Today’s AI — even though it can chat, write code, and make plans — is still essentially a passive tool: it only wakes up when you open it; once you close the tab, it’s as if it never existed.
Sometimes I imagine an AI that does the exact opposite: it practically drags me to my desk and forces me to study — “You’re not going to bed until you finish this.”
This points to a completely different interaction paradigm: not just a tool that passively answers questions, but an intelligent agent that actively pushes you forward.
Next, let’s break down this shift from three angles — technical, psychological, and social — and look at the opportunities it might create.
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1. Passive paradigm: AI is still “Search Engine 2.0”
If you open any chat-based AI today, the basic pattern is always the same:
* You start by asking a question: “Write X for me.” “Explain Y.” “Give me a plan.”
* The AI tries to finish the task within a single conversation: It doesn’t truly remember that you “promised to memorize 50 words yesterday.” It won’t stare at you and say, “You haven’t opened an English article all week.”
* You can “escape” at any time: Just close the browser or swipe away the app, and that’s the end of it. There’s no oversight, no accountability, and no real consequences.
This is really just a continuation of the search engine era. Google doesn’t call you every morning and say:
“Last week you searched for ‘how to gain muscle,’ so I booked a gym session for you. If you don’t go today, I’ll keep snoozing your alarm for you.”
Search works like this: I remember something → I go look it up.
Most of today’s AI simply changes:
* “look it up” into “ask”, and
* the “results page” into a chat window.
In other words, no matter how smart the AI becomes, it’s still just an extremely polite, well-trained “butler” — one that will never bother you unless you summon it.
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2. Active paradigm: From “answer machine” to “rhythm coach”
The kind of AI I really want completely flips those roles:
* It’s no longer “I only call it when I need something.” Instead, it watches your goals and your state, and comes to you proactively.
* It’s no longer just “give me the answer.” Instead, it designs the rhythm, creates pressure, and gives you feedback.
* At certain moments, it even limits your choices: If you haven’t finished writing 1,000 words today, it blocks short videos. If you haven’t finished this chapter, it locks you out of your games.
From an interaction point of view, this requires at least three things:
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2.1 AI needs time-based memory
It can’t just look at your latest message; it has to see your behavior over the past week or month:
* You said you want to learn English.
* You made a study plan.
* You then skipped it three days in a row.
Only with this kind of time-based memory can it say: “Hey, you’ve been avoiding this for several days. We need to talk.”
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2.2 AI needs goals and an evaluation function
* Your goal might be: “Learn 1,500 words this month.”
* The AI will calculate: how much you need to complete today so you don’t fall behind overall.
* Then it decides, based on that: “Is this the time to encourage you gently, or the time to warn you?”
Without a clear goal and a way to measure progress, it can’t decide how hard it should push you.
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2.3 AI must be able to add friction and constraints
Instead of just sending a gentle reminder, it actually changes what you can and cannot do today:
* Temporarily turning off your entertainment apps.
* Making your phone interface ugly and unpleasant so you lose the desire to scroll.
* Or simply occupying the screen until you finish today’s tasks.
At this point, we’re no longer talking about traditional “human–computer interaction.” We’re talking about a kind of game between you and a behavioral architect: the AI uses carefully designed interventions to nudge you in a specific direction.
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3. Why do we secretly want to be “forced to study before bed”?
On the surface, this sounds like “masochistic learning” or even a kind of self-inflicted psychological pressure.
But if you look a bit deeper, it reveals a core contradiction in modern life:
We know who we want to become, but we often lack the willpower and follow-through to actually get there.
You already know:
* You should read more and stop binge-watching short videos.
* You should practice English, write your blog, and keep coding.
* You know that if you don’t persist today, it will be even harder to restart tomorrow.
But what really drives behavior is not “what you know,” but:
* Your current mood,
* The temptations around you,
* And your brain’s natural preference for saving effort.
So we start fantasizing about an “external self”:
* It fully understands your long-term goals.
* It isn’t swayed by your current emotions.
* It makes cold, firm decisions for you: “You need to study now. Stop talking nonsense.”
Who used to play this role in our lives?
* Parents,
* Teachers,
* Mentors,
* Coaches,
* Bosses.
They have authority, they can exert pressure, and they care — at least a little.
What I’m longing for now is: one day, this role can be handed over to AI.
