Origins of Beth’s System

Ken Green had used compatibility matching to help put together teams of people to work in his business enterprises, but had never taken it further. In his books, however, he had written about using it to change the world. Despite Ken’s early interest in this subject he had done relatively little to implement it. This would change very soon, when he got the help of his ten year old daughter, Beth.

Briefly in the Green Private School, Beth had since gone back to having private tutors. As well as working with some of the well-educated women who lived in the building, Beth also studied with her father. Ken taught Beth mostly math and computer science, though he was not sure how much longer he could stay ahead of her.

Occasionally the math lessons detoured into physics, since so much of mathematics had its origins in physics. One day he was explaining to her the very mathematical theory from physics called wave mechanics. Ken happened to mention to Beth at this point that for the invention or discovery of wave mechanics the physicist Louis de Broglie received the 1929 Nobel prize in physics.

“It is so mathematical, he should have received the Nobel prize in mathematics for it instead, shouldn’t he, Daddy?”

“Well there is no Nobel prize in mathematics, Beth.”

“That’s silly. Why not?”

“Well, Alfred Nobel, the man who donated the money for the prizes apparently didn’t think mathematics was as important. He left out biology, too, though he included medicine.”

“What about computer science?”

“The early mechanical computers were almost unknown or the subject of jokes or annoying office machines at best. Nobody thought they would ever be important, and Alfred Nobel didn’t either.”

“Are all Nobel prizes forever to be determined by the prejudices of one man, Daddy?”

“No, much later, in the 1960s sometime, the national bank of Sweden donated the money for a Nobel prize in economics.”

“Well somebody should donate the money for a Nobel prize in mathematics.”

“Well, I’m trying to fund the creation of a university, Beth.”

“Oh, I didn’t mean you, silly. The Nobel prizes are paid out on the interest from the original amount of money that the guy left in his will, right? They are about a million bucks, Daddy, so it would take at least 10 million to fund a new one, and probably more like 50 million, right? I don’t think you have that kind of money.”

“Beth.”

“You do?”

“Well, the university is going to cost me at least 100 million, and probably a lot more. A lot more.”

“Holy Cow, Daddy. Did you inherit this, or get it doing business, or something?”

“In business.”

“If you are one of the important business kind of guys with that much money, how come you have so much time to spend playing with your children?”

“I would let it all dribble away before I gave up a single minute playing with my children. Especially you.”

“Oh, Daddy. So, here’s what you do, Daddy. Put your loose change in a piggy bank. You probably have a lot of loose change. If you put only the tiny bit you can afford without hurting your university or family into a piggy bank, then maybe you can fund a Nobel prize in mathematics some year.”

“Yes, I guess that would work. Maybe I could do computing science as well. I could probably put together 100 million worth of loose change in 10 or 15 years.”

“Daddy, you are teasing me!”

“No I’m not, Beth.”

“How much money do you have, anyway?”

“Well, lots.”

“Are you a billionaire, Daddy?”

“Please don’t tell anyone, Beth, but yes, I am.”

“Wow, rich Daddy! OK, I won’t tell. I guess that’s how you can afford to have dozens of children.”

“Beth, I have hundreds of children.”

“Oh. Oh, yeah, I guess I knew that. So many leave with their mommy’s I forget. Daddy, you are a very unusual man!”

“I am a very fortunate man to have so many children, Beth, it is a great honour. But I think if I’d stopped after the first, I would be almost as happy.”

“Oh, Daddy. You are so nice. Well, if you are rich rich rich, I think you should start that piggybank and try to setup those two new Nobel prizes within a couple of decades. OK?”

“OK, I promise. But you have to try to win one of them, alright?”

“Well, maybe, but I think my field is social technology. I guess you can’t endow a prize for a discipline you almost invented, especially when nobody seems to be doing it. Let’s revisit that question in a decade or two, OK, Daddy?”

“Sure thing.”

Beth wasn’t quite sure he was serious, but Ken did did get his office staff to put together a trust fund, untouchable except for donations to the Nobel Foundation, arranging to put a some amount of money in it regularly. How much would depend on the available resources his corporation had, but money would collect in that fund at a rate which would indeed allow him to establish two new Nobel prizes with a few years.

Ken and would live up to promise he had made Beth. He kept promises made to his kids. Someday he would endow two new Nobel prizes in her favourite fields.

But Beth and her father did not only talk about such subjects. Beth’s father spent a lot of time trying to explain life to her. Not sex, life. Actually he seemed to spend a lot of time trying to explain life to everybody, but without much luck. Beth felt she understood, but nobody else seemed to get it, and she could sense his frustration.

“Poor Daddy. Nobody really understands, do they?”

“No, not really”, Ken said, rather sadly. “Nobody but you, Beth.” As he said this, Ken realized for the first time that Beth really did understand, that his ten year old daughter was the only one who did. Even mathematical sociologist Edna Stilling didn’t understand everything, but Beth did. When she had idly commented that her field was social technology, she meant it. Beth had read and absorbed her father’s books, and absorbed even more from all her talks with him. Edna knew the sociology and some math, but Beth knew more math and also what kind of computer programs would need to be created in order to actually make it happen.

“Beth. Darling. You do understand, don’t you?”

“Yes, Daddy, I am pretty sure I do. We’ve talked about it a lot, haven’t we, and it all made sense to me.”

