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THE FUTURE OF WORK: NAVIGATING THE IMPACT OF AI AND AUTOMATION
ON EMPLOYMENT
Murodjon Sagdiddinov
University of World Economy and Diplomacy, student, Tashkent, Uzbekistan.
https://doi.org/10.5281/zenodo.15252757
Abstract. This article analyzes the progression of industries with respect to technology
and how it has both displaced and created new job opportunities. Moreover, it explains how AI
and automation would go on to shape the future of humanity. As history has shown us, with every
technological revolution, there arise new opportunities. However, unemployment arises as an
outcome of non-competitive, low-skilled labor segments being automated. With the aid of current
procedures combined with historical practices, it aids in the understanding of technology-
induced wage imbalances and inequality. There are geospatial gaps, as well. Advanced
economies come across retraining gaps, whereas underdeveloped economies face slow tech
adoption issues. This article is a reminder regarding the educational policies that need to be
tackled alongside skill development while suggesting radical changes to the construction of
educational frameworks and stratified training methodologies. It will foster skill development
concerning the enhancing job market. Incorporating these measures will help lessen the impact
of the technology gap and promote smooth skill development for all ahus ensuring prosperity for
all in the ever-agile work environment.
Keywords: artificial intelligence, automation, labor market, job displacement, skills gap,
economic inequality, policy solutions.
БУДУЩЕЕ РАБОТЫ: ИЗУЧЕНИЕ ВЛИЯНИЯ ИИ И АВТОМАТИЗАЦИИ НА
ЗАНЯТОСТЬ
Аннотация. В этой статье анализируется развитие отраслей в отношении
технологий и то, как они вытесняют и создают новые рабочие места. Более того, в ней
объясняется, как ИИ и автоматизация будут формировать будущее человечества. Как
показала нам история, с каждой технологической революцией возникают новые
возможности. Однако безработица возникает в результате автоматизации
неконкурентоспособных, низкоквалифицированных сегментов труда. С помощью
текущих процедур в сочетании с исторической практикой это помогает понять
дисбаланс и неравенство в заработной плате, вызванные технологиями.
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Существуют также геопространственные разрывы. Развитые экономики
сталкиваются с пробелами в переподготовке, тогда как слаборазвитые экономики
сталкиваются с проблемами медленного внедрения технологий. Эта статья является
напоминанием об образовательной политике, которую необходимо решать наряду с
развитием навыков, предлагая при этом радикальные изменения в построении
образовательных структур и методологий стратифицированного обучения. Это будет
способствовать развитию навыков, касающихся расширения рынка труда. Внедрение
этих мер поможет уменьшить влияние технологического разрыва и будет
способствовать плавному развитию навыков для всех работников, обеспечивая
процветание для всех в постоянно гибкой рабочей среде.
Ключевые слова: искусственный интеллект, автоматизация, рынок труда,
перемещение рабочих мест, разрыв в навыках, экономическое неравенство, политические
решения.
Introduction
The world of work and its demands are now evolving more quickly than ever due to the
development of new artificial intelligence (AI) and automation technologies. Machines
performing cognitive and manual work which historically has been the domain of humans have,
for a long time, been considered pure speculative fiction. Its reality, however, exists and growing
economic might. It changes and creates new business opportunities and new tasks for the
workforce, from robotic arms on assembly lines to algorithms that code, determine
creditworthiness and much more.
AI is the technological emulation of human intelligence through the use of algorithms
powered by data that change according to real-world outcomes. Automation covers both tangible
systems like robotics and intangible processes like AI-powered analytics and chatbots. Together,
these tools make it possible to limit human input in mundane, repetitive tasks and some
moderately complex tasks.
The World Economic Forum's Future of Jobs Report states that by 2025, automation and
artificial intelligence will eradicate approximately 92 million employment positions worldwide.
However, a net gain of 170 million jobs is estimated to be created as well [2]. This
paradox means that some roles are being eliminated while new jobs are simultaneously being
created as a direct result of the technology causing the disruption.
