Executive summary

Advancements in the field of artificial intelligence have created a veritable scramble to integrate the technology with consumer products among firms. This competition has given rise to a number of useful insights that reflect the problems that the industry faces in the decades to come, and illustrates the direction of innovation in the race to create increasingly competent and “general” intelligences.
Though specific AIs trained on niche tasks have been developed in the past, multiple companies have suggested that the future of artificial intelligence lies in creating the aforementioned artificial general intelligence for overall tasks.
These pose the biggest threat to human employment, but as the field stands right now, do not pose a massive development threat.
Right now, the biggest threats posed by artificial intelligence-based systems come from the fact that advanced technologies have shown moderate levels of success in driving automation, automation of sales tasks, as well as success in retail industries.
The near-future shows the possibility of achieving profitability for these products in the consumer space as well, creating an unemployment crisis for those currently employed in said industries.
With these developments, and the threat of general intelligence in the future, the idea of a Universal Basic Income (UBI) scheme has often been floated.
Such a development would ensure that people are monetarily secure from the issues posed by unemployment.
On a more philosophical level, however, the purpose of this work must also be considered.
Meaningful employment often serves an intrinsic value to people completely divorced from the material wealth accumulated.
This reality makes it necessary to consider the sociocultural impacts of such changes; one possible way to deal with said issues is to set quotas for human employment in certain fields, such as those with artistic necessities and more creative needs overall.
This is of particular necessity in fields that involve interaction between people, such as teaching, and the aforementioned retail and sales industries. The former solution also assists wealth accumulation in a more monetary sense, and deals with the oncoming employment crises as well.

Overview

Relevance

With the development of specific artificial intelligence systems as well as the production of artificial general intelligences in the near future, humanity is faced with a multifaceted threat, material and existential in nature. The rapid development of said new technologies is exemplified by the sheer volume of automation-based products currently being developed and used.
Image generation technology, like Midjourney and DALL-E, as well as text-generation models (LLMs) like ChatGPT and Claude have only gotten more accurate since their market adoption, and threaten to destabilize the copywriting and marketing industries.
The development of generative adversarial networks (GANs) have made artistic pursuits, like the analysis and processing of images, and the creation of images in specific styles writ large.
This is not to mention the role artificial intelligence technology plays in the creation of increasingly accurate models for the automated driving of vehicles, and even fields that require human interactions, such as sales and the education industry.
Since antiquity, labor has played a central role in people’s lives, both monetarily and socioculturally. With the advent of such revolutionary technologies, then, humanity is faced not only with a crisis in unemployment, which will require significant investment into a more diversified education system for the populus, but also with an existential threat about the role of meaningful work and the worker in society.

B. Current Stances and Tried Policy

In a study from the Pew Research Center, 19% of the American workforce have jobs that are highly exposed to artificial intelligence, while a warning from the International Monetary Fund posited that 40% of workers worldwide have jobs threatened by artificial intelligence systems.
A majority of these jobs are also concentrated in higher-income countries than lower-income ones, and a majority of those with jobs threatened by artificial intelligence reported higher levels of education and higher overall wages, and reported feeling more hopeful about the prospect of using artificial intelligence systems in their daily work overall.
Thus, an analysis of jobs that have a high risk of artificial intelligence exposure versus those that have a lower risk of such exposure show that tasks that include higher levels of analysis and critical thinking are at highest risk, and must be insulated through regulatory policy.
For many, this involves sizable investments into trade-related jobs, such as pipelaying, repairs, and child-care work, as opposed to the current emphasis on more analytical work.
This is especially important in higher-income countries.
Another perspective, however, suggests that with analytical jobs being automated, society will begin to increasingly prioritize more artistic pursuits and industries, and thus investments should be directed in this critically underfunded area.
An analysis of the current product field for artificial intelligence, however, shows that these fields in particular are at a higher risk for being exposed to artificial intelligence, up to 26% compared to ~20% for the general workforce.
With these current stances in mind, it is also important to acknowledge that apart from some regulations, most of which have come in the form of handbooks and guidelines unlikely to be enforced, most governments around the world have not acted upon the threats posed by artificial intelligence systems, and no clear parties have emerged to lead the way in their absence either.
In terms of relevant tried policy, then, the only applicable statute in the United States is the Fair Labor Standards Act of 1938, a part of Franklin D.
Roosevelt’s New Deal Programs, which according to the Bulletin of the Atomic Scientists should “all data laborers, including those whose work is harvested to train AI without compensation.” This statute is thus applicable to those in the workforce whose jobs can in the near future be replaced by artificial intelligence systems.
Liberal legal interpretations of this law have also extended to enacting universal basic income in general, while a more conservative stance posits that the government should pursue a pro-work, pro-business strategy to combat issues posed by artificial intelligence. Legislation in the European Union has been more current and effective in moderating the use of artificial intelligence, particularly in enacting safeguards on general artificial intelligence systems, and limits on unregulated usage of AI through increased customer/consumer rights.