Ken thought back over his conversations with the lovely little genius he and Sarah had produced. “Yes, yes, I believe you, I am sure of it. We have talked a lot, and what you’ve said made sense too. Oh, Beth, it is so wonderful to have a daughter like you.”

“Thank you, Daddy.” He always loved to hear these words.

“So what should I do?” He often sought her advice.

That advice was rather oblique, today.

“Well, I think we make plan to offer a service of some sort. We need to devise some genuine solution, to use your phrase, and work on it, probably with hired help. Whatever we do should be a unified treatment of various problems done with the help of a team of committed experts. I think you should hire some computer applications specialists, you know, people who actually do things with computers? And then some computer scientists, algorithm people, to advise them, and maybe a couple of mathematicians to advise the algorithm people. Are you with me so far, Daddy?”

“So far, I suppose. I can see this as a project. So if we can find some people to get started with, then what?”

“Then we make them understand, Daddy. You do what you usually do. You know. When you hire them, hire lonely single women around thirty or so, with no kids. Some of them will stay here and have babies with you, then there will be computer and math people for you and me to talk to.”

“Uh, Beth. You are not supposed to know about that.”

“Oh, Daddy, silly, I may be a kid, but I’m not an idiot. I don’t know exactly what you do in bed with the women, other than, you know, that, but something makes them want to stay and talk with us. Whatever you do, I know you get interesting and nice women for our building by going to bed with them and giving them babies. So do that with the computer and math people, OK Daddy? Bring them here, make them love you and have your children, and meanwhile we’ll work on them, we’ll get them to understand, slowly. “

Ken groaned theatrically, but promised to do his part, however onerous it would be. Beth was right. But then Beth was always right. So Ken contacted Beth’s mother, Sarah Rivers and outlined the plan. She grumbled and fulminated about over-educated bitches trying to steal her man, but she got to work. Actually she liked the idea, and was proud of her little girl for thinking it up. Sarah didn’t like new women coming for Ken’s bed, but she liked doing anything that was a positive step towards making his ideas a reality.

All three of them then tried to find the names of possible candidates and Sarah worked out the details, ordering the new computer and networking equipment Ken wanted. Meanwhile Beth and Ken worked hard to take his vast scheme and extract from it a plausible project that hired experts could help with. The project didn’t have a name or clearly spelled out purpose, but both Beth and Ken knew what it was.

It proved impossible to find more than a few suitable candidates, so job offers were sent out to all of them. Not many accepted, just seven. These newly hired employees included three research oriented computer people with doctorates and two professional mathematicians with a very strong background in computer science. There was one doctorate level computer hardware specialist with a thorough background in software as well, and a pure software person, an algorithm implementation expert. A small number of less qualified people who seemed exceptional were also hired, including two good programmers, a hardware technician and a computer communications expert.

A few female employees of Green Eye Software were seconded to work with the new experts. After the newly imported experts had a day to recover from their flights, they met with the local software people, and were briefed by an odd management team consisting of a fiftyish man, an attractive woman in her late twenties, and a ten year old girl.

“Thank you for coming. I am Sarah Rivers. I’ll be handling logistical matters. You have a rough organization chart for this computer division in front of you, and you’ve been issued name tags. We can all get acquainted later. Briefly we have here three scientists from back east, four local people who seem very good, and a few software people from a local company. Ten of you altogether. You’ve probably noticed that all of you are women. This building has a large number of vulnerable young women and many children in it, so we have decided to forestall any possible problems by allowing only women in the building. We’ve tried to keep Mr. Green out, but he owns the building and pays for everything, so we have to let him in. So far he’s the only exception and we watch him like a hawk.

“The project requires work in the building, so we’ve hired only women. Now of course if you are married or living with a boyfriend you’ll have to live outside the building somewhere, but if you happen to be single or are seeing someone but don’t live with him, then you might want to live here in the building with us. In that case we can offer you one of the nice rooms we call visitor’s rooms, rent free. That applies both to people from out of town and local people. Whether you live here or outside the building we will provide food for free if you eat here with us, though you might decide to eat elsewhere. But again because of the children, this building has a firm policy of no alcohol and no smoking in the building. No drugs, too. If you needed to drink you can temporarily leave the building, of course. The project will run at least one year, so if you don’t mind these restrictions it would save you a lot to live here. We do have a nice swimming pool and gym, if those amenities would attract you.”

“So, if I move out of my home, which costs me a fortune, I could live here rent free and eat free too, for at least a year?”, a programmer named Katrina asked.

“Yes. We have storage rooms if you have furniture or other belongings which would need to be stored and we would cover your moving costs.”

“Why would you go to all that expense?”

“Oh, to provide a collegial atmosphere, to get you to hang around and put in longer hours, if you want to, no obligation, to get to know you better, to encourage networking amongst you. To better exploit you!”

“Ah!”. There was some laughter.

“So, what do we do?”, another person asked.

“Well, we want to provide some new kinds of services for people, what Ken Green here calls Social Technology. We want to design and test software to provide these services. We need to write software to simulate users. I’m told we want some kind of expert system with a mathematical basis. Apparently this is going to take massive amounts of computer power, so we well need powerful computers, which we will provide. Or to put it another way, I don’t know.