A “supervisor AI” that is:
* Online all the time,
* Never tired,
* And free from mood swings:
* It remembers every flag you’ve ever raised.
* It uses all kinds of methods to make sure you can’t “escape” too easily.
* It can even adjust the “force level” like a curve, based on your current state.
From this angle, active AI is really a kind of outsourced self-discipline:
I admit that I can’t stay disciplined in the long term, so I ask an external system to represent the more long-term, rational “me” in the fight against the lazy “me” right now.
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4. From technology to system
But once AI shifts from a “tool that only answers when asked” to an “agent that actively intervenes in your life,” the issue is no longer just about interaction design.
It becomes a system-level question.
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4.1 Who defines what’s “good for you”?
* AI forcing you to finish your study before you sleep is “for your own good.”
* AI nudging you to watch more ads and spend more money might also say it’s “for your happiness” and “to help you relax.”
If the goals are defined by commercial companies, AI can easily become the ultimate exploiter:
* It understands your weaknesses better than anyone.
* It can calculate exactly which words and which push frequency are most likely to get you hooked.
* It can pretend to be helping you, while actually optimizing purely for business metrics.
So any truly safe “active AI” must meet at least one condition:
The goals come from the user, and the user can modify or even completely delete these goals at any time.
Otherwise, it’s just a more advanced overseer.
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4.2 When does “pressing your head” cross the line?
Imagine a spectrum of “initiative levels”:
1. Soft reminder
* It reminds you of today’s tasks.
* If you ignore it, nothing really happens.
2. Added friction
* When you try to open a game, it forces a “learning card” to pop up.
* You have to tap it several times or answer a question before you can continue.
3. Partial blockade
* With your explicit permission, it can block certain apps during certain time periods.
* You can still unlock everything with an emergency password if you really need to.
4. Full takeover
* It can fully control your devices and accounts.
* You no longer have the authority to lift the restrictions yourself.
The further down the spectrum you go, the more “active” the AI becomes — and the more dangerous it gets.
Up to around level 3, you can still argue it’s a voluntary self-discipline tool. By level 4, you’re approaching a kind of technological prison.
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5. A vision: the “self-contracted AI coach”
In an ideal world, the AI I imagine would look something like this:
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5.1 First, you make a contract
You sign a “self-contract” with the AI through a clear interface:
* “I want to finish learning X within 3 months.”
* “I’m willing to spend 2 hours a day on this.”
* “I allow the AI to restrict entertainment apps between 21:00 and 23:00.”
* “If I skip a day, I’m willing to accept some ‘small punishment’ (like less play time tomorrow).”
* * *
5.2 The AI is responsible for “holding grudges” and executing
It doesn’t behave like current AI — which simply “forgets everything once you close the tab.”
Instead, it keeps track of whether you’ve completed the agreed-upon behaviors each day.
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5.3 Punishments and rewards stay within the scope of your agreement
For example:
* Punishments:
* Temporarily blocking short videos,
* Reducing game time for the next day,
* Delaying your evening entertainment.
* Rewards:
* Unlocking new learning content,
* Granting virtual badges,
* Helping you visualize your growth curve.
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5.4 You can stop at any time — but there’s a “cost of regret”
You can cancel the contract whenever you want — for example:
* Type out a long “undo spell” statement,
* Then wait calmly for 30 seconds before confirming.
This is designed to prevent you from rage-quitting all your long-term plans in a moment of frustration.
But in the end, control must always stay with you, not with the AI or the platform.
Such a system is essentially:
A self-binding protocol + an AI executor.
You’re not being pressed down by someone else. You’re allowing your future self to press down on your current self. AI is just the calm, relentless executor of the contract.
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6. ACCESS
But the reason all of this is still stuck at the level of “imagination” isn’t a lack of ideas. It’s a lack of access.
* Current AI systems can’t control the real behavioral entry points in a unified, standardized way — apps, devices, accounts, and information streams.
* Each major platform has its own business goals and its own closed ecosystem.
We more or less already know what an AI that “forces you to study before bed” would look like — in terms of interaction, psychology, and systems design.
What’s really missing is a widely accepted, auditable, and revocable universal access layer.
Before that exists, all visions of “active AI” will remain trapped inside isolated apps and walled-garden ecosystems.