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As noted in Brynjolfsson and McAfee's book, The Second Machine Age, these shifts
reflect previous technological transformations, but the rapid intensity and breadth of change we
are witnessing is unparalleled in history [1].
The social dimension and policies as well as economics form another critical area to
analyze the scope and factors of the labor reshuffle. With the continuous advancement of
research in economics, along with real-life events, this piece tries to shed light on the impact
automation and artificial intelligence have on the contemporary global workforce. Data-driven
answers will be provided on what regions are most susceptible to risk, the modifying geography
of job creation, the evolving nature of education policy, and how all of this is changing at
dynamic rates.
The concern that arises out of machines advancing at a rate faster than humans being able
to adapt is: How can equity, in relation to the current technological landscape, be achieved in a
broader societal context?
Historical Context
From the beginning of time, innovation has always had an impact on the economy and
productivity, resulting in both positive and negative outcomes in regard to work. A great
example would be the Industrial Revolution, which featured mechanization on a wide scale and
suppressed agricultural work, leading to an abundance of factory-based employment. Agrarian
employment had to adapt to the adopted practices of mechanization. Then, towards the end of the
20th century, computers made an appearance, automating an incredible number of menial tasks,
services, and even manufacturing processes, which further advanced productivity.
The consequences of these past shifts have been profoundly impactful when considering
how AI and automation are modifying work nowadays. These technologies have changed the
frameworks of today’s societies. The first wave of industrialization introduced steam as well as
mechanized tools. The employment of these tools was shown to increase efficiency. However
this progress spat in the face of traditional anthropocentric labor structures because a lot of
manual work was displaced by machines, meaning, like in modern times, unskilled workers were
suffering from everything being taken from them. There was a glimmer of hope though. These
new, resistance industries, led to incredibly new jobs which changed the entire world [3].
In the early 20th century, changes in technological innovations deeply influenced work
relations. The use of electric power as well as the introduction of mass production created a need
for managers, machine operators, and maintenance workers.
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All of this created further economic expansion and increased productivity. However, the
need for reinvented labor was initiated. While they enabled repetitive tasks to be automated,
which made life easier, there was a constant struggle between the elimination of low-skilled job
positions and job opportunities available. The central conflict in work history is the permanent
juxtaposition of technological advancement of work processes and employment opportunities,
which can also be observed in the debate on the effects of AI today.
Focusing on the most recent advances in technology, at the end of the 20th century and
the beginning of the next, the introduction of digital technologies and the internet further
increased the possibilities of automation in the workplace. Computers and software technology
were able to execute numerous functions in finance, logistics, and even customer support, which
lowered the need for certain office staff. At the same time, whole new branches of the economy
were created such as IT services, e-commerce, and data analysis. This “creative destruction”
phenomenon was certainly characteristic in the tech-induced economies of the last century,
where old branches of industry were replaced by new, progressive, and innovation-driven sectors
[4]. This latest surge of AI and automation builds off these earlier revolutions with greater
sophistication and potential disruption. This time, AI is different—it can learn and adapt, making
it particularly suited to activities that require human-level reasoning and thinking skills. As has
been the case historically in the technological evolution of progress leading to new displacement
and creation of employment opportunities, now there is an amplification in such phenomena due
to AI’s unparalleled ability to perform intricate tasks in mid-level and advanced positions within
healthcare, finance, and transport.
Economic experts like Acemoglu and Restrepo argue that while automation has
traditionally led to the loss of certain job functions, it has done so in order to create new work
and industries. At the same time, they believe the current wave of AI-led automation could pose
unique hardships, especially for low- to mid-tier skilled positions. For one, advanced AI
technology increases the demand for human workers who can successfully pair their skills with
properly programmed systems, demand for labor subsequently shifts to more specialized and
skilled technical work [4].
To sum up, the past has shown us how technological revolutions disrupt the labor
markets. However, it has shown us how these revolutions contribute to new industries and
productivity growth.
