Can AI Help Us Achieve UBS (Universal Basic Income)?

Can AI Help Us Achieve UBS (Universal Basic Income)?

Could AI, the very technology potentially causing job losses, be the key to unlocking Universal Basic Income (UBI)?

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5 min read

UBI aims to bridge the gap between technology innovation and social welfare. But why is the discussion becoming so contentious now that notable figures have joined in? Let's start with the crux.

What is Universal Basic Income or UBI?

The notion of UBI could be traced back to the 16th century, when philosopher Thomas More mused about a society in which everyone receives a guaranteed income. In the twentieth century, economists such as Milton Friedman proposed a negative income tax, a version of UBI, to simplify social programs.

The notion became popular in the 1960s and 1970s as a result of numerous studies conducted in the US and Canada to examine the effects of providing citizens with a guaranteed income. In spite of these early setbacks, UBI was rejected as a utopian concept and remained marginal for decades before returning to popularity.

Universal Basic Income seeks to provide a consistent, fixed sum of money to all citizens of a state or country, regardless of employment status or income level.

Here's a simple demonstration of UBI in a country:

Assume a country has a population of 100 million. The government chooses to introduce a $1,000 per month UBI for each resident.

To determine the overall cost of UBI per month, multiply the amount by the population.

Total UBI Cost = UBI per person x Population.

To calculate the total cost of UBI, multiply $1000 by 100,000,000 to get $100,000,000,000 (100 billion dollars).

So, establishing UBI for one month in this country would cost a massive $100 billion.

Now, evaluate how this expense would be covered. The government can raise funds through a variety of sources, including taxes, resource royalties and even creating money.

If we assume that the government collects taxes to support UBI, the revenue generated must be sufficient to cover the UBI expenditures. To generate the necessary money, tax rates may need to be adjusted or new taxes imposed.

So, in general, this appears highly hopeful with advocates of universal basic income (UBI) hope to relieve people from the never-ending stress of living paycheck to paycheck so they can follow their interests in education, caring or entrepreneurship.

Opponents, meanwhile, are concerned about UBI's potential to create a work disincentive and its financial viability.

AI intervention in addressing issues with UBI outcomes

Prominent figures are already seen adding their own rhythm to the UBI discussion:

  • Andrew Yang, Entrepreneur and Former U.S. Presidential Candidate, champions UBI, arguing that automation necessitates it. He proposes a "VAT Forward" system, allocating a portion of the sales tax to citizens.

  • Elon Musk, CEO of Tesla and SpaceX supports UBI as a solution to job displacement from AI. He believes a basic income is vital in an increasingly automated world.

  • Sam Altman, Former President of Y Combinator, suggests that AI could create abundant resources, making UBI a viable option. He emphasizes the need to explore innovative ways to fund such a program.

As it happens, AI is viewed as both the root cause and the solution for universal basic income. Automation is undoubtedly taking over certain important responsibilities, but artificial intelligence (AI) can also have beneficial implications on UBI policies.

The following are two instances in which AI has the ability to simplify UBI implementation, but there are probably many more.

Case 1: Because AI-powered companies rely primarily on machines rather than humans for much of their work, they can afford to spend less on office space, benefits and salaries. As a result, they stand to save a substantial amount of money that may be used to fund UBI dividend payments.

Case 2: Tasks can be automated by AI, which speeds up and reduces costs. Consider a warehouse where orders are picked and packed by robots rather than by people. This expedites the procedure and lowers labor expenses, increasing revenue for the business. The UBI may then distribute a portion of these profits as dividends.

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Moreover, GenAI plays an important role in improving tax collection and processing. As an example,

  • GenAI algorithms can analyze complex financial data and detect tax evasion tendencies more successfully than previous approaches. According to research, AI-powered tax audits might recover massive amounts of money from the market. Increased tax revenue collection with GenAI may improve the financial feasibility of UBI initiatives.

  • GenAI can automate tax filing and processing operations, lowering administrative expenses and potentially making the process easier for citizens. This could lead to higher tax compliance rates, which would boost UBI funding.

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Policy overhauling to accommodate AI and UBI

As AI capabilities grow, authorities must consider key questions about economic security, opportunity and well-being. AI and data science can contribute to these talks if used wisely.

For example, AI forecasting techniques may aid in projecting the rate of employment disruption and the skills required. This could direct educational efforts to assist workers in transitioning. AI can also evaluate massive amounts of transdisciplinary data to simulate various policy scenarios and potential results.

This study looks at how the human right to science (RtS) intersects with data science (DS) and related activities, including data monetization. It claims that AI and data science can help achieve Universal Basic Income (UBI) in three ways:

  1. Ending harmful data practices: RtS entails prohibiting data monetization that breaches human rights, such as privacy invasions.

  2. Sharing monetary advantages: While data monetization continues, RtS means sharing monetary advantages via a UBI system founded on RtS principles.

  3. Promoting participation and pro-social uses: RtS also entails encouraging ordinary people to participate in DS and prioritizing non-profit, pro-social uses of DS, such as citizen or community-driven projects.

To make AI and UBI work in tandem, political unanimity is also important and all parties must reach an agreement in the near future. AI has a job to play, but sufficient regulations must be established to make things run smoothly.

So, the bottom line is that UBI enabled by AI is still unattainable at this time due to the sensitivity of the subject, but there is speculation that tech innovators are preparing AI in such a way that it will alleviate some income-related concerns.

If you have any thoughts on the matter, please leave a comment and share your ideas and knowledge with our readers.

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