Moore’s Law for Everything revised edition

revised edition by Eliya Magesa

Introduction

This article is based on my views on how the plan of what’s coming that was suggested in ‘Moore’s law for everything’ article by Sam Altman should it look like. It is based on the work we have been doing at Bitbao technologies. Some places in this article have been copied from Sam’s article, thus because the purpose of writing this article is to improve Sam’s article rather than oppose it.

I do agree with Sam’s AI’s progress projection, computer programs that can think will read legal documents and give medical advice in the next five years. In the next decade, they will do assembly-line work and maybe even become companions. And in the decades after that, they will do almost everything, including making new scientific discoveries that will expand our concept of ‘everything’.

What I don’t agree with is Sam’s plan of what’s coming, thus because:

1. I find it wishfully or less actionable. As we are moving toward socioeconomic change faster than most people could imagine, we can’t wait for another Franklin Roosevelt to make a change, as suggested by Sam.

2. I find it centralized. Trendlines in governance is clear, the world is moving toward decentralization, so surviving by orders from a centralized system, I mean the wealth distribution policy suggested by Sam, is like taking us back to the socialist era.

3. I find a tax as a traditional way to address inequality. The tax has failed to solve inequality in this current world. You just take a look at the trendlines, no matter what governments do in updating tax policies inequality has continued to increase year after year from the beginning of capitalism. So, I think updating what we tax won’t do any better for the future world of AI. As Beth Singler, I may say, overly relying on corporate tax for human survival and flourishing has always seemed a mistake to me.

4. I find it exclusive. The plan sounds too American; has ignored the existence of other parts of the world which are factors you can’t keep constant in this connected world, as they may affect the whole plan.

5. I find it with bigger questions. To me, it sounds like the theory of everything in physics, as it has done well in collecting the required pieces to solve the challenge of the future, explaining outcomes of a solved future. But the left and arise challenges to be solved are very big and hard to solve, almost impossible as it is with the theory of everything. Since my purpose in writing this article is to improve rather than criticize or oppose, I won’t get a dipper on this point.

In this revised edition, I have recommended an actionable, decentralized, and inclusive plan of what’s coming, the plan that is built upon the use of technology to create more wealth and technology, rather than policy as recommended by Sam Altman, to fairly distribute it.

What follows are a description of what’s coming and my plan for how to navigate this new landscape.

Part 1: AI revolution

On a zoomed-out time scale, technological progress follows an exponential curve. Compare how the world looked 15 years ago (no smartphones, really), 150 years ago (no combustion engine, no home electricity), 1,500 years ago (no industrial machines), and 15,000 years ago (no agriculture).

The coming change will center on the most impressive of our capabilities: the phenomenal ability to think, create, understand, and reason. To the three great technological revolutions–the agricultural, the industrial, and the computational–we will add a fourth: the AI revolution. This revolution will generate enough wealth for everyone to have what they need, if we as a society manage it responsibly.

The technological progress we make in the next 100 years will be far larger than all we’ve made since we first controlled fire and invented the wheel. We have already built AI systems that can learn and do useful things. They are still primitive, but the trendlines are clear.

Part 2: Moore’s Law for Everything

In capitalism, there are two paths to earn an income: an individual to get employed, or own a means of production (self-employed).

Increasing workforce productivity is the only way to increase income hence wealth. Workforce productivity is explained by the rate of growth of capital intensity: the larger the rate of growth of capital/input per worker, the larger the rate of growth of output per worker, of the labor/workforce productivity.

AI and technology, in general, will dramatically increase workforce productivity while lower capital required. Consider the example of semiconductors and Moore’s Law: for decades, chips became twice as productive/powerful for the same price, which means the same capital required, about every two years. This will enable everyone to benefit from the world, because there will be dramatically more wealth to go around, so it will be much easier for everyone to win.

For instance, in Agriculture, AI will help yield healthier crops, control pests, monitor soil, and growing conditions, organize data for farmers, help with work land, and improve a wide range of agriculture-related tasks in the entire food supply chain. In learning and development, AI teachers will diagnose and explain exactly what a student doesn’t understand. In manufacturing, AI will do assembly-line work and maybe even become companions. In health, AI doctors will give medical advice and diagnose health problems better than humans. In transport, AI will bring self-driving, manage traffic, and drone taxes. In supply chain management, AI will plan, schedule, forecast, and spend analysis, logistic network optimization, and more. In law, AI will read legal documents and give legal advice. And so on.