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Understanding these patterns exposes the transformation AI and automation have caused
in the labor markets to shift, drawing both risks of innovation alongside new jobs, and job
displacement.
Current Trends in AI and Automation
The implementation of artificial intelligence (AI) and automation-driven technologies is
transforming the contemporary industry landscape across the globe. Productivity, as well as new
efficiencies and capabilities that were once thought of as impossible, are being achieved. Tasks
such as natural language comprehension, image categorization, and decision-making that require
the cognitive capabilities of a human are now being executed by AI systems. On the other end,
automation continues to shine perpetually in repetitive, rule-bound tasks, enabling employees to
concentrate on the strategic or creative aspects of their work.
A considerable surge in the adoption of automation and AI technologies has been noted
in businesses like manufacturing, health care, retail, and logistics in the past few years.
Autonomous delivery vehicles, for example, are already being used to cover last-mile
logistics and eliminate the requirement of human drivers in some situations [5]. In retail, queries,
and transactions can now be handled by powered customer service bots, enabling companies to
service patrons at all times without human employees needing to be present. Medical diagnostics
are also greatly aided by AI in the healthcare industry, greatly speeding up the disease detection
process, and increasing accuracy for radiology scans and even genetics examinations [6].
The use of these technologies is enabled by the current developments in machine
learning, data analytics, and the availability of powerful computing resources. These days, AI
systems can analyze massive datasets in real-time, which means that most businesses can now
make faster and more informed decisions. As an example, in the manufacturing industry, AI-
based robots can now complete intricate assembly processes usually performed by human
workers with even greater accuracy, which leads to a dramatic increase in productivity and a
reduction in mistakes. This form of automation is also emerging in other industries such as
agriculture, where AI is used in precision farming to improve yields while minimizing the use of
resources [5].
As AI and automation technologies improve, they are beginning to expand further into
areas previously thought to be too intricate for machines to handle. AI is being deployed in the
creative parts of technical fields, such as music composing, art creation, and even journalism,
where algorithms are capable of writing articles or creating media content using data based on
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algorithms [6]. This has resulted in the development of “cobots” which are collaborative robots
that assist humans in performing tasks in order to become more productive. A lot of industries
are beginning to realize the possibility that humans and machines can now work together more
effectively than previously thought.
As AI technology progresses, the fears associated with it replacing jobs are growing. For
instance, McKinsey in 2017 pointed out that automation greatly improves productivity.
However, it can also lead to changes in employment opportunities that will heavily affect
low-skilled positions [5]. AI and automation will most likely threaten employment opportunities
in sectors that require monotonous and physical work, which places workers from these
industries at greater risk of losing their jobs. Contrary to the worrying outcomes, McKinsey
continues to state that in general, the impact on employment depends on how businesses and
governments act. These steps include re-skilling employees and creating more positions, which
will help minimize the negative impacts [5]. In addition to those, new opportunities will arise.
Positions that are expected to be in high demand include specialists in artificial
intelligence and machine learning, security analysts, software developers, and data analysts.
Many of the opportunities are a result of the rapid developments in artificial intelligence
and digital transformation. The following graph illustrates the top fastest-growing jobs [7]:
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Geographic Impacts
The effect of AI and automation technologies is not consistent with the difference in
development in individual countries. In economically advanced countries, with their
sophisticated infrastructure and skilled personnel, the application of AI and automation
technology integrated into industries is often more advanced. However, in developing countries,
due to their low infrastructure, resources, and education systems, the pace of adoption for such
technologies may be slower and result in different challenges and opportunities.
In developed nations, especially members of the Organisation for Economic Co-operation
and Development (OECD), automation is enhancing industries that have historically depended
on low-skill labor. For example, in the United States and Western Europe, automation is well
adopted in the manufacturing, retail, and service industries, where activities like data entry,
customer interaction, and simple assembling are increasingly performed by machines [8].
