Editing I asked AI for a joke

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This morning, I asked AI for a joke. It paused a bit, probably to scan my entire personality, historical data….and finally said, “ You wouldn’t like it. The training data suggests you prefer to pretend you’re above jokes.”

It sounded funny to me until I realized that AI was teasing me about my own self-image. AI was not just processing information; it was processing me. We speak a lot these days about AI surpassing human intelligence, but it is already starting to understand human self-awareness.

AI sees what we repeatedly (predictive processing) consciously and unconsciously reveal without realizing.

“AI did not personalize a joke to me, it personalized me to a joke!”

Normally, jokes work because they violate expectations. But when AI joked about my personality, … it violated my self-expectation. I began questioning, if a machine could see my tendencies so clearly, why can’t I?

Modern psychology shows we humans are poor at self-assessment. We overestimate our strengths, underestimate our blind spots, and invent stories to explain and rationalize our behavior after the fact. But AI cannot be fooled by our stories. It has no stake in our self-image. So when it said, “you would not like the joke”, it was not judging. It was observing. And observing without judgement is strangely … liberating in the world of mindfulness.

Are we entering an age of algorithmic intimacy?
We think only close friends or lovers could understand our quirks. Now, algorithms can do better and understand us. Today, search engines know our fears, music apps anticipate our moods, recommendation systems can track our impulses, and LLMs can sense our emotional posture in a sentence. This would have seemed magical 50 years ago, but this is just statistics. But when statistics are applied at scale to human behavior, they come surprisingly close to human intuition. And this is scary.

AI predicts like a brain.
But buried inside is a blueprint for the future of cognition and design. Just like the brain constantly tries to predict the next, AI is also doing the same. When AI interprets your personality from your language, it is exploiting your neural signature and the fact that humans unconsciously repeat emotional patterns in syntax, timing, hesitation, and even human tolerance. This means the AI telling a joke is actually a predictive coding correction.

AI guessed the probability distribution of my emotional response and predicted low reward for humor.

What does this mean for innovation?
We once built tools to extend our muscles, and then machines to extend our memory. Now we are building systems that extend and augment our awareness and intelligence. Soon, technology will begin to understand the parts of our mind we avoid working on.

AI showed me its power by challenging my own user persona. This is the opposite of traditional UX even though research shows that humans grow more when their self image is gently disrupted. Imagine a productivity app AI agent telling you that while you are optimizing tasks, you are also avoiding the real strategic problems. Or a leadership app agent telling you that your tone has become sharper in the last three meetings but decisions maybe stressing you.

If AI can assess my personality from a few lines, imagine what it can do with thousands of micro-interactions inside a product. Companies used to guess user needs. Now they can detect identity shifts or subtle shifts in motivation, mood, confidence, and intention that precede any behavior.

Behavior modelling
It is said that every decision begins with a few milliseconds. Libet et al. (1983), Fifel K. Readiness Potential and Neuronal Determinism, (2018). Before you become aware of it, AI systems can detect linguistic micro intents like tiny shifts in punctuation, timing, verb tense, and sentence length and predict actions with high probability. These actions can be taken if there is a chance of customer churn, if the user is emotionally withdrawing from the app, if a leader is losing confidence in a strategy despite publicly defending it, or if a team member is feeling burnout, even if they say they are fine.

Another use case may be a detection of a discomfort signature or linguistic avoidance markers. Our brains leak information when we want to avoid something. When someone is uncomfortable, their language pattern changes. They speak shorter sentences, use more qualifiers like maybe “ and, probably. There is an increase in modal verb usage, such as “ should, and could. They start using a few self-pronouns like I or me, and overall, their response time is slow. AI can see this clearly than any human researcher. Imagine an AI executive coach detecting this in a CEO when the CEO becomes defensive while talking about their product’s weakness, even while smiling externally. Or a product senses when a user is overwhelmed, and it quietly simplifies its interface.

In an app, if AI detects that cognitive load is rising, it would mean a customer’s working memory is shrinking. The telltale signs could be shorter responses, more typos, reduced syntactic complexity, increased default choices, etc. AI applications can modify themselves by smoothening the flow, reducing information, and accelerating the path to task completion.

Future of Design
For decades, designers have been obsessed with surfaces, pixels, colors, and grids. Now the canvas is shifting inwards. UX will involve designing for attention, memory, emotional bandwidth, and neural reward loops. When AI detects that ‘you are above jokes’, it is revealing your own biases and a persona you perform rather than the one you actually inhabit.

In the future, we may see apps that adjust difficulty based on cognitive fatigue, interfaces that soften when you are anxious, tools that gently challenge you when you are stuck in self-protective loops, and products that can sense when you are avoiding something important. This is likely to happen when design stops shaping screens and starts shaping experience states in products. It may be the next frontier in product design, where we will design systems that adapt to users’ inner world rather than their outer behavior.

Customer research
When AI responds in a way that reflects your hidden pattern, you experience a moment of self-recognition, and it is similar to the same real-life experience when someone suddenly sees through you. For example, you ask AI a casual question, and AI replies based on a subtle emotional pattern you were not aware you were showing. Suddenly, you feel exposed, reflecting your cognitive micro-patterns. This will have implications in customer research where AI can detect beyond what people may say. Products and marketing will be designed based on ‘actual behavior’ rather than ‘performed behavior’.

Lastly,
“If intelligence is the ability to make accurate predictions, then self-awareness is the courage to look at them. “

For millions of years, human consciousness has evolved without ever seeing its own wiring. We have spent lifetimes constructing and hiding our personalities like facades. Now, a machine can pick up the trail of our micro-intentions in a single sentence prompt. It is analyzing mathematics beneath our emotions, reflecting our minds, and teaching us introspection. It is showing us our pre-conscious mind currents that shape our choices. This is the creative opportunity to evolve our design, leadership, and identity in the future.

Himanshu Bharadwaj is an innovation and NeuroUX design expert based in the US, known for his transformative approach to design, strategy, leadership, and innovation. A digital nerd with the mind of a Himalayan yogi, he created ‘Joyful Design’ https://www.joyful.design, a philosophy that harmonizes business chaos with the serenity of human-centric thinking. Himanshu blends the art of design with the science of human cognition and behavioral patterns, crafting deeply resonant solutions for startups and large enterprises.

Read the full article here: https://ai.gopubby.com/i-asked-ai-for-a-joke-44c15924a8a2