BY KEVIN POLICARPO
As A.I. becomes more prevalent, concerns about the dangers of the technology continue to intensify. The ability of A.I. to produce material at a rate that humans cannot match makes it attractive for corporations to increase their bottom line. However, this focus on automation is threatening the livelihoods of employees who could end up jobless as a result.
USE OF A.I. RAISES CONCERNS FOR JOBS & EMPLOYEES
The National Bureau of Economic Research (NBER) published a paper titled ‘How Might Fiscal Policy Respond to the Rise of Artificial Intelligence?’. The goal of this paper is to explain the impact of A.I. in the U.S. economy, which is summarized in the report’s abstract:
“Artificial intelligence will probably generate major changes in the US economy, although the nature, timing, and magnitude of those changes are highly uncertain. We analyze a set of long-term scenarios involving different combinations of faster productivity growth, greater income inequality, job displacement, and a higher capital share of income. For each scenario, we assess the implications for federal debt and potential policy responses related to faster economic growth, the distribution of income, support for workers who are laid off, and taxation and ownership of capital. Given the uncertainty surrounding AI’s economic effects, policies that are robust to different scenarios would be especially valuable.”[1]
The scenarios are as follows and are summarized:
- In the first scenario, AI is a “rising tide” that lifts all businesses. In this scenario, A.I. boosts the annual growth of Total Factor Productivity (TFP) in the non-agricultural sector by .5% over the next 30 years.[2]
- In the second scenario, AI is again a rising tide, but it lifts only some businesses. This scenario has TFP and GDP (Gross Domestic Product) growth, but the national income gains are skewed toward specialized roles and the top quintile.
- The third scenario has the same GDP and TFP growth as the second scenario, but it leads to a considerable loss of workers who have a hard time finding new jobs. This scenario has “…the unemployment rate ends up 1 percentage point higher and the labor force participation rate 1 percentage point lower than otherwise would be the case.”[3]
- In the fourth scenario, AI has more profound effects, with even faster economic growth, major permanent job displacement, and income gains going exclusively to capital rather than labor. TFP grows 1 percentage point per year faster than current projections from the Congressional Budget Office, and job losses raise the unemployment rate by 2% and reduce the labor force participation rate by 4%.
The report summarizes the scenarios thusly:
“The pace of disruption to labor markets would matter crucially for macroeconomic outcomes and appropriate policy responses. If the demand for workers with particular skills dropped sharply, many workers would lose their jobs and need to find new ones—but if the demand diminished gradually, some workers with those skills would retire, and new workers would enter other fields, so fewer workers would be laid off. In our third and fourth scenarios, job losses occur at a moderate pace as additional TFP emerges. Faster changes would be more disruptive and would increase public pressure for policy responses.”[4]
Three industries highlight the threat of A.I. causing job loss: Healthcare, Astrophysics and Fashion:
HEALTHCARE
A MedPage Today article (October 13th, 2026), AI Has a Darker Side in Healthcare, Expert Says, warns that while A.I. can provide benefits for the healthcare industry, there are numerous pitfalls to be mindful of. Mishal Khan, a senior researcher at the Technology and Work Program from UC Berkeley’s Labor Center noted several potential harms:
- “Job loss
- Theft of work product
- Job de-skilling
- Lower wages and wage theft
- Work speed-up and injuries
- Discrimination
- Suppression of labor organizing
- Loss of autonomy and control”[5]
Of these concerns, “…Khan found that de-skilling — in which humans lose specialized skills due to AI or other automation taking over those tasks — was a particular concern, and could threaten healthcare workers’ scope of practice.”[6] This observation was echoed by Tina Hernandez-Boussard, a professor of biomedical informatics at Stanford University at another conference. She spoke about an incident in Uganda where a group of medical residents struggled to work as the loss of electricity meant they had no A.i. to assist them in reading electrocardiograms of their patients.
Khan also worried about A.I. causing alienation and detachment of doctors and their patients as the work is handed off to automated systems: “’Workers are concerned about what this is doing to patient relationships,’ she pointed out, adding that there is also the issue of liability: If a mistake is made as the result of an AI recommendation, who will be held accountable?”[7]
Fortunately, Khan stated that state governments are taking action on these issues. One example is that Illinois and Vermont have prohibited replacement of mental health workers with A.I.. Another is a California law that bars companies from advertising an A.I. chatbot as a healthcare worker.
RISKS TO ASTROPHYSICISTS
Science Magazine recently reported on The Last Astronomers: Amid a flood of AI advances, astrophysicists are questioning the soul of their field about the growing use of A.I. to solve complex problems.
The report citied the Center for Astrophysics | Harvard & Smithsonian, which employs over 800 astronomers and is one of the world’s largest concentrations of stargazers.[8]
Cecilia Garraffo, the founder and director of the AstroAI Institute[9], led the center’s efforts to incorporate machine learning to solve various problems. In the four years “…since they first proposed this specialized team, Garraffo and her colleagues have forged collaborations throughout the building and with industry teams such as Google DeepMind and Anthropic.”[10]
Originally, the team wanted to use A.I. and machine learning (ML) to solve math and computations, not wanting to use models like ChatGPT to solve the scientific questions. This policy changed when one of Garraffo’s colleagues, Alyssa Goodman, used ChatGPT to solve the question of how the spiral arms of a distant galaxy were moving as her team had failed to solve it after years of work. ChatGPT solved the problem in a few minutes, producing data which they used in reports that they published.