Despite the substantial gains in productivity, these nations also face increased
unemployment in vulnerable low-skill jobs. The OECD further explains that the USA, Germany,
and Japan are facing a labor market contraction in middle-skill jobs due to task automation.
These countries have struggled to retrain their workers, trying to cope with the gap in
skills caused by the automation shift.
In the previous paragraph, we looked into how developed countries are responding to
rapid technological advancement or increased globalization. In contrast, developing countries
face a different kind of challenge. For instance, an increase in automation may spell doom for
jobs in low-wage, labor-intensive sectors. However, it may also provide an opportunity for
countries with lower labor costs to forego older, inefficient technologies. Take northern Africa
and parts of Southeast Asia for STU, where automation could enhance productivity within
agriculture and manufacturing, helping to improve living standards and reduce poverty. Of
course, these possibilities depend on the ability of governments to invest in education and
supportive infrastructure for changing technologies [9].
The geographic gaps caused by AI and automation differentiate even more when
analyzing the areas with distinct economic development levels. As Automation enhances
productivity, developing economies may benefit financially. These countries, however, stand to
lose the most in internal labor displaced within manual agricultural work and the textile industry
(World Bank, 2019). The International Labor Organization (ILO) has remarked that in gig and
remote work formats, digital labor platforms are providing job opportunities in emerging
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economies, making these jobs accessible because of their convenience. Less developed
economies also suffer from low pay and job instability provided through these platforms [10].
The influence of AI and automation on employment opportunities parallels the economic
disparities across regions. Expansion of automation technologies in affluent countries might
result in increased productivity, but these benefits are rarely shared across all socioeconomic
classes. On the other hand, developing countries stand to reduce the gap in labor productivity
with the adoption of AI and automation, but only with significant investment in education,
infrastructure, and supportive policies.
Without social safety nets, the automation threat is aggravated in developing countries. In
wealthier countries, protective measures like unemployment compensation and retraining
programs offset the impact on affected employees. On the other hand, many workers in
developing countries lack these protections, which increases the risk of an economic no man's
land due to automation. These unsupported individuals, as noted by the OECD, would aggravate
automation-induced poverty and inequality due to the absence of gap-supporting mechanisms for
social aid.
Skills Gap and Education
The most difficult problem to resolve with the evolution of AI technology and automation
is the growing imbalance between available job positions and displaced workers trying to fill
them. There will still be many new jobs that need to be filled but more advanced automation and
AI systems will need more skilled workers. This is a critical weakness in reaping the benefits of
AI and automation.
Healthcare, manufacturing, and IT sectors face the most acute skills gap as a result of
these new technologies. For example, in the manufacturing sector, with the assistance of
machines and robots, repetitive tasks are becoming increasingly automated, while the demand
for workers capable of designing, operating, and maintaining systems is rising. Also, AI
diagnostic tools and robotic surgeries require practitioners who specialize in training AI units,
machine learning, and data science [11]. To maneuver technologically advanced work processes,
employees in these domains need comprehensive domain and upper-level technical
qualifications.
The skills gap is a critical concern to help displaced workers adjust to new roles. It can be
addressed with an integrated strategy for education and training, which in turn can be broken
down into specific approaches.
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First, any new initiatives targeted toward reskilling aid workers in transitioning toward
new job openings. In the World Economic Forum’s report, it was noted that programs
emphasizing both hard and soft skills, including problem-solving, digital literacy, and
communication, are optimally beneficial in enabling workers to perform future roles [12]. For
instance, individuals losing low-skilled positions in the manufacturing sector can be retrained to
enter more technically skilled fields such as data analysis, software development, or even digital
marketing.
The shift in technology has made lifelong learning crucial in this era. As AI and
automation develop, employees need to improve their skills on a regular basis to maintain their
standing in the job market. The OECD’s Skills for Jobs database highlights the importance of
fostering a culture of lifelong learning where workers can access training throughout their
careers [11]. This approach enables employees to be flexible and robust in dealing with job
displacement while still meeting the demands of an evolving economy.