Policy Problem

A. Stakeholders

There are many stakeholders in labor policy, particularly when the issue is as imposing as the risks of artificial intelligence. As previously mentioned, those at a higher risk of having artificial intelligence exposure in their industries include people who work in industries that require more analytical and critical thinking skills.
These include web developers, software engineers, copywriters, marketing professionals, and a number of similar industries that require deriving insights from data presented, or using said information to develop software-based solutions.
A caveat to this, as previously stated, is the art industry; with the development of increasingly sophisticated products to generate artistic content, the profit-mechanism for employed artists declines, leading to unemployment in the field. For the purposes of proposed solutions, this policy review focuses on the trucking, retail and sales industries.

B. Risks of Indifference

The urgency in developing regulatory labor policy for artificial intelligence is shown not only in the rapid development of artificial intelligence products that automate analytical and artistic endeavors, but also in the increasing profitability and spread of said products.
An important factoid to highlight here is the idea that artificial intelligence systems are only going to get more developed in the future, capable of handling more complicated tasks and possibly even generalities rather than just niche subject matters.
If such systems do develop before anticipatory regulatory policy is developed, then it will be increasingly difficult for governments and regulatory bodies to control such systems, leading to disastrous consequences for future labor forces. These consequences include unemployment and underemployment, as well as a whole host of other issues, many of which possibly haven’t been anticipated.

C. Nonpartisan Reasoning

Regulation of artificial intelligence, as well as regulation overall, is not a partisan issue, with a majority of both major parties in the United States (50% of Republicans and 57% of Democrats) and many political groups in the European Union agreeing that AI should be regulated. Partisanship comes into play, however, when workers rights and compensation are discussed.
Ideologically, those on the political right tend to be more pro-business, thus making the just compensation for those whose jobs are displaced by AI a disproportionately more left-leaning issue. However, non-partisan reasoning is especially important for artificial intelligence-based regulation and labor policy, as without it, the livelihoods of millions of workers are progressively threatened as AI systems advance in their development.

Conclusions and Policy Recommendations

In conclusion, the progressive development of artificial intelligence systems poses both a material risk to people employed in jobs involving critical and analytical thinking as well as artistic pursuits, but also more existential risks in the changing sociocultural perceptions of meaningful employment.
In order to combat the issues faced by these rapid developments, it is imperative that progressive regulatory labor policy is developed, particularly those concerning universal basic income and employment quotas in key industries such as trucking, retail, and sales.
With regards to the first key industry, the development of automated vehicles makes this a field that must be considered rapidly disappearing with developments of increasingly sophisticated models for self-driving.
As for the latter two industries, the human to human interaction as well as nascent developments in powerful analytical capabilities make these industries particularly susceptible to significant exposure to AI.
By enacting a universal basic income scheme, the monetary displacement issue posed by artificial intelligence taking over certain job sectors can be dealt with.
Taking into account the role workers and meaningful work plays socioculturally, however, it is difficult to suggest how such perspectives may change given the exposure issue.
However, if the status quo is to be maintained, a quota system could be implemented to ensure that a certain number of humans are employed in a given sector.
As for funding considerations, Universal basic income can be provided by taxing AI companies for employing technology in direct opposition to people for certain roles.
Subsidies can also be instituted that will ensure the quota system for employment can be maintained. Since such issues fall under the purview of the departments of labor under a government, urgent action is needed to bring said issues to light and to address the need for progressive regulatory labor policy that accounts for the role of the workers in a given industry.

Acknowledgment

The Institute for Youth in Policy wishes to acknowledge Paul Kramer, Carlos Bindert, Gwen Singer, and other contributors for developing and maintaining the Programming Department within the Institute.

References

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