How a need finds an answer
When you ask an assistant to find help, such as a plumber, a ladder or a tutor, it should search in widening circles: your own records first, then people you trust, then the open network, revealing less about you at each step. Most platforms today do the opposite and ask for your location, schedule and needs up front.
Most online searches for help start by uploading your private life: where you live, when you're home, what you're worried about. Those details become records on a distant server before you get an answer.
We propose that a personal assistant search the way people already do. It checks what you already have, asks people you trust, and only then goes wider, sharing with each circle only what that circle needs to know.
The hardware store full of shouting salespeople
Think of what happens when you type a simple practical question into a commercial search engine today. It is like walking into a corner hardware store for a two-cent rubber washer and being surrounded by twenty commissioned salespeople shouting about full kitchen remodels.
The store does not make its money by handing you the right brass washer in thirty seconds. It makes its money by auctioning your footsteps to whoever bids the highest to interrupt you.
Because the platform profits from attention bidding, the first five answers you see are rarely the most honest or neighbourly craftsmen in town. They are simply the firms that spent the most on advertising, and they recoup that ad spend by padding the bill once they step through your door.
Now contrast that noisy showroom with how a small-town librarian or a parish bulletin board works. When a parent asks the librarian whether anyone nearby teaches beginner piano, the librarian does not auction the parent's phone number to fifty music franchises.
She remembers that a retired school music teacher two streets over has a free afternoon slot. She checks with both sides, and introduces them only when both are happy to meet. Nobody's diary is sold, and nobody is hounded by unwanted calls for the next six months.
The natural geometry of human trust
Human beings did not evolve to live inside a single global crowd of strangers. We live inside overlapping circles: households, close friends, workshops, neighbourhoods, and wider communities of craft or interest.
The anthropologist Robin Dunbar showed that human social networks naturally arrange themselves into distinct layers of trust.1 They scale outward from an inner circle of five close confidants to wider rings of fifteen, fifty, and a hundred and fifty people. Each circle works because it carries a different habit of candour.
With the people in your own kitchen, you share raw context because they already know your life. With a friend of a friend, you share the practical question and leave the personal history at home. With a stranger across town, you share only the barest description of the job until both sides choose to meet.
What this means
Privacy works best as a series of doors that open gradually, matching how much you reveal to how much trust a relationship has earned.
Four rings, from your own shed to the open commons
We have been designing a different way for software to help a need find an answer. Instead of uploading your problem to a central marketplace, an assistant that works only for you on your own device looks outward in four concentric rings. At every step outward, it strips away personal detail, and it stops searching the moment a good answer arrives.
Ring 1: Your own memory and household
Before asking anyone else, your assistant checks what you already know and own. Perhaps you saved the card of a reliable appliance repairer two winters ago, or someone at home already has a free hour this week. Many everyday headaches vanish simply by searching your own notes on your own hardware first.
Ring 2: People you trust directly
If the answer is not at home, your assistant reaches out to the assistants of friends, family, or neighbours in your trusted circle. Even here, it never copies your raw diary onto their devices. It sends a polite, narrow question, such as whether anyone can lend a folding table on Saturday, and waits to see who is free to help.
Ring 3: Friends of friends and local co-ops
When your immediate circle is busy, the request steps out one ring further to friends of friends or a neighbourhood guild. Here, trust is real but indirect. Your assistant removes your name and personal backstory, passing along only the facts needed to spot a match. If a neighbour's cousin knows a retired joiner who repairs wooden window frames, their assistants introduce you only after both sides consent.
Ring 4: The wider network, stripped to the essentials
Only when local circles come up empty does a request travel to the open network. By the time it reaches this outer ring, it carries no personal identity at all. Mathematical rules for privacy budgets let your assistant measure and cap how much information leaves your device, so outsiders cannot stitch small clues together to map your life.2
How a student finds a piano teacher two streets over
Walk through how those four rings handle an ordinary request. Suppose Sam wants beginner piano lessons for his eight-year-old daughter on Thursdays after four o'clock, within walking distance of Elm Street.