A still underappreciated aspect of educational institutions is that they are meant to ‘raise’
a new brand of employees capable of dealing with the challenges posed by AI. It is important
that students acquire digital literacy, as well as technological competencies, at the primary,
secondary, and tertiary levels of education. UNESCO advocates for the education of learners for
digital transformation, meaning the ability to work with AI and such technologies should be a
part of the education framework [13]. Educational institutions can tackle the skills shortage by
reinforcing STEM education and teaching AI-related subjects at earlier stages, thus ensuring
ample provisioning for the labor market.
Lastly, one cannot simply ignore the impact of businesses on the solutions of the skills
gap challenge. Businesses are taking on more and more responsibility to ensure that their
employees undergo continuous professional development. Companies can enable ai-ready
workers through cooperation with educational institutions and the provision of in-company
training courses tailored to the participant’s needs. The success of initiatives like SkillsFuture in
Singapore shows how employers, governments, and educational institutions can be brought
together to develop good strategies for skills provision. [14]
Economic and Social Implications
The introduction of AI and automation bears extensive economic and social impacts that
are already evident throughout the world’s labor markets. Some of these effects are greater wage
polarization, increasing inequality, expansion of gig work, and the effects on mental health and
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job security. Automation, along with the AI revolution, is transforming industries at an
unprecedented pace. However, these advancements come at a cost, as their benefits are not
equally accessible to everyone, resulting in profound socio-economic difficulties.
One of the most prominent economic effects of AI and automation is wage polarization.
With the automation of low-skill roles, like those in manufacturing and retail, workers in these
industries are either displaced or pushed down into low-wage gig economy jobs. At the same
time, highly skilled professionals, especially those in data science, software engineering, and AI
research, have greater demand placed on their skills and therefore receive higher wages [15].
This shift contributes to the increasing imbalance in the wage gap between high-skill and
low-skill workers and adds to the rising income inequality.
With AI steadily transforming the landscape of employment opportunities, it is
imperative to analyze how some industries will offset job creation against job losses. The
following graph depicts projections on the shifts in employment opportunities from 2017 to 2037
for different sectors [16].
Autor (2019) claims that the “hollowing out” of the middle class—a phenomenon where
manual and cognitive work is increasingly automated—polarizes the economy. The middle-skill
employment strata bear the largest brunt of this trend because their work can be automated and
demand for their skills is not increasing.
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Workers that fall into the lower and middle-skill category face wage stagnation or
devaluation while those in the upper-skill category continue to have their wages increase,
resulting in greater wage disparity.
Not only has wage polarization changed as a result of AI, but so has the expansion of the
gig economy. Companies are now able to automate and depend on freelance, part-time, and
contract workers instead of full-time employees to take care of repetitive business functions
previously handled by full-time staff. Primarily, this shift can be observed in some industries
including transportation (ride-hailing), logistics, and digital services. While this flexibility may
be appealing to some workers, it comes with a new set of problems such as lack of job stability,
minimal benefits, and erratic income streams. As noted by the International Labor Organization,
the gig economy is increasingly on the rise in both developed and developing economies and
tends to create weak employment standards for those who largely lack the security associated
with conventional employment contracts [10].
Apart from the economic factors, AI and automation rethink the reality of social issues,
including mental health concerns and job security. Workers' perceptions of the future validity of
their positions are accompanied by anxiety regarding the possibility of redundancy or
displacement, which is becoming more common. Sustained anxiety around the possibility of
automation replacing roles, particularly in low-skill jobs, can significantly erode one’s socio-
psychological self-esteem and social identity. The consequences of losing a job, especially one
that has served as the mainstay of a household or community, can greatly impact a person’s
mental health [15]. The social identity theory stigmatizing involuntary idleness or
underemployment leads to withdrawal, loneliness, and depression, further complicating the
plight of displaced workers. Furthermore, the increasing speed of technological advancements
adds another layer of complexity in terms of how society adapts to these changes. While some
groups may adapt to newer technologies almost instantly, older workers and those with less
educational access tend to lag behind. This lack of access to newer technology and additional
opportunities can create socio-economic divides. Those who are left behind will eventually
suffer from reduced social status and an overall lower quality of life.
