INTRO TO AI PRODUCT DESIGN

Master the fundamentals of AI and its applications in user-centered design, placing user needs at the core of innovative technology and data integration.

• Introduction to artificial intelligence and applications
• Trends: ChatGPT, LLM, machine learning, neural networks, foundation models
• Human-centered design for AI product development
• AI product lifecycle exploration
• Case study: Human-computer interaction

Assignment #1: Explore AI Integration in Real-World Products
Discover a real-life product harnessing AI, decipher its AI integration, and elucidate the value it delivers to both the business and the user.

Learn the principles of Machine Learning, distinguishing between supervised and unsupervised algorithms. Apply linear regression models to enhance design by integrating predictive capabilities.

• Technical learning for design
• Machine learning essentials
• Algorithms: supervised & unsupervised
• AI-driven data analysis: Exploring clustering mechanisms
• Demo: Real-world linear regression prediction

Assignment #2: Designing for Predictive Systems
Enhance subscriber retention through predictive design. Explore innovative strategies, and present your ideas in written or wireframe format.

In this class, you’ll explore neural network architecture, applications in product design, and the potential of Generative AI. We’ll also talk about applying RNN and NLP techniques.

• Complex algorithm introduction
• Neural network architecture overview
• Deep learning applications
• NN and Generative AI impacts and uses
• RNN, NLP, LLM exploration
• Demos: Neural Network applications & Generative AI in action

Assignment #3: Experimentation with Complex Algorithms
Dive into the world of AI experimentation using open and free-access models like MidJourney, Dallé, and OpenAI's ChatGPT. Showcase your unique creations and discoveries with these tools.

Bonus Assignment: Discover and evaluate an app that leverages GAI or Neural Networks. Analyze how the AI enhances user experience and the product itself. Highlight any unique design elements that exemplify its value.

Unlock the essentials to crafting exceptional user experiences for AI-driven products. Dive into UI/UX design, AI-powered recommendations visualization, explainability, and harness AI tools for your design arsenal.

• Prior task: Product review
• UI & Interaction design
• Patterns & frameworks usage
• Designing for explainability & transparency
• AI within the Toolkit
• Case study: AI recommendation visualization
• Demo: Figma & Adobe Creative Cloud techniques

Assignment #4: Experimentation with Advance Features
Dive into AI-driven plugin experimentation. Harness your creativity to design a prototype or wireframe integrating AI, ML, or GAI tech, all linked to your career path.

Empower yourself to create AI systems that are ethical, unbiased, and inclusive, aligning with societal values and user needs.

• Understanding biases in AI algorithms & data
• Ensuring fairness, diversity, & inclusivity in AI design
• Protecting user data & ensuring data privacy
• Compliance with regulations & standards
• Aligning AI systems with societal values

Assignment #5: Promote Ethical Data Use
Analyze potential biases in our subscription churn prediction experiment, identifying ways they could lead to harmful or unintended outcomes, and propose measures to ensure data-driven decisions are fair and ethical.

Develop the skills to analyze KPIs and user feedback to refine and achieve product goals, driving effective AI product development.

• Establishing measurable AI integration goals
• Identifying metrics for AI product success (KPIs)
• Conversion, retention, acquisition, engagement, etc.
• Designing for one vs. multiple metrics impact
• Incorporating user feedback, iterating for improvement

Assignment #6: Product Invention — Find a Problem to Solve with AI
Explore your chosen domain, identify a pressing user problem, and develop a concept for an AI-driven solution. Create a concise white paper outlining your product's functionality, expected outcomes, and the necessary requirements for implementation.

Enhance your AI product design skills by optimizing data structures, aligning user goals with AI features, and prioritizing user-centric design through personas and journey mapping.

• Role of information architecture in AI: Efficient data models and hierarchies
• Organizing and structuring data for AI applications
• User alignment strategies: Mapping user goals and AI features
• User personas and scenarios: Creating personas and journey mapping
• Case study: Analyzing IA in successful AI products

Assignment #7: Defining Data & Information Flow, Sourcing & Creating
Visualize the flow – transform your white paper and sketches into a dynamic data flow diagram, elucidating the origins of data and the means to source or generate it. Discover insights from illustrative examples for effectively orchestrating information flow in the age of technology and human collaboration.

Empower yourself to conceive, prototype, and validate AI-driven product ideas, expertly integrating AI solutions to address user needs while honing your agility in crafting interactive AI prototypes.

• Reviewing product concepts
• Applying AI to solve user problems
• Rapid prototyping methods with AI tools & platforms
• Use of Pencils in AI
• User testing, iteration, & building interactive AI prototypes
• Workshop: Prototyping & interactions

Assignment #8: Initial Feature Definition & Prototyping Core Features
Breathe life into your product concept by creating wireframes that illustrate core features, detailing user interactions, processes, and UI outcomes.

Craft intuitive user experiences for AI products and understand the pivotal role of UX design in enhancing user engagement and product adoption.

• Crafting AI-powered interaction user flows
• Designing seamless user experiences in AI products
• Case study: UX design's impact on AI product adoption and engagement

Assignment #9: Continue Developing Your Concept
Elevate your concept with engaging UI designs that emphasize UX, leveraging elements like color, imagery, iconography, and text to showcase the AI's user experience enhancements.

In this class, you'll gain expertise in navigating the AI product development lifecycle, devising effective strategies for AI solution planning and deployment, and implementing efficient management techniques for models and data pipelines.

• AI product development lifecycle phases
• Strategies for managing AI models and data pipelines
• Requirements for AI engineers in designs and prototypes
• Testing, refinement, and feature
• Workshop: End-to-end AI product design management

Unlock the potential of user research data to elevate your AI product design, encompassing research mastery, data integration, A/B testing, experimentation, and real-world case study applications.

• User research methods
• Using user research data effectively
• A/B testing and experimentation
• Case studies: AI product design with user research
• Workshop: Enhancing AI system with validation data

Assignment #10: Gather Feedback via Simplistic Methods
Engage friends or family to review your app, gather feedback on UX aspects, and categorize responses to enhance usability and identify critical improvements.

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

• Purpose & importance of design reviews
• Structuring effective design reviews
• Constructive feedback & iteration
• Design documentation & presentation
• Addressing stakeholder concerns

Assignment #11: Getting, Applying, and Refocusing Feedback Through Storytelling and Objection Handling
Prepare a presentation that outlines the problem, the opportunity, the solution, and a SWOT analysis that illustrates clearly the why and risks of not acting. Include a final slide that has visuals of the designed product denoting where the main AI-to-user value happens.

Gain insight into how to bridge design and technical teams through compelling storytelling and agile workflows, fostering seamless and collaborative product design journeys.

• Cross-functional collaboration: developers, data scientists, & stakeholders
• Bridging design and technical teams through effective communication
• Effective storytelling for AI product design
• Embracing Agile workflows for iterative, collaborative processes
• Incorporating feedback

Navigate the AI product design landscape, learn how to craft a compelling portfolio, and gain career insights from industry experts.

• Exploring AI product design role requirements
• Building a professional AI portfolio
• Industry insights and perspectives