Although AI will replace laborers, everyone will benefit from it because everyone will be able to be an owner of a means of production since AI will increase economic inclusivity to a higher extent. You will see and understand this well when I will describe my plan of what’s coming.

For instance, think of services provided by Upstart Company, leverages AI to predict individual creditworthiness using non-traditional variables such as education to provide loans of up to $50,000; Lenddo Company, leverages AI to predict individual creditworthiness using non-traditional variables such as social network data; Robo advisor platforms like Robinhood and SoFi, enable individuals to be owners by invest as little as a dollar; Crowdfunds; and so on. All of these services have increased economic inclusivity to a higher extent by enabling financially excluded individuals to take economic opportunities.

Part 3: Capitalism for Everyone

A stable economic system requires two components: growth and inclusivity. Economic growth matters because most people want their lives to improve every year. In a zero-sum world, one with no or very little growth, democracy can become antagonistic as people seek to vote money away from each other. What follows from that antagonism is distrust and polarization. In a high-growth world, the dogfights can be far fewer, because it’s much easier for everyone to win.

Economic inclusivity means everyone having a reasonable opportunity to get the resources they need to live the life they want. Economic inclusivity matters because it’s fair, produces a stable society, and can create the largest slices of pie for the most people. As a side benefit, it produces more growth.

Capitalism is a powerful engine of economic growth because it rewards people for investing in assets that generate value over time, which is an effective incentive system for creating and distributing technological gains. But the price of progress in capitalism is inequality.

Some inequality is ok–in fact, it’s critical, as shown by all systems that have tried to be perfectly equal–but a society that does not offer sufficient equality of opportunity for everyone to advance is not a society that will last.

The traditional way to address inequality has been by progressively taxing income. For a variety of reasons, that hasn’t worked very well. It will work much, much worse in the future. While people will still have jobs, many of those jobs won’t be the ones that create a lot of economic value in the way we think of value today. As AI produces most of the world’s basic goods and services, people will be freed up to spend more time with people they care about, care for people, appreciate art and nature, or work toward social good.

We should therefore focus on allowing everyone to be an owner of a means of production rather than labor, by enabling everyone to access the required capital. AI is the right tool that could bring such economic inclusivity.

Just think of services like the ones that are provided by Upstart Company, leverages AI to predict individual creditworthiness using non-traditional variables such as education to provide loans of up to $50,000; Lenddo Company, leverages AI to predict individual creditworthiness using non-traditional variables such as social network data; Robo advisor platforms like Robinhood and SoFi, enable individuals to be owners by invest as little as a dollar; Crowdfunds; and so on. All of these services have increased economic inclusivity to a higher extent by enabling financially excluded individuals to take economic opportunities.

Let us take a look at my theoretical stages of evolution of the capitalism system to see where capitalism messed up and lead to inequality, and how AI makes it possible now more than ever to achieve complete economic inclusivity hence reduce inequality and make capitalism be for everyone.

The first stage is early capitalism. It was characterized by human resource capital for one to privately own a means of production. The ones with more manpower or large families produced more because manpower was everything. At then it was when hard work paid, and inequality was quietly low. Economic inclusivity was higher since everyone had the required capital, manpower, and an opportunity to own a means of production, and everyone owned one. Then capitalism was true for everyone.

The second stage is middle capitalism. At this stage, slaveowners invested human resource capital, slaves’ manpower, powered by shelter and food energy. During this stage, inequality increased at a higher extent since few people, slaveowners, owned a large portion of means of production by exploiting the human resource capital of others, slaves, which at the first stage was the required capital someone could provide to privately own a means of production. Thus why it is safe to say that companies that were built by slaves, should measure the human resource capital (manpower) slaves invested and transform it into shares of a certain company, and give those shares to the clans of those who were slaves.