“But I do know where the systems are, or will be and what our initial base of users will be. We have three private schools each with gifted students and well-chosen teachers. Each school has a big computer to do serious processing in support of this project. We are starting a college, and hope it will become a university, centered around this building. Two communications facilities are planned. And this building itself has a large computer system involving several mainframe computers used in Ken’s research. Later whatever service we prototype hear will be offered very widely. Nobody here has any real understanding of what Ken wants todo, except possibly our daughter Beth, who has rather unique talents.”

“Uh, yes, so, what do we do?”, the questioner asked again.

“OK. Well, there are two preliminary tasks. One is to grow. I’d like your help in hiring a few more of you. The other is to examine our rough outline of the project and see how you might fit into it. We won’t be micromanaging anything. We want you to isolate tasks that need to be done by somebody, not necessarily yourselves. I’m handing out this project description as a starting point. The more mathematical people will work with Ken and Beth. They will tell you what they think they want, and you can explain what they should want. You should look at everything, drink a lot of coffee, talk a lot, and try to codify your own future tasks. Ken will veto things he doesn’t like, but we might put together an appeals process for this.”

“How do we start?”

“Let’s go for coffee. We also have danish!”

And they did. Coffee and danish being the staple food of computer people, they thrived. Ken and Beth explained as much as they could, then took a party to see the school’s computers and communications systems, then to see the building’s more impressive machines.

One mathematician was Dr. Helen Rollins. She didn’t care about the machines, and just wanted to look into the guts of the matter. “Well”, Ken explained, “you know the classical assignment problem. There are N jobs for N people and you want to produce the best assignment of person to job. We are more interested in multiple assignment problems. Suppose, just for example, that each person being assigned a job also needs exactly one spouse and exactly one best friend of the same sex. That’s not the same kind of problem, now is it?

“No, I would say that’s much harder, NP-complete, like the travelling salesman problem.”

“Just so. I think I have a proof of that. Now suppose we wanted to provide approximate solutions to that very hard problem. Fast. For vast numbers of people. Could we do it?”

“Ouch. OK, you have a legitimate task that would take me the rest of my life to deal with. Neat. Can you hire me a couple of colleagues? Someday I’ll need to know the actual problem, instead of the spouses and best friends example, but for now I just need an office with a computer.”

“Can you get me a list of suitable people? I might add to it, then I’ll try to fly people in for interviews.”

“OK, will do. You really want women only?”

“Not necessarily. We have some accommodation down the street, and could put in male associates. But then we’d have to move your meetings outside. That is workable, if necessary. We are just limiting access to this building to women for now. If you want a specific man to work with, let me know, and I’ll make all the arrangements.”

“Good. Office?”

“Follow me. It will have a computer in it, for your work. And it is connected to the Internet. That should be all you need to find yourself some friends.”

“Hmm. Yeah. I wish it could find me a best friend and a spouse!”

Never for a moment did this highly education person imagine that simultaneous matching of jobs, friends and spouses might be the actual problem to be solved, or one of them, or that a computer really should be able to get her a best friend and a spouse. Had that crossed her mind, it would have sounded too much like computer dating.

“So, Daddy, did you think any of them was sexy?”

“You aren’t supposed to think that way, Beth. You’re a kid.”

“My own hormones are due to start assaulting my rationality any second now, Daddy, so I have had to learn about these things. You find women sexy, you do things to them, they have babies. That’s what we want to happen, right? So are any of these ladies hot?”

Ken suppressed a gasp, and tried to think rational thoughts, while inevitably he reacted with horror to the thought of his little girl growing up and becoming aware of sex.

“Oh, Beth. Father’s don’t like to hear their daughters talk about sex, but if you must know, I did find a few of them quite attractive, but would sleep with any of them if it would bond them into our community. They all seem to be bright, interesting people with something we need. If I had a choice, I’d take that combinatorial mathematician, Helen Rollins, who seems to have a fine mind.”

“I thought you were supposed to find only faces and breasts and other stuff sexy.”

“No, that’s just not true. Men usually think it is, and focus their attention on those things, but minds attract minds, and a fine mind is a very sexy thing indeed.”

“Really. That’s not what my books said, but I believe you. Didn’t you notice anything else about her? She seemed shaped like a woman is supposed to be shaped. And she was cute, wasn’t she?”

“Can’t say I noticed.”

“Liar.”

“There now, you sound exactly like your mother.”

Most of the visitors rooms were filled, with two left for contingencies. Including existing live-in childcare staff, all the staff rooms were filled. A small overflow group including two men were placed in an apartment building across the street which Ken owned and a meeting room was created there for formal meetings involving the entire computer project or any sub-project involving the men.

To the surprise of all the regular inhabitants of the building, the new additions to the staff were all quiet, pleasant, friendly, but not aggressively gregarious people. After working hours they like to swim, talk, walk around the building on the walking path, drink coffee and use their own computers for their own purposes. The were rarely seen to read a book, however, except possibly for some non-fiction, usually related to their field. They were not particularly literate or cultured, but liked music. Not well rounded people, they were nevertheless nice people whom everyone liked.

To Beth Green’s delight, a few other people from the computing and math project drifted into Ken’s net, including the pretty mathematician he craved — for her mathematical skills, of course. First had come a dawning awareness that there were indeed a lot of children in the building, but only one man, and most of the children shared some of his features. This began to happen when the new people had been in the building about two weeks.

One day Katrina said to Dr. Rollins “I think he is the father of all those children, himself, all of them. I think all those women sleep with him.”