Sam tells his personal assistant on his kitchen tablet. In Ring 1, the assistant checks Sam's own contacts and old messages first; nobody in the household book teaches piano. So Sam approves stepping outward to Ring 2 and Ring 3.
Sam's assistant does not post his daughter's name, age, school, or street number on a public web page. Instead, it crafts a short, unsigned note for the neighbourhood co-op bridge: "Looking for beginner piano lessons, Thursdays between four and six, ten minutes' walk from Elm Park."
Two streets away lives Mrs. Gable, a retired music teacher who takes three pupils a year. She told her assistant about an open Thursday slot for a beginner vouched for by two parish families.
Their two assistants compare notes across the bridge. Mrs. Gable's assistant verifies that Sam belongs to the neighbourhood association and shares a mutual friend on Oak Avenue, without ever seeing Sam's address book. Sam's assistant sees signed receipts from two local families confirming Mrs. Gable's decades of patient teaching.
Both assistants ask their humans first: "Would you like an introduction?" Only when both Sam and Mrs. Gable tap Yes do their names and phone numbers cross the bridge. No ad platform took a cut, and no data broker learned that an eight-year-old child lives on Elm Street.
Finding shared goals without showing your hand
Some needs are too large for one household to solve alone. Imagine ten families on the same street who each wish there were a safe walking group to bring young children home from school. Or picture eight rural clinics that want to pool an order for bandages so distributors do not overcharge them.
In both cases, a standoff often blocks action. Nobody wants to be the first person to post their family routine or clinic budget on a public board if nobody else joins in. Because everyone waits, everyone stays stuck.
Modern cryptography offers a graceful way out of that trap. Using privacy-preserving matching protocols, personal assistants can check whether neighbours share the exact same goal without exposing anyone's private list.3 If only two households want the walking group, nothing is revealed. Once ten households match, each family receives a private invitation to begin.
The same coordination works for family shops, independent pharmacies, and rural clinics. Six county clinics can compare monthly supply needs for sterile gauze and blood-pressure cuffs. By pooling orders, they secure fair wholesale terms without opening private patient ledgers to a broker.
Honest questions we still have to solve
When help travels through concentric circles, communities can meet most daily needs close to home while keeping a shared, checkable record of larger public commitments. Still, building this well raises hard human questions:
- Clues hidden in rare requests. Even an unnamed request for a rare medical specialist in a small village can hint at who is unwell. An assistant must warn you before a specific question leaves your trusted rings.
- Making sure newcomers are not left waiting. If answers flow fastest through established friendships, someone who just moved to town starts with an empty inner circle. Libraries, co-ops, and community centres need simple ways to offer newcomers a warm starting ring.
- Keeping everyday kindness off the scoreboard. Holding a ladder for twenty minutes or lending a cup of flour does not need a formal receipt. Neighbourly favours should stay informal while structured records track larger shared projects.
- Zero pressure to overshare. Being open about a project can help people find you, but no system should ever penalise someone who keeps their doors closed.
Help close to home
Think of a pebble dropped into a pond between neighbourhood houses. The ripples are strongest right where the stone touches the water, and they soften gently as they travel outward toward the far bank.
When our digital tools respect that same natural geometry, asking for help stops feeling like standing in a hardware store surrounded by shouting salespeople. Most everyday needs are met by people who already know and care about one another, and the wider world sees only what you freely choose to share.
Sources
- Robin I. M. Dunbar (1992), "Neocortex Size as a Constraint on Group Size in Primates," Journal of Human Evolution, 22(6), 469–493. ↩
- Cynthia Dwork and Aaron Roth (2014), "The Algorithmic Foundations of Differential Privacy," Foundations and Trends in Theoretical Computer Science, 9(3–4), 211–407. ↩
- Michael J. Freedman, Kobbi Nissim, and Benny Pinkas (2004), "Efficient Private Matching and Set Intersection," in Advances in Cryptology — EUROCRYPT 2004, Lecture Notes in Computer Science, vol. 3027, 1–19. ↩
