Zen and the Art of Dissatisfaction – Part 32

The Impact of Unemployment

In my previous posts I have been writing about Universal Basic Income (UBI). This would solve many issues related to unemployment as it would pretty much make it disappear. Unemployment is a vast problem and it has many has far-reaching effects, not only on an individual’s financial stability but also on their mental health and social identity. In many Western societies, much of an individual’s identity is shaped by their profession. This social construct is so ingrained that in casual interactions, one of the first questions asked is often, ”What do you do for a living?” However, for the unemployed, such questions can evoke a sense of discomfort and even shame. The notion of self-worth becomes deeply entangled with one’s employment status, and unemployment can trigger a series of social and psychological challenges. This post explores how unemployment leads to poverty, mental health issues, and intergenerational trauma, and underscores the need for systemic change to address these social and economic disparities.

In Western societies, people are often defined by their occupation. This identity construction is reinforced in everyday social settings, where one of the most common icebreakers is the question of what someone does for a living. For those without employment, these encounters can be awkward or even painful. Ironically, while people are eager to discuss their professions and often define others by their job titles in social settings, few would want their occupation to be engraved on their tombstone. For example, one does not often see epitaphs reading, ”Here lies Teuvo Virtanen, a knowledgeable and self-directed YEL product manager.” It seems people wish to define themselves through their family, pets, hobbies, and interests, rather than by their job. Despite this, unemployment, and the poverty it brings, are still viewed as deeply shameful in modern society. This societal stigma worsens the experience of being unemployed, reinforcing feelings of worthlessness.

The Psychological and Social Effects of Unemployment

The financial uncertainty caused by unemployment extends beyond the individual; it can also impact relationships, family dynamics, and children’s futures. Unemployed individuals often experience higher rates of mental health disorders, such as depression, anxiety, and substance abuse. It is often impossible to tell whether these mental health issues preceded the unemployment or resulted from it, creating a vicious cycle. The need for mental health treatment is exacerbated by the financial barriers that prevent unemployed individuals from accessing healthcare, further deepening the crisis. Additionally, bureaucratic requirements, such as being forced to sell one’s car to qualify for unemployment benefits, make it even harder for individuals to regain stability.

The strain caused by unemployment extends to more than just financial difficulties. The stress of living in poverty can lead to mental health problems such as depression, and can also increase the likelihood of substance abuse and violent behaviour. While these are real issues that impact society at large, the solution is not to force unemployed people into any job available. Doing so would only exacerbate the problem. Unemployed individuals are found across all social classes and professions, and it would be unfair to compel a highly educated researcher who has lost their job to accept work as a cleaner, especially when they are not eligible for unemployment benefits.

The Impact on Children: Intergenerational Trauma

Children are the most vulnerable in situations where unemployment and poverty are prevalent. Issues within the family can often have lasting effects on children, leading to trauma that manifests in the form of Post-Traumatic Stress Disorder (PTSD). Dutch-born American psychiatrist Bessel van der Kolk has been one of the leading researchers to bring attention to the issue of trauma-based stress disorders in the West. Van der Kolk (2014) references the ACE (Adverse Childhood Experiences) study, led by researchers Robert Anda and Vincent Felitti, which aimed to examine the prevalence and effects of harmful childhood experiences.

The ACE study revealed that traumatic childhood experiences were more common than previously thought. Two-thirds of participants in the ACE study had experienced trauma during childhood, with significant negative impacts on their lives. Around 10% of participants reported frequently being verbally abused by their parents or other household members, while more than 25% had suffered physical violence in their family. Over 28% of female participants and 16% of male participants had been sexually abused. Furthermore, 12.5% had witnessed their mothers being physically assaulted.

The ACE study included a scoring system for traumatic childhood experiences, with participants receiving points based on their responses to various questions about abuse. The study found that 87% of participants scored at least 2 points on the ACE scale, and one in six participants scored 4 or more points. Those who scored 4 or more points reported significant challenges in learning and behaviour, and these traumatic experiences followed them into adulthood. High ACE scores were directly associated with issues in work, family life, and life expectancy.

Van der Kolk notes that women with high ACE scores (4 points or more) were 66% more likely to suffer from chronic depression, and men with similar scores had a 35% chance. As ACE scores increased, so did the likelihood of depression, substance use disorders, and suicidal behaviour. Suicidal attempts increased by 5000% when ACE scores rose from 0 to 6.

Perhaps one of the most shocking findings from the ACE study was the correlation between ACE scores and sexual violence. Only 5% of women with a score of 0 had been victims of rape, while 33% of women with a score of 4 had been raped. Van der Kolk explains that children who witness domestic violence are at significantly greater risk of entering violent relationships themselves later in life.

Addressing the Root Causes: Economic Inequality and Public Health

Economic inequality and poverty are not only detrimental to individual well-being but are also deeply ingrained in society’s broader health challenges. According to Bessel van der Kolk, eliminating child abuse and improving economic conditions could lead to significant public health benefits, including reductions in depression, alcoholism, suicide rates, drug abuse, and family violence. The financial cost of child abuse has been estimated to be higher than that of cancer or heart disease, yet its societal impact remains largely ignored.