“Uh, well, he is the only guy around. And I guess I have seen some of them come out of his room in the morning with a big smile on their faces. Yeah, I did see that. And the kids … it’s obvious if you look at it. OK, we are working in a harem!”

“Yeah”, Katrina agreed, “something like a harem. Nobody seems to be a prisoner, but he does exclude men. I haven’t seen any eunuchs, though. Aren’t there supposed to be eunuchs?”

“Eunuchs are out of fashion, I believe. Damn. I keep thinking of those women and the smiles on their faces. I wonder what he has got that ordinary male turkeys don’t.” Dr. Helen Rollins had once had boyfriends, like most women, and like most women she’d been less than impressed.

“Maybe he has a very big one, you know?”

“I doubt if that’s it. Do you want to volunteer to find out, Katrina?”

“No! Definitely not! Sleep with him? He’s old. Handsome, I guess, but old. Well maintained, though, to judge by the way he looked in a bathing suit last night. Yes, I noticed. But sleep with him? Definitely not. Probably not. Well, I guess, I might, I suppose. Would you?”

“Yes.”

“Yes? Just like that? Yes? Why? What makes you so interested all of a sudden?”

“I’ve been interested for quite a while. But I didn’t think he was available. I’ve been interested because he has a fine mind. We’ve worked together a lot. He’s really some kind of mathematician.”

“I don’t know if he is available. He has lots of women. Maybe he wouldn’t mind a couple more.”

“A couple more? I thought you were Miss Definitely Not.”

“Well. You know. I may have exaggerated. So how do we find out if he is available?”

“Why don’t we just ask him? Both of us. You know, ‘Oh, Mr. Green, are you available for sexual encounters?’ Something like that.”

“OK. Let’s do it.”

The two women stood up, amused, intrigued, then abandoned their coffee. They walked around until they encountered Ken alone in the library. He was the old-fashioned kind of guy who read books when he could be online.

“Mr. Green, are you busy? Could we talk to you?”

“Aren’t you supposed to call me Ken? Anyway, yes, you can talk to me. Anytime.”

“Uh, Ken, uh”, Katrina began, “are you the father of all those children and do you sleep with all those women in the big rooms near the dining area?” She got it all out in a rush.

“Yes.”

“Oh. Oh! Wow. We guessed, but, still. OK, then, here’s another question which is purely hypothetical. Would you sleep with me? No, no, sorry, what I meant was, if another woman like me or Dr. Rollins here was interested in a sexual encounter with you, and we are not, this is purely hypothetical, but if, just if such a women were interested, would it be possible?”

“No, but yes. No, I don’t just have sexual encounters. I have an exclusive commitment to the women here. I won’t sleep with anyone else. But the group of women here can be expanded, so yes, it is remotely possible for a women to join the group and end up in my bed. But this arrangement is for breeding purposes only. I only sleep with women for the purpose of making them pregnant. OK?”

“OK”, Katrina said, feeling somewhat disappointed, and showing it. She was 22 years old, and not ready to have any children. “Thanks for answering our questions. We won’t take any more of your time. Come on, Dr. Rollins.”

“You go, OK, Katrina? Now that I am here, there are some problems in small group theory that I should talk over with Mr. Green.”

Katrina left. “Small group theory?”, Ken asked. “Not exactly your field.”

“I’m thirty-two, Ken. If I don’t have a baby in the next few years it will be too late. Being here, walking around the building, and seeing the beautiful little babies, I’ve come to want one. Please, let me join your family here. Please give me a baby.”

“I thought you’d never ask. I’ve wanted you since the day I met you. And I’d love to impregnate you. But you have to take a medical exam first to prove that you are fit enough to have a child and aren’t carrying any nasty sexually transmitted diseases. Do you think that will be a problem?”

“No, no. You wanted me? You mean you wanted to procreate with me? Or something else?”

“I always think about procreation, but I wanted to rip your clothes off and ravish your naked body. If you didn’t mind.”

“Oh, uh, that would have been fine. Maybe we can schedule that for a day or two from now.”

“I’ll pencil you in.”

A dazed Helen Rollins was escorted to the clinic to see Dr. Richards. A couple of days later she met Mr. Green for the encounter he had described, which proved satisfactory to both of them.

“Daddy, Daddy! Did you do it to her? Was she good?”, Beth asked the next morning.

“Beth, I never kiss and tell, you know that. She was great.”

“What, I mean how, I mean, well, I know you put your thing in her, I know that. I saw the last sex ed video in grade four, the one the school gave Mommy but couldn’t show us themselves. But how do you actually, uh, I mean, what steps do you take, and how do you arrange your bodies? The videos in school were not very explicit at all, and everybody is supposed to do it differently anyway. What do you do?”

“Oh, this is so hard for a father to explain to his daughter”, Ken moaned.

“Daddy, how many daughters do you have over on the children’s side with me who are going to stay and grow up here?”

“Oh, a dozen or so, I guess. I’m not sure. Most are off with their mothers, and more will leave. About twenty counting the babies likely to stay.”

“More than thirty, counting those babies. More kids are staying since the school got started.”

“Oh.”

“How many of them are going ask you about sex?”

“Oh, well, uh, they do have mothers, like you do, and if they were smart, like you are supposed to be, they might ask their mothers, but I suppose they might want to get the male point of view. And some of their mothers don’t live here, and just visit. Oh, probably most of them, I suppose”, Ken said, miserably.