The third stage is the current capitalism. At this stage, machines' capital has replaced slaves or I may say much of human resource capital, and they are powered by oil energy. Much of the left human capital has been skilled laborers and few unskilled laborers all powered by a salary/wage energy and sometimes various kinds of employee benefits. This stage has brought about the rise of educational institutions. At this stage inequality has increased so much since few own means of production by exploiting human resource capital of many that is enough to be counted as an investment, actually, it happens at some companies, the providence of stock options to workers is a good example of human resource capital as an investment. Also something call unemployment has risen; it has come to life because machines capital has replaced much of human resource capital, mostly manpower, unskilled laborers. Technology has brought economic inclusivity but the one that is not enough to reduce the growth of inequality.

The new capitalism will have machines capital powered by clean energy, and AI capital, replacing human capital, powered by data energy. Every economic era has its engine of growth – from the Stone Age to the Industrial Revolution, which relied heavily on coal to transform manufacturing processes. While today oil drives economic growth through everything from product derivatives to effective international transport networks, it is data that will surely fuel industry 4.0, the future world of AI. Every single day we produce more than 2.5 quintillion bytes of data, that can be re-used a countless number of times and don’t expire, which is different from the current economic driver, fuel oil, that can’t be re-used and expires.

We could do something called the ‘United Companies of Digital (UCD)’. As the United States of America (USA) that is formed by states, the UCD would be formed by digital companies around the world that have agreed to recognize their users’ data ownership rights and control, and their users would be members/citizens of UCD. UCD would enable four billion digital users to translate their output/data into economic goods.

UCD would be in charge of issuing bonds (UCD bonds), on behalf of UCD companies, that have a maturity time of 100 years and a fixed coupon payment of 0.5%, whereby its value would be equal to the economic value of the data the UCD companies have collected and stored. UCD bonds would be distributed to UCD companies, whereby the worth of UCD bonds each UCD company would get would be equal to the worth /economic value of data that have been collected and stored by each.

UCD companies would trade (sell UCD bonds) in the, let us call it UCD Data Exchange Market, whereby they would sell to buyers/traders/their users UCD bonds in exchange for ownership rights and control of the data they, the UCD companies, have collected from them, their users, instead of money as it is in the capital market or money market, where bonds are traded. It would be costing UCD companies around 10% to 15% of their revenues to pay for the UCD bonds coupon payments, and face value (par value).

US bonds (treasury bonds) are considered the safest financial securities in the world, because buying them, treasury bonds, is like betting on the future of the US economy, US government ability to collect tax. But UCD bond would be safer than treasury bills, thus because buying them would be like betting on the future of the digital economy, of which the leaders of it are not politicians, but result-oriented leaders, tech visionaries who only thing that keeps them in the office is delivering value, it is also like betting on the productivity of AI labor against human labor.

The UCD bond that UCD members/citizens would earn in exchange for their data ownership rights and control, would be used as money (cryptocurrency) of which its value would depend on the digital economy, UCD companies GDP. The more the digital companies join UCD the more the UCD cryptocurrency (UCD bonds) value reflects that of the digital economy.

That is how we would make capitalism be for everyone.

Part 4: Implementation and Troubleshooting

The GDP of United Companies of Digital (UCD) would be that of the digital economy, which is expected to reach $53.3 trillion in 2023 if all digital companies become members of UCD. It would be saving roughly four billion digital users. The value-added of the said GDP has been growing by an average annual rate of 10% per year from 1998 to 2020, but if digital companies freed on using AI it might even be more, though we would only need a forever not less than 10% growth year after year to balance the proposed system.

The best way to get digital companies to join UCD, recognize their users’ data ownership rights and control, and terms of collecting and storing their user's data would be forming a game-changing and convincing policy for UCD.

The policy I would suggest is ‘PAY FOR DIGITAL SERVICES’; All the users of UCD companies would pay the price of using digital services and UCD companies would be allowed to increase costs of their digital services by up to 10% after each software updating or service improvement.

In fact, people have already started feeling comfortable paying for digital services, take an example of services like Amazon Prime, Netflix, Spotify, Medium, and now even Twitter. I think digital users should pay for every service from payment gateways, social networks, Apple Siri, Google Map, to Operating Systems.

The said the policy would increase digital companies’ revenues by more than two times. You might say that people wouldn’t be able to pay for digital services, but if in exchange, they would earn from their data an amount that is worth three times more than the cost charged by digital services they would feel comfortable paying.

