UBI or Global Spending Plans: Mitigating Economic Inequality Amid Generative AI Boom

A recent article in Vanity Fair, Artificial Intelligence May Be Humanity’s Most Ingenious Invention—And Its Last?, states that "…for example, call centers in India make up 8 percent of that country’s GDP. In Brazil, it’s 6.3 percent. The US, despite having already outsourced millions of those jobs to places like India and Brazil, still employs 3.4 million people who work in call centers. Call centers could be the first job to be completely replaced by AI, and the repercussions could be disastrous."

If too many people lose jobs to AI too fast, what can be done? There might be a few options: redefinition of work, alternation of remuneration and spending plan.

A spending plan is proposed here as a global fintech-based project where people in different cities in countries around the world publish a financial plan on how to spend a certain amount per month.

This implies a plan for how to spend A amount per month at B location, on feeding, clothing, transport, and bills. This amount will range from the lowest possible amount to an upper limit, across seasons.

For example, how an individual spends say $100 a month, for those expenses in some lowkey county in Indiana, in summer, as the lowest possible amount. Or, how can this go up to a maximum of $170 during the winter months?

The minimum grade, A, may stay at its lowest, while it might occasionally increase slightly to C, D, or E. Similarly, the price range could fluctuate from $100 to a maximum of around $130. During the winter months, expect the grades to remain at their lowest or slightly higher, with price intervals within a similar range.

This would vary across locations within the United States and across regions in countries around the world, showing what food to buy, how to conserve bills, cheaper transport to take, clothes to buy, and so forth, ensuring that a $100 budget is not exceeded in one month, for say, Fowler, IN.

This plan will be published on a website matching the map of the country, to expose possibilities with pre-set spending plans for people, so that affordable options are possible. This is not a personal budget, but a plan to spend an amount for some necessities in a month, showing how that is possible, with what to buy, what to skip, what products or services, may work for that bracket, and so forth.

There will also be a category in this publication, to list cheaper variants of things and where to get them, so that rather than see the amount a person has as inadequate, the reserve can be true.

This spending excludes rent, healthcare, tuition for kids, emergency, insurance, mortgage, and so forth, but if there is saving on those other needs, it is possible to have more for these other more expensive needs.

This individual budget is different from a family or couple's budget but with the lowest possible for individuals, families and couples may subsume within those options.

Advantages to this plan include debt prevention for some, crime prevention for some, and migration desperation prevention for some, it may drive more corporations to have more affordable consumer plans or products.

It may also lead to extra options like housing, health options, and others so that possible allowances are exposed for that location.

So, how can an individual spend a very low amount per month? The first thing is how many times will someone eat a day? Also, what is transportation like, individual or public? What is the mobile phone plan or internet? What toiletries would be purchased and how many times? What bills are paid, and what is the possible or constant minimum? People will be asked to provide this, as much as they have been able to save on things, which will be sent into this database. The figures can be corroborated as they come from others or feedback can be sought from others.

The public information provided by people will be free. This fintech solution would maintain itself by paid consulting of financial strategy to people, as requested, helping to cover servers, labor, and technical services.

LLMs can also be used to predict possible plans after a while.

If cities in different countries have this, it is possible to use this information to decide options, especially on moving plans where to save the most, or where it is possible to manage, while between jobs or working remotely.

Some people can already live on a really low income, which without any bad luck is quite OK. However, the goal here is to see an established plan exploring possibilities for one's income or where doing more with less is possible.

This exceeds the universal basic income [UBI] option. It makes an inflation-free provision, to be maximized for information-guided survival, against seeing an individual's income as limited. There is a problem of economic inequality that AI may exacerbate. If there is a public spending plan for pegs of amounts, which is fairly accurate, and updated, its applicability may lead to equivalents of necessities where affordability is prioritized, lowering some of the massive inequality gap that LLMs may induce.

The future of work can also be resized with this, where work is seen as doing, and remuneration must not be money. Work is generally what is valued and wages are often monetary. In the age of generative AI, it is possible to invert these, to spread work into more.