Questions are the answer

If you start a project and immediately jump to a solution, you will only find more questions and problems. On the other hand, if you start a project with the right set of questions, the solution will invariably present itself. Questions reveal ideas that were previously hidden.

Learning to ask questions is about curiosity, rather than criticism, and it’s always a crucial skill to practice., And, in this moment when AI gives us access to all the information in the world, what now becomes most important is being able to find the right questions to ask to get the best results from AI tools. To use these new tools wisely, we’d do well to listen to Neal Postman, who writes,

“Wisdom does not imply having the right answers. It implies only asking the right questions.”

So how do you learn to ask the right question? I would recommend these three books.

Learning to Question
Paulo Freire

"Because, I repeat, knowledge begins with asking questions. And only when we begin with questions, should we go out in search of answers, and not the other way round."

"What does it mean to ask questions?" into an intellectual game, but to experience the force of the question, experience the challenge it offers, experience curiosity, and demonstrate it to the students. The problem which the teacher is really faced with is how in practice progressively to create with the students the habit, the virtue, of asking questions, of being surprised".

Critical Thinking
bell hooks

"The other challenge is to remember not to feel compelled to respond to every question. My training in academic traditions of public speaking taught me to always answer questions even it I did not know the answer; and if I did not know the answer, to act as if I did. What a horrid teaching practice!"

Teaching As a Subversive Activity
Neil Postman

"Once you have learned how to ask questions—relevant and appropriate and substantial questions—you have learned how to learn and no one can keep you from learning whatever you want or need to know".

"Prohibit teachers from asking any questions they already know the answers to. This proposal would not only force teachers to perceive learning from the learner’s perspective, it would help them to learn how to ask questions that produce knowledge."

Are questions the key?

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Make your own matrix

“This is your last chance. After this, there is no turning back. You take the blue pill, the story ends, and you wake up in your bed and believe whatever you want to believe. You take the red pill, you stay in Wonderland, and I show you how deep the rabbit hole goes. Remember, all I'm offering is the truth, nothing more." - Morpheus, The Matrix 

The world is a simulacrum, but if you can free your mind, you can play inside that perfect virtual simulator, and anything is possible if you can think the impossible. This is the brilliant concept behind the movie The Matrix. 

But what if I said to you that the new wave of AI LLMs allows you to create a virtual simulation like the Matrix today? If you can imagine what isn’t yet, this simulator will enable you to test out ideas without ever having to leave your desk. 

We have all read the stories about AI being the end of design and many other professions. These stories have all focused on the idea that AI can create outputs, screen designs, writing, photography, and apps. But what if we flipped the use of AI? Instead of looking for outputs to create a solution, what if we asked AI to offer inputs and virtual playgrounds to help us understand problems? 

For example, if you were designing a new software tool for a healthcare company to help people recover from a medical treatment, you could get an AI to simulate a 56-year-old male who had just had back surgery, and you could step into the matrix (via a Chatgpt prompt) and ask him any questions you thought would be relevant to making your software work for him. There are an estimated 1.2 billion webpages.  Somewhere in there is healthcare information that can help you simulate this person fairly accurately.

When you create this person in the matrix, consider imagining and adding details such as demographics, income level, geography, and cultural background. Adding these layers of interconnected information will provide you with better insights into the problem you are trying to solve. 

A simple design exercise would be to draw out a series of screens for your new health app. You could ask the 56-year-old man (created from an LLM matrix) what he thought of your screen designs and what the most critical information he would want to see. You could try out different information hierarchies to see which ones made the most sense to him.. Then, you could create another person in the matrix and try out your screen designs with a 26-year-old athlete recovering from an ankle sprain; what would she want to see? 

Because your matrix characters would have cultural and geographic context, your simulation could take into consideration a factor like the distance a person has to travel to a local physiotherapy clinic, and your simulation might make clear that the virtual therapy option would be useful for people who have to drive long distances. 

Each time you run a simulation in your matrix, you’re able to see the problem you are trying to solve with more clarity. You’ve honed what you’re making, and now, you can take what you’ve learned and try it out with real people who’d need this service or experts who have seen these types of situations. 

AI is great at summarizing data; it’s not always a hundred percent correct, but if you do enough matrix simulations with enough types of virtual people and imagine widely and thoroughly, you can figure out where it is going wrong. This is not a replacement for research with real people; it is an additional type of process, a method of inquiry that informs research and enables us to ask better-informed questions.

Build your own matrix today by talking to a taxi driver, a hospital administrator, or a new home buyer. Don’t imagine you’ll get exact answers, but look for the questions unlocked as you run through your matrix virtual simulation. Noticing the gaps and contradictions allows you to ask more insightful questions, which, in my experience, leads to better solutions.

As Morpheus says in the Matrix, "There is a difference between knowing the path and walking the path." AI tools will not magically solve design problems, but they can be used to expand your knowledge and free your mind!

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