“So, I think it’s time you learned how talk to your daughters about these things.”

Ken grimaced and gave a brief account of what he ususally did with a woman. “But Beth, the hard thing to understand and deal with is not the physical situation and what happens but the overwhelming feelings that results. Desire and satisfaction and pleasure and other powerful emotions. It will be the feelings and emotions that you will have the most problem with. Though like all daddies I hope you never have sex, yourself. That’s one of those emotions that is hard to explain. Daddies just can’t bear the thought of their daughters having sex.”

“Well, don’t worry. I won’t for a very very long time, maybe till I’m thiry”, Beth insisted. But that night in bed she rubbed herself between her legs and rubbed where she thought she could almost feel tiny breasts. Nothing much happened, but it felt good. She imagined a man doing it to her, and that made it feel a bit better. Then she went to sleep, smiling.

In a surprisingly short time, Dr. Helen Rollins discovered she was pregnant. It had happened just that quickly. She was one very happy mathematician, and Ken was delighted with the prospect of having a baby with this fine woman. A few weeks later a paper that Helen Rollins co-authored with Ken Green on his multiple assignment problem was accepted for publication in a good journal of combinatorial optimization theory.

The day after this, ten year old Beth sat down with a miserably nauseous Dr. Rollins and offered her soda crackers. “Put one half of one in your mouth and chew it very slowly. My mother says it always helps. Now, Dr. Rollins, in the paper you wrote with Daddy, you suggest that as the number of simultaneous best matches being sought increases the problem gets much harder very fast. I think that’s true of the strict mathematical problem, but for approximations to it, I believe a larger number of connections can actually help.”

“You know, I actually wondered about that. Damn, you’re a smart girl, Beth. Let’s work on … yeaacchh! … that problem a bit, and see what we can come up with.”

“OK. Another cracker, quick.”

Two weeks later Beth was listed as the junior author of a paper on the multiple assignment problem, submitted for publication to the same journal. Beth asked Helen Rollins not to tell her father about it. He’d be too disappointed if it was not accepted. While waiting, Beth and Dr. Rollins submitted another paper, on a slightly different topic to another journal, this time with Beth’s name listed first.

Both papers were accepted and would be published, but it was this second paper which was accepted first. At that time Beth brought the letter of acceptance to her father, who yelped and hugged her, and picked her up in the air and twirled her around and kissed her, then cried and cried. Tears of joy.

They held a little party for Beth and Helen Rollins. Live music, dancing, and a decorated cake. And that night Ken took Helen to bed for some very redundant insemination, which they both thoroughly enjoyed. Afterwards, a glowing Helen asked Ken some questions.

“Ken, we’re friends, aren’t we?”

“I hope so. We are certainly lovers, but I feel closer to you than that.”

“Me too. Then tell me. There seems to be an issue that you are dodging.”

“I can’t marry you, however much I would indeed like to. The other women would kill me.”

“No, no, nothing like that. I mean what’s the real problem you wanted me to solve, that all this multiple assignment problem work is about? You have computing people working on it, too, as if there is something very real to be solved, but you didn’t explain the real problem.”

“I did, you just didn’t believe me. And if I had insisted on it you would have refused to take the problem seriously.”

“Uh. You don’t mean the simultaneous best friends and spouses problem thing you used to explain the problem to me? Not that? But, but why?”

“Helen, why are you in my bed?”

“Because I badly wanted you to fuck me?”

“Oh. Well, a nice reason. I always like that in a woman. But seriously. Why aren’t you in your husband’s bed, enjoying pleasant conversation in a sexual afterglow generated by your very own man?”

“Because I don’t have a husband?”

“Helen, you are one of the most attractive women I know. Why don’t you have a husband?”

“I couldn’t find one. All I could find were male turkeys who wanted their pleasure, when and how they felt like it, and couldn’t or wouldn’t enter into a real relationship and contribute something to it.”

“Well, believe it or not, there are millions of nice men out there. You should have found one. Actually if you hang on a couple of years until we get our true graph-theoretic combinatorial matching system going, we will find one for you. You deserve better than a shared man. We have several other related projects of course, but the matching problem is quite central.”

“Oh. Well, oh, OK, I guess. But I must say, sharing this one has been fun. I hope you’re not going to boot me out too soon.”

“I never boot anyone out. You can stay forever if you want. In my greedier moments I hope you will. But I think you deserve a man of your own. A good one.”

“You really think this is something that can be done? If it is based on combinatorial matching, it wouldn’t just be a dating system at all, but something much more, wouldn’t it? So much more that I can’t begin to imagine it. Goodness, it would change the world!”

“Exactly. I think you are only the second person after Beth that has understood what I am trying to do. Maybe the third. You should talk to my mathematical sociologist friend Edna Stilling.”

Ken talked more about the system they were trying to create, and made a deep impression on Helen Rollins. It was obviously something needed yesterday at the latest.

The system must incorporate a lot of various matching facilities, but also technology for helping people in other ways, social technology. For example it should be able to divide students into a number of classes, precisely the problem done by hand and rather poorly by teachers at the beginning of a school year.

It should be able to do all of the organizational functions based on error-covariance minimization which Ken’s early software had done plus adding the new combinatorial matching facilities to find people to hire and put them into appropriate jobs.

It should be able to give people a wide variety of suggestions about running their lives, all carefully chosen for their individual personalities and situations.

