Lateral AI #001 — What If AI Couldn’t Answer? From Recommendations to Learning Discovery

AIYING • LATERAL AI #001

What If AI Couldn’t Answer?

Change the thinking. Discover the possibility.

When AI gives you more options, do you always gain more clarity? This first Lateral AI experiment explores what happens when we temporarily remove the answer.

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In this Thinking Lab

1. The familiar situation
2. The thinking concept: PO
3. From provocation to possibility
4. Try the prompt
5. Run a small experiment
6. Reflect and apply

1. More recommendations, less clarity?

Imagine you are choosing a course. You ask AI, “Which course should I take?” It produces an impressive list. You compare subjects, certificates, formats, and fees. Yet you still cannot decide.

The hidden assumption is that you already understand your learning need well enough to request a recommendation. Perhaps the missing step is discovering what you actually want to become capable of doing.

This is an illustrative scenario, not a reported case study.

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2. The thinking concept: PO

In PO: Beyond Yes & No, Edward de Bono presents PO as a tool for moving beyond established patterns. A provocative statement becomes a starting point for exploration: we temporarily suspend immediate judgment and look for where it can lead.

For this AIYING adaptation, our provocation is:

PO: AI cannot recommend a course.

We use this temporary restriction to explore another role for AI. After generating possibilities, we return to judgment and test their usefulness.

Source and adaptation: PO is de Bono’s concept. The course-selection scenario, prompt, and experiment below are contemporary AIYING applications.

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3. Make the thinking movement visible

1. Remove recommendations temporarily. What useful assistance remains?
2. Extract a principle. AI can help clarify the need behind the request.
3. Explore the difference. Instead of comparing courses, investigate the task you want to perform.
4. Develop a possibility. Design a small trial task that reveals what you need to learn.

Suppose your goal is to create a simple personal website. Before enrolling, you attempt a basic page. You discover whether your main difficulty is writing, visual design, or building the page. That evidence can make your next learning choice more specific.

The discovery: A useful first output could be a learning experiment rather than a course list.

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4. Copy and try this prompt

I am considering taking a course, but first help me clarify my learning need.

For now, do not recommend courses.

Ask me one question at a time about:
- What I want to become capable of doing.
- A real situation where I would use that capability.
- What I have already tried.
- My available time, resources, and constraints.

After no more than five questions, summarize my goal and any assumptions that remain untested. Ask me to correct your summary.

Then help me design one small task I can attempt in 20 minutes using resources I already have. Define an observable result and what to notice when I get stuck.

After I report the result, help me identify my learning gaps. Distinguish evidence from guesses. We can then consider whether a course is appropriate.

Adapt the time limit to your situation. If you later compare actual courses, verify their current syllabus, fees, availability, and entry requirements directly.

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5. Run a small experiment

Use the same learning goal in two separate AI conversations.

• Conversation A: Ask directly for course recommendations.
• Conversation B: Use the question-first prompt above and attempt the task.

Compare the results: Can you state a specific capability you need? Can you name a gap supported by your task attempt? Do you have a feasible next action? Record a concrete example for each answer.

Notice what each approach contributes. This personal experiment can inform your next step; it does not establish that one method is universally better.

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6. Reflect and apply

• What assumption did you discover in your original question?
• How did removing recommendations change the conversation?
• What did the task reveal that an AI answer alone could not?

Try the same movement when choosing a tool or planning a personal project: temporarily remove recommendations, clarify the purpose, and design a small test.

Share your discovery: What happened when you asked AI to help you find the question before providing the answer?

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Lateral AI explores Edward de Bono’s thinking concepts through everyday AI situations, with explicit movement and practical experiments.

Conceptual reference: Edward de Bono, PO: Beyond Yes & No, revised Pelican edition, 1973.

AIYING — Accomplishing with AI
By Ravindra Dastikop