As many largest digital companies are focusing on reducing the over-dependence of one revenue stream and would want to impress their investors with a large jump in revenues, they would agree to join UCD hence recognize their users’ data ownership rights and control, and terms of collecting and storing their users’ data.

The term regarding the trading of digital users data would be, a UCD company would be supposed to purchase each data they collect from their users and store, at its economic value.

At the UCD Data Exchange Market, UCD company would be granted rights and control of their users' data that they have collected and stored, in exchange for their promise (UCD bonds) of paying the whole price (face value/par value) of the data at its current economic value after a period of a hundred years, and interest (coupon payment) of 0.5% annually till the time of maturity of the promise (UCD bonds). The said UCD company would be giving a promise (UCD bonds) for each data at each time (at the end of a day) they collect from their users, whereby the promise (UCD bonds) value would be equal to the economic value of the said data.

The economic value of user data shared to a digital company would be measured by first, determine data quality, the qualitative and quantitative of data, of the said data and assign the value in percentage. Second, determine the value of the digital user potential or consumption ability in the said digital company by checking on his/her credit scores that are based on his/her income and worth of the digital economy of the country that the said digital user lives, and assign the value in US dollars. After all that, we would take the value of data quality (in percentage) that we would have got in the first step, multiply by the value of the digital user potential (in US dollars) that we would have got in the second step, and then we would now get the economic value, in the US dollars, of user data shared to the said digital company.

If total average revenues, GDP, of UCD companies keep growing by not less than 10% each year and average data stored by UCD companies keep growing by not more than the percentage growth of that year’s revenues, of which in simple words it means the usefulness of data should always increase, then UCD bonds would never drop in value, else it would be changing accordingly.

The following is the average worth of UCD bonds Facebook users would have earned in the year 2020:

1. Facebook users from the US and Canada would have earned UCD bonds worth $3,277.

2. Facebook users from Europe would have earned UCD bonds worth $1,019.

3. Facebook users from the Asia Pacific would have earned UCD bonds worth $275.

4. Facebook users from the rest of the world would have earned UCD bonds worth $175.

It would have cost Facebook not more than 10% of their that year revenues, but keep in mind with the implementation of the ‘PAY FOR DIGITAL SERVICES’ policy, whereby each Facebook user would have paid approximately an average amount of $100 for the subscription of the said year, this would have caused a jump of about 300% more on each said year revenues, users’ data economic value, and worth of UCD bonds earned by Facebook users.

The following is the average worth of UCD bonds Facebook users would have earned in the year 2020 if the said policy would have been implemented completely:

1. Facebook users from the US and Canada would have earned UCD bonds worth $9,831.

2. Facebook users from Europe would have earned UCD bonds worth $3,039.

3. Facebook users from the Asia Pacific would have earned UCD bonds worth $825.

4. Facebook users from the rest of the world would have earned UCD bonds worth $325.

Those dividends could be much higher if AI accelerates growth, they grow with the growth of Facebook revenues, GDP. But even if they’re not, those are earnings a digital user would receive from social media (Facebook) only, what about other digital services he/she uses like Google search, Google map, Apple Siri, YouTube TV, Netflix, Quora, and so on. Probably a total average worth of UCD bonds a digital user from the US would have earned from digital services in the said year is close to $40,000, and it would be increasing each year with the increase of the digital economy GDP.

Part 5: Shifting to the New System

A great future isn’t complicated: we need technology to create more wealth, and fairly distribute it. We do have AI, that will increase workforce productivity hence create more wealth, and most of all a technological system, UCD system I have described in part 3 and 4, that will distribute to people technological, AI, gains and make AI join the workforce.

Data is considered the most valuable commodity in the world, the oil of industry 4.0 (AI world), and we, people, produce it every day. At Bitbao technologies, we’re developing a system, works as a UCD system described in part 3 and 4, that leverages AI to translate people output or data into economic good, it will enable people to benefit from the future data economy world.

Data ownership is privacy as well as an economic issue, thus why hear at Bitbao technologies we give people control over their data from both a financial and privacy perspective, enable them to use, trade, give away, destroy, control shared information, and track and break the use of data around organizations you have shared data with. Currently, we’re developing a beta.