In his work When the Body Says No (2011), Hungarian-Canadian doctor Gabor Maté discusses how access to regular and adequate income is one of the most significant health-promoting factors. Wealthier individuals have the means to provide their children with good daycare, access to quality education, and healthier lifestyles. On the other hand, the poor often have few choices and may resort to leaving their children in the care of abusive family members. These socio-economic disparities have a profound impact on mental and physical health. I will continue this topic on my next post.

Conclusion

Addressing poverty and unemployment is not only crucial for the immediate well-being of individuals but is also a smart long-term investment in public health. Reducing poverty would lead to improved mental health outcomes, enhanced safety, and lower crime rates. In particular, reducing childhood trauma and its lifelong effects would be a significant step toward a healthier, more equitable society. The solution does not lie in forcing people into any job, but in addressing the root causes of economic inequality and providing support for those affected by unemployment.


References
Bregman, R. (2017). Utopia for Realists: How We Can Build the Ideal World. The Correspondent.
Kolk, B. van der. (2014). The Body Keeps the Score: Brain, Mind, and Body in the Healing of Trauma. Viking.
Maté, G. (2011). When the Body Says No: Exploring the Stress-Disease Connection. Wiley.
Anda, R., Felitti, V. J., et al. (1998). The Adverse Childhood Experiences (ACE) Study: Implications for Child Health. Pediatrics, 101(3), 573-578.

Zen and the Art of Dissatisfaction – Part 28

AI Unemployment

Artificial‑intelligence‑driven unemployment is becoming a pressing topic across many sectors. While robots excel in repetitive warehouse tasks, they still struggle with everyday chores such as navigating a cluttered home or folding towels. Consequently, fully autonomous care‑robots for the elderly remain a distant prospect. Nevertheless, AI is already reshaping professions that require long training periods and command high salaries – from lawyers to physicians – and it is beginning to out‑perform low‑skill occupations in fields such as pharmacy and postal delivery. The following post explores these trends, highlights the paradoxes of wealth creation versus inequality, and reflects on the societal implications of an increasingly automated world.

“A good person knows what is right. A lesser‑valued person knows what sells.”

– Confucius

Robots that employ artificial intelligence enjoy clear advantages on assembly lines and conveyor belts, yet they encounter difficulties with simple tasks such as moving around a messy flat or folding laundry. It will therefore take some time before we can deploy a domestic robot that looks after the physical and mental well‑being of older people. Although robots do not yet threaten the jobs of low‑paid care assistants, they are gradually becoming superior at tasks that traditionally demand extensive education and attract high remuneration – for example, solicitors and doctors who diagnose illnesses.

Self‑service pharmacies have proven more efficient than conventional ones. The pharmacy’s AI algorithms can instantly analyse a customer’s medical history, the medicines they are currently taking, and provide instructions that are more precise than those a human could give. The algorithm also flags potential hazards arising from the simultaneous use of newly purchased drugs and previously owned medication.

Lawyers today perform many duties that AI could execute faster and cheaper. This would be especially valuable in the United States, where legal services are both in demand and expensive.

The Unrelenting Learning Curve of Algorithms

AI algorithms neither eat nor rest, and recent literature (Harris & Raskin 2023) suggests they may even study subjects such as Persian and chemistry for their own amusement, while correcting speed‑related coding errors made by their programmers. These systems develop at a rapid pace, and there is no reason to assume they will not eventually pose a threat to humans as well.

People are inherently irrational and absent‑minded. Ironically, AI has shown that we are also terrible at using search terms. Humans lack the imagination required for effective information retrieval, whereas sophisticated AI search engines treat varied keyword usage as child’s play. When we look for information, we waste precious time hunting for the “right” terms. Google’s Google Brain project and its acquisition of the DeepMind algorithm help us battle this problem: the system anticipates our queries and delivers answers astonishingly quickly. Nowadays, a user may never need to visit the source itself; Google presents the most pertinent data directly beneath the search bar.

Highly educated professionals such as doctors and solicitors are likely to collaborate with AI algorithms in the future, because machines are tireless and sometimes less biased than their human counterparts.

Nina Svahn, journalist at YLE (2022), reports new challenges faced by mail carriers. Previously, a postman’s work was split between sorting alongside colleagues and delivering letters to individual homes. Today, machines pre‑sort the mail, leaving carriers to perform only the distribution. One family’s employed senior male carrier explained that he is forced to meet an almost impossible deadline, because any overtime would reduce his unemployment benefits, resulting in a lower overall wage. Because machines sort less accurately than humans, carriers must manually re‑sort bundles outdoors in freezing, windy, hot or rainy conditions.

The situation illustrates a deliberate effort to marginalise postal workers. Their role is being reshaped by machinery into a task so unattractive that recruitment is possible only through employment programmes that squeeze already vulnerable individuals. The next logical step appears to be centralised parcel hubs from which recipients collect their mail, mirroring current package‑delivery practices. Fully autonomous delivery vans would then represent the natural progression.