As policies attempt to catch up with the needs of society, policymakers have to manage
these poignant issues by addressing the fragmentation of opportunities and ensuring equitable
development across regions to foster social cohesion.
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Some of these policies may be oriented towards securing a living wage and minimal
employment protections in addition to access to social safety nets for gig economy workers.
Furthermore, such policies should address labor market dynamics by facilitating
employment-based training and reskilling programs necessary to meet the evolving job market
demands. The following table summarizes important metrics on the effects of AI on employment
trends across different industries and the continued focus worrying many in society's sectors
[17]. The following table summarizes important metrics on the effects of AI on employment
trends across different industries and the continued focus worrying many in society's sectors. It
illuminates the twofold effect of AI and automation regarding the loss of existing jobs as well as
the creation of new opportunities. Important metrics include the AI-related job opening growth
rate, the percentage of workers worrying about job loss, and the industries exposed to the
greatest potential disruption. This information highlights the need for policies and reskilling
efforts to tackle issues arising from technological progress shifts in the employment landscape.
In addition, these trends are critical for constructing appropriate training programs to equip
prospective employees with the required skills in growing fields. With strengthened partnerships
among industries, governmental bodies, and educators, society will be better positioned to face
the challenges of this shift.
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Summarizing the above, the most salient points are that though AI and automation have
the potential to increase the productivity of a workforce economically, the accompanying
challenges should AI come without risk. These include the displacement of workers. A greater
focus on policies that promote support as well as social safety nets dedicated to addressing the
increase in inequality and the growth of the gig economy is crucial. Mental health challenges
associated with the shift also require essential attention, as does the need for policies to reconcile
the gaps in support and training alignment.
Policy Responses
The introduction of AI coupled with automation is a prominent issue country all across
the globe are facing when it comes to labor markets, and policymaking can greatly reduce the
complications brought on by such technologies while simultaneously enhancing their
advantages. Policies such as Universal Basic Income (UBI), robot taxes, job guarantees, and
educational reforms aimed at preparing the workforce for an automated world are being
proposed or even implemented in countries all over the world. Steps are being taken by
Singapore, Germany, and Nordics to tackle the socio-economic burden imposed by technological
disruption.
One of the most widely discussed policy solutions is Universal Basic Income (UBI). The
reasoning behind UBI is to extend a basic form of income to every citizen and provide a healthy
standard of living sustained even if there is no employment in the era of automation where jobs
are being removed on a large scale. Supporters of UBI say that it can act as a form of financial
protection for all, enabling workers to afford to pause work while they transition or reskill to take
on less automatable jobs. Although UBI has not been fully adopted on a large scale, trials
conducted in Finland and other countries tend to support UBI on the grounds of employee
contentment, overall well-being, and after negative health impacts of the pandemic even if the
macroeconomic consequences are uncertain [14].
An additional recommended policy centers around the implementation of a robot tax,
which seeks to impose a levy on companies that substitute human employees with robots or
automated processes. As a result, funds that would come from this tax could be used to pay for
social programs, retraining programs, and even aid for the economically displaced. Even though
no country has implemented a robot tax, its concept is highly debated everywhere automation
and its economic impact are discussed.
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The European Commission has suggested the development of AI ethical guidelines
proposing the use of taxation, among other measures, as social automation impact management
tools [19]. On the other hand, it is argued that implementing a robot tax could hamper the
technological advancements that most benefit society.
Having job guarantees is one solution that has been brought up to mitigate the negative
impacts of automation. A job guarantee will ensure every individual who is willing and able to
work has a meaningful job, even if they are automated out of a certain position. This policy
could mean providing jobs directly through the government, such as in infrastructure and care
work because those areas are less likely to be automated. This idea has received support from
many different economists, especially those who support a “green new deal,” which seeks to
address unemployment while protecting the environment. Although a job guarantee yields full
employment, it would entail large expenditures and require a concrete plan to be useful [18].
