A place to begin with AI

What is AI?

Artificial Intelligence isn't a single technology. From traditional computing to the peaks of modern innovation, AI encompasses any system that mirrors human-like thinking.

AI spans a range of technologies, from traditional rule-based systems for specific tasks to generative AI, which adapts and creates content like improv. Machine learning (ML) identifies patterns in structured tasks, while deep learning uses advanced neural networks for complex applications. Transformative models enable human-like responses by processing data in parallel. Yet AI remains a pattern recognition tool rooted in past data, not a future predictor.

• AI is not just ChatGPT

• Traditional AI is like a Play, Generative AI is like Improv

• Machine Learning is not the same as Deep Learning

• Attention is All You Need

• ChatGPT is like type ahead search
  

How does AI work?

Every digital interaction leaves a trace, like footprints in the sand. When you search online, post on social media, or shop for groceries, you're contributing to an endless ocean of data. This vast sea of information forms the foundation of modern artificial intelligence.

AI generates human-like responses by compressing vast datasets into patterns, akin to a lossy JPEG. Large Language Models (LLMs) map relationships through neural networks, enabling tasks like text generation, but rely on biased historical data, limiting innovation. With quality training data dwindling, approaches like Retrieval-Augmented Generation (RAG) and specialized smaller models are emerging to enhance accuracy. AI’s potential is vast but requires human creativity and oversight to realize responsibly.

• LLMs are like a JPEG of the Internet

• Where do LLMs store data? They don’t

• AI Reflects Our Biases

• Garbage In, Garbage Out

• AI is a time machine looking back, not forward

• AI aren't getting much better, just more specialized
  

uxGPT: Mastering AI Assistants for User Experience Designers and Product Managers

RECOMMENDED REsource

An essential read with practical strategies to harness AI Assistants to plan and brainstorm user experience and product management activities. By mastering these prompts within the design thinking process, you'll unlock new ways to streamline workflows and generate innovative solutions.

How to approach AI?

For every headline celebrating AI's capabilities, there's another warning about its limitations. But here's a simpler truth: AI works best not as an oracle delivering answers, but as a diligent partner offering possibilities.

Approaching AI requires treating it as a collaborative tool, not a directive force, leveraging its strengths in idea generation, refinement, and cognitive assistance while relying on human judgment for the "messy middle." AI excels at brainstorming, pattern recognition, and narrowing skills gaps but depends on clear framing and context to be effective. It acts as a thought partner, providing suggestions and feedback rather than definitive answers, and is best suited for hot starts and polish rather than complex, nuanced tasks. To maximize its value, integrate AI as part of iterative processes, ensuring it complements human creativity, decision-making, and design.

• AI is a Suggestion, Not Direction

• Gen AI Helps with Hot Starts and Refinement

• Prompt Engineering is Coding in your Natural Language

• Treat AI as a Thought Partner

• AI first Products will work differently
  

What does AI mean?

The AI age brings us choices – countless decisions about how to harness this technology that seems to evolve daily. From doctors analyzing medical scans to writers crafting stories, AI reshapes not just what we can do, but how we do it.

AI offers both promise and challenges, shifting from use-case identification to solving broader business problems while prioritizing augmentation over automation. Human-centric AI enhances, rather than replaces, human expertise, with liberal arts skills crucial for articulating AI's potential. Efficiency gains risk driving consumption, while generative AI may thrive as a component in workflows. Viewing AI as "Augmented Intelligence" reduces risks, amplifies human capabilities, and ensures better outcomes.

• AI is Hype… and Hope

• AI Has an “Articulation Barrier”

• AI Efficiency May Lead to More AI Consumption

• The Automation of Automation

• AI is not Artificial Intelligence
  

About AI Demystifying

You don’t have to be an expert to understand AI, just like you don’t have to be a mechanic to drive a car.

But it can be challenging to sort through the noise - and we need cartoons in our heads about how technologies work.

AI Demystifying is a place to begin sorting through the hype, unpacking foundational concepts and developing frames of reference for AI.

Process is a set of tools, not rules.

AI Demystifying is another UX How Tool from Method Toolkit LLC.

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About UX How and T. Parke

UX How is a set of UX & Product Design “How To” sites with insights, resources, and blueprints for Design, UX and AI.

T. Parke is the Director of UX How with prior experience at ESPN, Disney, and Alaska Airlines. He has previously been a design leader on projects for Rolling Stone, Microsoft, Nickelodeon, and Marvel.

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