It should be able to network people, connecting existing friends and acquaintances, helping them to remain in contact while new friends were found for each. In short the new system should contain every piece of social technology Ken and Beth could imagine, all carefully integrated.

Ken and Beth had both had papers had papers accepted for publication which had been co-authored with Helen Rollins. Now they wrote one together. “Simultaneous Bipartite Matching for Social Technology.” They didn’t know if it would be accepted for publication or not. When submitting it, Ken included copies of the previous papers, with their acceptance letters. They they waited.

Yes! In August they got an acceptance letter, Beth’s third. The paper came out in December. Together with Ken’s books on the subject, it clearly established that they were the first to envision what would be such an important part of the society’s future.

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Business Development Short Story

Once upon a time the world’s richest man lived on cheap rations and was terribly in debt. All he had were ideas and a very smart woman in his bed.

Nobody is going to listen to you, Ken”, May said. “And nobody will read your book, either. If I can’t read it, nobody can.”

This was pillowtalk, after an exceptionally fine recreational session in his tiny basement suite. His single bedroom was not good for much else, but sleep and fun were enough. Mellow from his exertions, Ken accepted the woman’s comments without the mild bitterness he might otherwise have felt. What she’d said was true, of course.

What you need is money. A fiery passion for social change is not enough. Add money and stir, suddenly you will have a real chance of making a difference.”

Yes. Money. Hey, maybe I could pay people to listen to me.”

I don’t know if you’d be able to afford that. Not unless you had a lot of money.”

Well then, I should just make sure I have a lot of money, to buy the ears of the masses. Where does money come from, by the way?”

It comes from people who have it, in exchange for something they want.”

Any man would want you, my dear. Why haven’t you left me for someone rich?”

Oh, I might. A better plan would be to make you rich. I like having you around.”

This idle talk one night was followed by more serious one two days later.

Business software, Ken.”

Huh?”

You can write software. Businesses buy software. They might buy yours, if you wrote something good.”

Ouch. No fun in that.”

Think of it as a means to an end. Write it, sell it, then pay people to listen to you spout your world changing stuff.”

OK, I’ll think about it. I know nothing about business, though.”

Neither do I. Find someone who does. Take an add out in the Peak.”

The Peak was the student paper at Simon Fraser University, near Vancouver, where Ken and May were undergraduates. It took a while to come up with a wording, but eventually May wrote and submitted an ad that read, “Programmer interested in writing and selling business software seeks business student partner.”

Ken did not get along with men, and was reluctant to work with any. May jealously voted down any female applicant. Finally a married couple applied. Deeply in love, Dora and Joe Tenley were both business students who had been interested in the business applications of computers from the beginning.

It took a lot of effort for Ken to drag out of the Tenley’s just what they wanted the programs to do. May knew little about software requirements analysis, but had a lot of common sense, so she was able to help a lot.

It was not fun writing these boring programs, but working with the others began to appeal to Ken. Eventually the Tenley’s were able to switch from analysis mode to sales mode, selling the software Ken had written.

By their simple agreement, each of the four would get a quarter of the money that came in, though Ken had written the software. That seemed fair to all of them and the partnership seemed like it would last. May was the first to leave, and that was heartbreaking. Ken truly loved her, but he was spending more and more time on his work, less and less on her. Eventually she took her affections elsewhere.

Ken and the others were bound by promises and some written words to keep giving May a share of the income from what had already been written. They would certainly do so, but as new software emerged, those amounts would become insignificant.

The small company expanded quickly by hiring a few new programmers, especially those with a business orientation, but its further expansion was threatened by a growing rift between Ken and the married couple.

We believe in just hiring the best people and leaving them to run with it”, Joe Tenley said to Ken, summarizing their differences. “You want to meddle too much.”

It is not meddling. I just don’t accept the idea that people can be evaluated in isolation. It is a question of optimizing the workplace. And we are all part of it, so we need to be fitted in as well.”

Yes, sure, all that is apparently in your book, but I could never make sense of it, and neither could Dora.”

But are you willing to cooperate, for now?”

Ah, no. Not really. I think we might have to go our separate ways, Ken.”

That put an end to it. Ken left, assured of a regular income from software already sold. He took with him one programmer and one management person, both women.  All were students, actually. The whole company had been based on students.

Ken entertained the idea of sleeping with his new employees, but did not feel right doing so. He got his entertainment elsewhere. The young women were not there so much because he wanted to work with women, but because he didn’t want to work with men.

Ken’s new girlfriend was named Millie. Emily, actually, but she preferred the silly version of her name. As before with May, much of the direction Ken got was in pillowtalk, when he was mellow and receptive to the ideas of others.

I can’t understand a word you’ve written, Ken, but I believe you have something there. You say you have, and I trust you. So why don’t you trust yourself more? Use your own theories.”

I suppose I could. It won’t be easy though. Or cheap. I have only so much money coming in, and I haven’t begun using it to pay my student loans yet.”

Well don’t. There is no need to start paying them back as long as you remain a registered student, so use what income you have to set things up the way you want to.”

Worth a try.”

Ken’s part time management person was a young third-generation Chinese-Canadian woman named Vera Ling.

Vera, I want to hire some part time staff to make decisions and produce estimates for me. Say an hour a week. What would we have to do to get a lot of applicants willing to take a lengthy test in order to get the job?”

A lot of applicants? How many?”