The result is:
“Representatives of the AI companies, who seem to view astrophysics problems as public relations boons that offer compelling showcases of their models, boast that their technologies will soon achieve supremacy over actual theoretical physicists, astrophysicists, and cosmologists. Some even make mechanizing the study of the night sky a selling point. In February, as Elon Musk began seeking to take SpaceX public to raise cash for orbiting data centers, his company explained its true goal as ‘scaling to make a sentient Sun to understand the Universe. Already, by making it faster and easier to produce professional-seeming papers, AIs threaten both to overwhelm journals and peer reviewers and to take opportunities away from junior scientists. But far upstream of that, many scientists interviewed by Science sense a phase change underway. Many fear that if unleashed in all parts of the scientific process, AI tools could lead to nothing less than the death of astrophysics as a human endeavor. A lot of people think that it’s too late to intervene—we’re done, says David Hogg, a computational astrophysicist at New York University (NYU).”[11]
A.I. ELIMINATES MODELS’ JOBS IN FASHION
Among the various businesses increasing their usage of A.I. a more recent development is their use in the fashion industry.
A Reuters report (October 27th, 2026), reported that using A.I.-generated fashion models would allow for retail “…to create lifelike images for their retail websites while cutting costs by 90% or more compared to photo shoots with human models.”[12]
This application of the technology “…poses an existential threat because of scant regulation governing the ownership or use of digital twins. Fashion models face the risk of unpaid replication of their image – or replacement by entirely synthetic models.”[13]
Reuters interviewed 15 model-agency directors and reviewed over a dozen confidential photo-shoot contracts where brands such as Calvin Klein, L’Oreal and Diesel detailed proposed contract requests, which “…included the right to swap a model’s face with another using AI; the creation of a digital clone with no additional compensation to the model; and the right to use images of a model’s body to train AI. The terms in the unsigned contracts also included broad legal language that could effectively give a brand leeway to use AI however it wanted.”[14] Some companies are looking to use A.I. repurpose or modify existing models, “others are using fully AI-generated models, not based on existing humans.”
The growth of A.I. in the fashion industry is hitting modeling agencies hard, “…seeing bookings decline, photo studios are closing and models are facing the loss of a chunk of their livelihoods: photo shoots by fast-fashion retailers constantly adding new collections to their websites.”[15]
The main reason that some firms are using A.I. for product promotion is to save money. Using A.I. to replicate their models allows for retailers “…to endlessly rework and redeploy a model’s image wearing different outfits at a fraction of the cost of new shoots.”[16]
An example of this benefit was the fashion retailer About You launching “…its Scayle Studios business, which creates digital imagery for other retailers using AI-generated models and promises a more than 90% production-cost reduction. Scayle has 130 brand clients and has generated 190,000 outfits in the last month…”[17]
This concern is amplified due to a lack of regulation to protect the livelihoods of models:
“Regulations globally haven’t kept pace with the threat to models’ livelihoods, but the New York State Fashion Workers Act is one exception. The law has made it illegal since June 2025 for brands to create or modify replicas of models without their explicit consent. ‘The misuse of models’ images is not new, but with AI that problem is accelerated tenfold,’ said Sara Ziff, founder and executive director of the New York-based nonprofit Model Alliance, which backed the legislation. Ziff, herself a model for years, pushes for similar laws in other states and federally.
The British Fashion Model Agents Association has drawn up an AI code of practice, including that AI can only be used with the consent of a model, who would own any digital twin. But BFMA head John Horner said that without binding regulation in Britain or Europe, models still risk being taken advantage of by less scrupulous agents. ‘A lot of young talents don’t fully understand the long-term consequences yet,’ said Staal, the Barcelona-based model agency director. ‘Signing away AI rights at 20 years old could still affect someone ten years later.’”[18]
FOOTNOTES
[1] https://www.nber.org/system/files/working_papers/w35437/w35437.pdf
[2] Ibid.
[3] Ibid.
[4] Ibid.
[5] https://www.medpagetoday.com/practicemanagement/informationtechnology/123393
[6] Ibid.
[7] Ibid.
[8]https://www.science.org/content/article/amid-flood-ai-advances-astrophysicists-are-questioning-soul-their-field
[9] https://www.cfa.harvard.edu/people/cecilia-garraffo
[10]https://www.science.org/content/article/amid-flood-ai-advances-astrophysicists-are-questioning-soul-their-field
[11] Ibid.
[12]https://www.reuters.com/legal/litigation/fashions-ai-era-face-swaps-digital-clones-2026-10-27/?utm_source=Sailthru&utm_medium=Newsletter&utm_campaign=Daily-Briefing&utm_term=102726&utm_content=102726&lctg=62fb99802babb15cdc0a4365&user_email=811ed8b292600ce981aafdcd541b60691ac1c024c7d281dc8621f11e98498b52
[13] Ibid.
[14] Ibid.
[15] Ibid.
[16] Ibid.
[17] Ibid.
[18] Ibid.