that augment (not replace) human capabilities. Learn what AI product development is and its nuances compared to non-AI products.

• AI is a Tool to Extend Human Capabilities, Not Replace Them
• Implications of exponential market speed
• Backcasting methodologies
• Case Study: Real-world augmenting examples
• Workshop: Identify human challenges that AI might help

Assignment 2: Revisit your chosen use case with the latest AI technologies in mind, and define a problem your product can solve more effectively with AI. Identify two key user interaction points where AI can provide the most benefit.

Create Al systems that are ethical, unbiased, and inclusive, aligning with societal values and user needs.

• AI behaves differently based on data
• Biases & risks in AI algorithms & data
• AI explainability to meet customers' new expectations
• Fairness, inclusivity & alignment with societal values in AI design
• Case Study: When things go wrong
• Demo: Use AI tools to research & identify potential data sources.

Assignment 3: Take a fresh look at your project and identify any aspects that could go wrong (aka all the risks) and write out your mitigation strategies to derisk early on.

Develop knowledge and skills needed to maximize experience outcomes from AI’s capabilities.

• Human and AI/Machine Relationship
• Framework: input, output & hierarchies
• Multi-modality in the AI era: How to think holistically to meet customers at the right point
• Gartner's Total Experience Strategies: Identify touchpoints
• Case Study: Impact of Human and AI/Machine Relationship

Assignment 4: Using your chosen case and problem space, apply the knowledge from classes 01-03 to map out how to maximize experience gain through AI at key touchpoints and address specific pain points.

Craft intuitive user experiences and understand the user's pivotal role in human-AI relationship and product adoption.

• Gartner's Total Experience Strategies: User flows for AI-powered interactions
• User control design at each interaction point
• Connecting each interaction point to create Intuitive & seamless multimodal experiences in AI products
• Case Study: Total Experience & Multi-Modal Approach in B2B & B2C Success Case

Assignment 5: Select 1-2 flows in your AI product to prototype in detail. Determine the best modality to help users achieve their outcomes at various touchpoints within the overall flow.

Develop understanding and knowledge of the factors involved to move early winning AI solutions to scale.

• AI model training cost: building trust & performance scaling
• Rapid & interactive prototyping methods for AI solutions
• User testing & iteration for problem resolution
• Monitoring & Learning
• Case Study: Guardrail Design

Assignment 6: Based on the risks identified in Assignment 3, design potential guardrails to monitor the AI product launch.

Build a structured plan to effectively test and de-risk your ideas. Strategically design prototypes to validate Al-driven product ideas.

• Research Methods in AI Initiatives
• Pros and Cons of Lean Experimentation
• Leveraging Research Data
• Testing, refinement, and feature
• Case Study: Lean experiment and prototype
• Workshop: Formulate lean experimentation ideas: hypothesis, ways to validate/invalidate the hypothesis and justify the product idea, and derisk early on

Assignment 7: Develop a lean experiment plan: form a hypothesis, outline validation methods, justify the product idea, and mitigate risks early. Refine the prototype to support the experiment.

Gain expertise in navigating the AI product development lifecycle, and understand new trends and current expectations. Craft strategies to manage AI product development at an uncertain and accelerated pace.

• Rethink Persona
• Everyday AI and Gamechanger AI
• Major experience differences between designing for AI and non-AI products
• Shape of future needs in design system
• How's your stakeholders' doing with AI? - Massive Impact on AI product design lifecycle
• Curve balls in the AI era
• Case Study: Why is commercializing AI such a topic?
• Workshop: What could be evolved?

Enhance your ability to conduct effective design reviews, offer constructive feedback and adeptly manage design documentation & stakeholder expectations in the face of AI.

• How’s your stakeholders’ doing with AI? Huge impact on communicating and being heard.
• Purpose and Importance of Design Reviews
• Structuring Productive Design Reviews
• Effective Storytelling for AI product design
• Constructive Feedback Response and Iteration
• Design Documentation and Presentation to Address Stakeholder Concerns

Given new Design challenges, learn how to bridge design and technical teams through compelling storytelling and agile workflows, fostering seamless and collaborative product design journeys.

• How’s your stakeholders’ doing in the face of AI? Impact on collaborating
• Simulated peek into high-profile and uncertain AI initiatives in the real world
• Cross-functional Collaboration and Feedback: Engaging with developers, data scientists, and business stakeholders
• Communication practices to Bridge the Gap between Design and technical teams
• Communication Tools to Foster Collaboration between AI teams
• Contributing Back to the Community

Learn how to craft a compelling portfolio, use Personal Monopoly to competitively position yourself in the job market, and gain career insights from industry experts.

• Secret Recipes for Keeping Up with AI Nuances and Breakthroughs
• A framework for decoding AI technicality for UX impact
• Skills and qualifications for different roles in the AI product design field
• Fresh Industry Insights for Your AI Career Journey
• Professional AI Portfolio

Final Project: AI solution integrated into a product design students can work on throughout the assignments.