Thousands. Not just from the university, but from all over. Not necessarily students, anybody.”

Well, it would have to be a lot. Not many people are going to attracted by the idea of getting an extra twenty dollars a week for an hour’s work.”

Let me think. What I want will be valuable. Suppose we paid them one hundred dollars a week, just for that one hour. That would be five hundred dollars a week or about $25,000 a year. Worth it. Easily worth it.”

Ken and Vera wrote up an ad, which went out to all university and college student newspapers as well as the local city papers. “Earn an extra $100 dollars a week. All that you need do is spend one hour a week answering a few simple questions. Applicants must take a one hour written test of general knowledge.”

Vera grimaced at the cost, but hired a hall, where Ken watched while a stream of arriving people took his carefully written general knowledge test. Over seven thousand people took the test, which was a multiple choice test. It used forms in which people blackened circles beside the list of possible answers. Ken had rented a device to automatically read these forms and enter the results into a computer.

Three days later, Ken had the information he wanted. He contacted the five selected people. To each of three he said, “I will be sending you short lists of yes-no questions. I just want you to guess at the right answers and submit them to me.” To the remaining two Ken said, “I will be sending you lists of questions for which the answer wanted is a numerical value, how much or how many or when. I just want you to guess at the right answers and submit them to me.”

With this set up, Ken talked to Vera Ling and his programmer, Henrietta Harris. “Well, it’s now up to the three of us to come up with questions. All of our people were selected to minimize their error-covariance, which means their tendency to make similar mistakes. We should be able to get pretty good decisions from votes of our decision making team of three. We should be able to get good numerical estimates from our two person estimating team. I call them teams, though they won’t work together or even know of each others existence.”

I think I understand about tendencies to make mistakes, Ken, and how we could good decisions using the votes of the three decision makers. But what about the estimators?”

Oh, another form of error-covariance. Where one tends to estimate low, the other tends to estimate high. The average or mean of their answers will almost always be pretty good, better than either one of them could guess.”

So what are the questions”, Henrietta asked.

Whatever we want to know. It is up to us, now. The three of us have to come up with things to ask.” In fact Ken also got good questions from his current girlfriend, the girl who had gotten him to apply his own methods, Millie Smith.

It took a while to become good at this. Vera wanted to know about investing money, Henrietta about whether a program of some kind would be useful. Programs that Henrietta suggested and were judged as useful by the decisions makers generated further questions from Vera, about how much they might sell for and how many copies might be sold. Ken’s questions were more general. Vera didn’t quite understand why he asked most of them.

Ken’s five person team of advisers was effective because they had been chosen well, but the supply of good questions to ask them was not ideal. Ken sought out an ideas person with Vera’s help, putting some questions to his strange committee about what kind of person to hire.

A week later, Ken and Vera hired a young woman (of course), Rina Anderson. She was an endless font of interesting ideas and could turn them into questions with great skill.

Now Ken had a good ideas person, a good team of decision makers and estimators, together with Vera Ling and Henrietta Harris to implement the decisions. It was now a machine which little input from Ken to run smoothly. He did provide ideas, but left decisions and implementation mostly others.

Now understanding how Ken’s theories applied, Vera got Henrietta to write software aimed at efficient use of them. Among the first things done was to expand the company, hiring more programmers, other managers, and eventually other teams of decision- makers and estimators.

As the company expanded, Ken finished his formal education, which he had continued part time. He got a bachelors degree in computer science with minors in psychology, sociology and linguistics. Then he did a interdisciplinary masters in computer science, systems theory, psychology and sociology.

We have enough money to buy a house now, Ken”, Millie said, the day he got his masters degree.

Millie. We should talk.”

Uh-oh. That sounds bad. Don’t tell me. I love you Ken. Don’t say it.”

 “You never did read my second book, did you, Millie?”

 ”Well, no, it wasn’t any easier to get into than the first one was.”

It’s mostly about people being compatible, Millie. I think people have to be really compatible to stay together. Ordinary love is not enough.”

But Ken, what are you saying. Don’t tell me you want to break up with me.”

No, but I think we should both look for someone else. I don’t mean split up right away, just assume we are not permanent. Keep our eyes open for other possibilities.”

Ken meant this to be gentle, but did not yet have the social skills he developed later. Millie felt heartbroken.

I can’t live that way, Ken. I can’t live with the idea that you might be looking for someone else. And I can’t look for someone else while being with you. I’d hoped we could stay together, get a house, you know, uh, well, maybe, you know …”

I’m sorry, Millie. I do love you, but I think we both need someone more compatible.”

Ken offered to buy Millie a place of her own, a condo of some sort, and to arrange that she could work for his company as an employee, reporting to Vera.

Having not only a broken heart but few choices, Millie agreed. She moved out of Ken’s apartment into the condo he bought for her, and worked for Vera. Eventually she got another job. Eventually she got another boyfriend. Eventually she got a whole new life, with a husband and family.

After Millie there were other women who wanted Ken to marry them. Again and again he had to explain his views on true compatibility. Once these were explained, a breakup was inevitable.

Meanwhile Ken’s commercial organization became enormous, increasing at an exponential rate. His scheme for making money was not a secret. Indeed, he published it in his third book. Somehow nobody understood what he was saying. Maybe he wrote poorly, maybe his ideas were to unconventional, maybe nobody understood that they were really working, making him rich.