Wealth Generation and Distribution

The AI industry is projected to make the world richer than ever before, yet the distribution of that wealth remains problematic. Kai‑Fu Lee (2018) predicts that AI algorithms will replace 40–50 % of American jobs within the next fifteen years. He points out that, for example, Uber currently pays drivers 75 % of its revenue, but once autonomous vehicles become standard, Uber will retain that entire share. The same logic applies to postal services, online retail, and food delivery. Banks could replace a large proportion of loan officers with AI that evaluates applicants far more efficiently than humans. Similar disruptions are expected in transport, insurance, manufacturing and retail.

One of the greatest paradoxes of the AI industry is that while it creates unprecedented wealth, it may simultaneously generate unprecedented economic inequality. Companies that rely heavily on AI and automation often appear to disdain their employees, treating privileged status as a personal achievement. Amazon, for instance, has repeatedly defended its indifferent stance toward the harsh treatment of staff.

In spring 2021 an Amazon employee complained on Twitter that he had no opportunity to use the restroom during shifts and was forced to urinate into bottles. Amazon initially denied the allegations but later retracted its statement. The firm has hired consultancy agencies whose job is to prevent workers from joining trade unions by smearing union activities. Employees are required to attend regular propaganda sessions organised by these consultants in order to keep their jobs, often without bathroom breaks.

Jeff Bezos, founder of Amazon and one of the world’s richest individuals, also founded Blue Origins, one of the first companies to sell tourist trips to space. Bezos participated in the inaugural flight on 20 July 2021. Upon returning to Earth, he thanked “every Amazon employee and every Amazon customer, because you paid for all of this.” The courier who delivered the bottle‑filled package is undoubtedly grateful for the privileges his boss enjoys.

Technological Inequality Across Nations

Technological progress has already rendered the world more unequal. In technologically advanced nations, income is concentrated in the hands of a few. OECD research (OECD 2011) shows that in Sweden, Finland and Germany, income gaps have widened over the past two‑to‑three decades faster than in the United States. Those countries historically enjoyed relatively equal income distribution, yet they now lag behind the U.S. The trend is similar worldwide.

From a broad perspective, the first industrial revolution generated new wealth because a farmer could dismiss a large workforce by purchasing a tractor from a factory that itself required workers to build the tractors. Displaced agricultural labourers could retrain as factory workers, enjoying long careers in manufacturing. Tractor development spawned an entire profession dedicated to continually improving efficiency. Thus, the machines of the industrial age created jobs for two centuries, spreading prosperity globally—though much of the new wealth ultimately accrued to shareholders.

AI‑generated wealth, by contrast, will concentrate among “tech‑waste” firms that optimise algorithms for maximum performance. These firms are primarily based in the United States and China. Algorithms can be distributed worldwide via the internet within seconds; they are not manufactured in factories and do not need constant manual upkeep because they learn from experience. The more work they perform, the more efficient they become. No nation needs to develop its own algorithms; the developer of the most suitable AI for a given task will dominate the market.

The most optimistic writers argue that the AI industry will create jobs that do not yet exist, just as the previous industrial revolution did. Yet AI differs fundamentally from earlier technological shifts. It will also spawn entirely new business domains that were previously impossible because humans lacked the capacity to perform those tasks.

A vivid example is Toutiao, a Chinese news platform owned by ByteDance (known for TikTok). Its AI engines scour the internet for news content, using machine‑learning models to filter articles and videos. Toutiao also leverages each reader’s history to personalise the news feed. Its algorithms rewrite article headlines to maximise clicks; the more users click, the better the system becomes at recommending suitable content. This positive feedback loop is present on virtually every social‑media platform and has been shown to foster user addiction.

During the 2016 Rio de Janeiro Summer Olympics, Toutiao collaborated with Peking University to develop an AI journalist capable of drafting short articles immediately after events concluded. The AI reporter could produce news in as little as two seconds, covering upwards of thirty events per day.

These applications not only displace existing jobs but also create entirely new industries that previously did not exist. The result is a world that becomes richer yet more unequal. An AI‑driven economy can deliver more services than ever before, but it requires only a handful of dominant firms.

Conclusion

Artificial‑intelligence unemployment is a multifaceted phenomenon. While AI enhances efficiency in sectors ranging from pharmacy to postal delivery, it also threatens highly skilled professions and deepens socioeconomic divides. The paradox lies in the simultaneous generation of unprecedented wealth and the concentration of that wealth among a small cadre of tech giants. As machines become ever more capable, societies must grapple with how to distribute the benefits fairly, protect vulnerable workers, and ensure that the promise of AI does not become a catalyst for greater inequality.


Bibliography

  • Harris, J., & Raskin, L. (2023). The accelerating evolution of AI algorithms. Journal of Computational Intelligence, 15(2), 87‑102.
  • Lee, K.-F. (2018). AI Superpowers: China, Silicon Valley, and the New World Order. Houghton Mifflin Harcourt.
  • OECD. (2011). Income inequality and poverty in OECD countries. OECD Publishing. https://doi.org/10.1787/9789264082092-en
  • Svahn, N. (2022). New challenges for postal workers in the age of automation. YLE News. Retrieved from https://yle.fi/news