Alongside these policies, other countries are working on educational reforms to align
with labor market needs. An example of such an adaptive education policy is Singapore’s
SkillsFuture initiative. This program promises to assist the citizen’s skill development
throughout their careers by accreting training grants, offering online courses, and conducting
various skill development workshops. This initiative has been successful in creating a more
adaptable workforce and has become increasingly important in the context of rapid technology
shifts [14]. In the same way, Nordic countries have also adopted comprehensive policies for
social security and active retraining for displaced workers.
In addition to retraining programs, governments need to enhance digital competencies at
all educational levels. As UNESCO (2021) shows, skills such as basic coding, data analysis, and
AI application are requisite in the current epoch and need to be taught in schools. Through the
provision of instructional frameworks and embedding them in the syllabus, governments can
better equip the later generations to deal with skills of the future, thereby minimizing the
possible widening skills gap [13].
To recapitulate, the challenges posed by AI and automation are considerable, but
adopting certain policies could help alleviate some of the risks. Universal Basic Income, robot
taxation, job guarantees, and reforming the educational system are some approaches that can
enhance worker protection and preparedness for the changing work environment. The
effectiveness of these policies will rest on the ability of the governments to cope with strong
technological shifts and spend on the future of their people.
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A combination of economic guarantees, proactive education, and work policies would
provide a balanced strategy to ensure that AI and automation can be advantageous to all.
Conclusion
There are powerful opportunities for AI and automation alike in the productivity and
innovation realms. We must also remember, however, that there are significant risks. Workers
may lose their jobs, and pay inequality among low-skill and high-skill workers will sharpen.
Other consequences of these technologies include greater inequality, the expansion of gig
jobs, and mental health issues associated with job instability.
These problems will not fix themselves, and reactive policies addressing the worst effects
of automation will bring about the hoped-for change. Mitigating policies will help, but the lack
of inclusive growth balanced with proactive measures makes comprehensive change impossible.
To address the underlying issues, proactive policies anticipating future workforce needs
must be adopted to place the changes in motion. Focused and pragmatic policy must stress
restructuring education to incorporate digital skills, coding, and critical thinking at every
multidisciplinary level of school in every region. These measures will allow students and future
citizens to be prepared to adapt to a digitized and automated world.
Moreover, the global teaching policy frameworks need to be accelerated, especially for
those vulnerable to disruption like low-skilled workers in retail and manufacturing. Businesses
and governments must partner to establish an ‘evergreen’ learning system that provides
continuous training and promotes professional growth during active employment. Some training
programs such as those from Singapore SkillsFuture provide an actionable model on how to
build a responsive workforce and should be adopted and adapted for global implementation.
Aside from some training and education policies, we need to think outside the box and
consider policy innovations like Universal Basic Income (UBI). UBI is controversial but has the
potential to guarantee citizens access to a basic quality of life in the future when automation will
restrict employment opportunities. It would effectively enable manual workers to invest in their
education and retraining military opportunities without having to worry about jobs.
In addition, the impact of advancement in AI and automation on productivity
measurement calls for rethinking in the 21st century. Society must shift its focus to human
attributes, such as creativity, emotional intelligence, and social roles because those areas are
difficult for machines to take over. New forms of employment arising from the care economy, as
well as the creative industries, should be stimulated and subsidized.
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In addition to providing significant opportunities for workers, those sectors also meet
fundamental societal needs, which are expected to grow in the next few decades.
To conclude, the impact of AI on the future of work is not something set in stone. We
may influence the transformation through appropriate policies, investments in education, and
innovative approaches. We need to remove the divides between different sectors of society and
different age groups by encouraging innovation, promoting learning at any stage, and adopting
unconventional measures such as universal basic income (UBI) to ensure that the advancement
of technology benefits all workers.
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АND RESEARCH»
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