Becoming rich changed Ken Green’s social life a lot. As soon as it became apparent that he had money, he was sought out by more and more women. To avoid breaking more hearts he now routinely explained his views on true compatibility upfront, insisting that any relationship they had was unlikely to last.

Though Ken explained this before getting involved with anyone, it did not take long before each woman developed domestic desires and wanted permanence. He had a nice house by this time. Over and over he got close to someone, explaining that their relationship would not last but inviting them to share his life and live in his house for a while. Over and over they found the warm nest seductive and wanted to stay, to marry and raise children in it. Over and over Ken had to gently explain about his desire for someone truly compatible, which eventually led to a breakup. Some were almost friendly separations, but some were not.

A billionaire by 35, Ken Green was still looking for the right woman as he approached 40. When between girlfriends he found sexual relief with a woman friend who did not need his money or want a family with him. She had a nice house of her own and children to keep her busy.

Edith Brown was an unusual woman. After she found out that her husband was cheating on her, she found a male friend of her own. That seemed only fair. Not wanting to divorce and still desiring each other, sometimes, both Edith and her husband had two sexual relationships at the same time, with each other and with their tolerant lovers.

Upon meeting and falling in love with Ken, she did not immediately seek a sexual relationship with him, but made it clear that he could have her whenever he needed her. So Edith had two men and occasionally three, when Ken was included. The men were jealous of each other, but stayed out of each other’s way, putting up with the situation.

It was probably Edith’s polyandry, a woman being with more than one man, which put the idea of polygamy into Ken’s head. He did not seek it out, but one day he found himself with two girls who both wanted him and a polygamous situation did develop.

Sarah Rivers and her friend Joan Simmons were very young, but a sexual relationship with them was legal under Canadian law. They pressed him for one. The insisted that they were not seeking marriage, but did want his children. They both wanted to stay with him and raise a family together.

Even Ken was not sure how they talked him into it, but they got what they wanted. Perhaps it was because Ken had begun to want children rather badly. What these girls offered was just too much to refuse. Thus was born the Green Family, which expanded rapidly as other women sought to join it.

Soon Ken changed the name of his corporate empire to the Green Family Corporation. It would continue to fund the growth of his family as it continued to grow itself.

Ken never intended to have a harem, it just worked out that way. He always claimed that it was not for his pleasure but for the production of children, and most people pretended to believe him.

Though he loved his children dearly, they were also intended for a purpose. He wanted to raise them to understand his ideas completely, and made sure they were taught about them from an early age. Each child was also taught something else from an early age, whatever the mother wanted. Thus many of Ken’s children became artists, musicians or scientists.

Probably the greatest success story in the Green family is the story of Beth Green, Ken’s first child. Raised to understand mathematics, computer science, psychology and sociology, Ken’s own special interests, she developed remarkable abilities at a young age. By age ten she was writing very useful software, some of which was sold before she was twelve.

That was the year Beth began to write an application of her father’s kind of social technology, which she called just The System. It would change the world.

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Error Covariance Personnel

Perhaps the most basic method used by Ken Green in acquiring his billions of dollars involves personnel selection using error covariance minimization.  The key notion is that having persons in an advisory capacity who tend to make similar mistakes is always bad.   By actually measuring error covariance it is possible to minimize it. 

There are two basic ways in which this concept can be applied.  One is by assembling a set of three people who vote on decisions to be made, choosing them carefully so that they have as little error-covariance as possible.   Having people vote on decisions to be made is ancient.  Ensuring that these people do not tend to make the same kinds of mistakes is crucial and little recognized.  

That is also true for the second way in the basic concept of error-covariance minimization can be applied.  A set of two people can be created to make estimates, such that whenever one person produces a low estimate, the other produces and equally high one.   The best estimate will be the mean (average) of the two estimates.  Choosing a set of two people which will have this property is not very hard if enough data is available.  For both of these methods to work, prospective employees would have to be given rather long and difficult tests. 

Creating useful tests is a non-trivial problem.  Happily, there is a way in which this can be bootstrapped to produce better and better results.  Advertise for people who might be able to write tests.  Use the trio of decision makers and estimators hired using the previously created tests to evaluate the applicants.  Estimators then give each test-writer applicant a numerical score representing the percentage of the test-questions provided by this applicant which would prove useful.  Decision makers then vote to hire or not hire the applicants with the best score.   Let the person or people hired during this round write a better test, more useful for hiring even better error-covariance-minimized teams.

In Social Techs, the more more recent and by far the largest of the large novels in which Ken Green’s business practices are described, he is shown to be working with people carefully selected in this way, though the details of how he started do so are not given.   Some will be given in other posts on this site.

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How Ken Green Made Billions

This website exists for two reasons.  One is to show others how a great deal of money can be made.  Another is to provide a reference site to which people curious about the fictional character Ken Green made his money.   In The Green Family Chronicles and the later composite novel Social Techs, Ken Green used various techniques based on social technology to make a lot of money.    For example, he hired people to make decisions based on error-covariance minimization.  He used similar techniques to hire people to do estimations, also based on error-covariance minimization, but this is an entirely different problem and he hired different people for it.  These technique were discussed in a work of fiction, but are valid and can be applied by entrepreneurs if they wish to use them — they are not trade secrets or patentable.   A site for entrepreneurs wishing to use social technology is http://Entrepreneurs.SocialTechnology.ca/ but most of the important information is elsewhere.

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