* From expansion in output to contraction in jobs

Preliminary research on the phenomenon of “jobless growth” in advanced economies and its repercussions in the Arab region

General introduction: The paradox of growth without employment
In recent years, advanced economies have witnessed a remarkable phenomenon of achieving high rates of economic growth without creating new jobs at the pace that was supposed to accompany this growth.
While GDP increases, driven by the development of knowledge and innovation economies, the need for human labor declines as a result of the entry of automation and artificial intelligence into production, management, and service lines.

Reports by the Organization for Economic Co-operation and Development (OECD), the World Bank and McKinsey have shown that automation has led to a rise in labor productivity by more than 10% in some sectors, offset by a decline in employment of about 2% during the first year of the introduction of the new technology.
At the same time, the gap is widening between high-skilled jobs, which are experiencing significant growth, and medium- and low-skilled jobs, which are at risk of decline or displacement.

This means that economic growth is no longer a guarantee of expanding job opportunities as it was in the past. Rather, it may sometimes be associated with the phenomenon of “jobless growth,” the effects of which are expanding in the United States, European Union countries, and even in emerging economies such as India.

Reasons for the phenomenon: the knowledge economy and the automation revolution
The essence of the phenomenon is due to the structural transformation in the nature of production, as growth no longer depends on employing a larger number of workers as much as it depends on improving efficiency and productivity through technology.
Robots and intelligent systems have led to the widespread displacement of human labor, especially in repetitive industrial and service sectors, while new job opportunities have moved to the fields of programming, data analysis, artificial intelligence, and renewable energy – fields that require high skills that are only available to a limited percentage of the workforce.

The McKinsey Global Institute report, titled Jobs Lost, Jobs Gained, showed that advanced economies will see a loss of between 10% and 25% of traditional jobs by 2030, offset by growth in new jobs that depend on knowledge and technology, but at a rate that is not sufficient to compensate for the loss.

Vision Dr. Maan Al-Qatamin: Redefining the relationship between growth and unemployment
Dr. Maan Al-Qatamin confirms in his talk that the historical relationship between economic growth and low unemployment has changed radically.
The higher the rates of automation due to artificial intelligence, the greater economic growth, but without being accompanied by an increase in employment rates.
He describes this phenomenon as a reflection of the new era that has transcended classical concepts in economics, which assumed that growth was the natural path to expanding employment opportunities.

Today, he explains, growth no longer results from the expansion of the labor base but from productivity leaps achieved by smart systems, robotics and predictive analytics.
Artificial intelligence increases the efficiency of companies, reduces costs, and doubles profits, but in return it reduces the need for humans in many operational processes.

Dr. believes This transformation means that governments and societies must reconsider the philosophy of development themselves: instead of focusing only on indicators of overall growth, the quality of growth must be looked at – that is, the extent of its ability to generate real and sustainable job opportunities that contribute to social justice and maintain economic balance.

Social impacts and challenges
These shifts lead to a set of new challenges:
– The widening income gap between highly skilled people and workers in traditional sectors.
The share of wages in GDP has declined in most developed countries.
– The escalation of social and class inequality as a result of the concentration of returns in the technology and knowledge capital sectors.
– Changing consumption and work patterns, as flexible jobs and remote work spread, while stable job opportunities shrink.

These indicators re-ask a fundamental question about the human future in the artificial intelligence economy, and about the role required of governments in restoring the balance between economic efficiency and social justice.

Lessons for the Arab region and Jordan
Although the phenomenon is clearly evident in advanced economies, its resonance is beginning to be felt in the Arab region, especially in countries that have adopted digital transformation programs.
In Jordan, which seeks to increase growth by transitioning to a knowledge and innovation economy, understanding this phenomenon is necessary to avoid repeating the Western experience.

The growth required is not only in numbers and indicators, but in employment opportunities and local skill-based production.
This requires adopting balanced policies that include:
– Rehabilitation and training programs (Reskilling & Upskilling) for workers affected by automation.
– Promoting entrepreneurship and small technology-based projects.
– Developing smart social safety networks to keep pace with changes in the labor market.

Developing smart social safety networks
The profound transformations brought about by automation and artificial intelligence in the labor market call for a redefinition of the function of the social state. The traditional concept of social safety nets – which is based on supporting poor or unemployed groups – is no longer sufficient in the face of the structural transformations that affect the middle class itself, and reshape the balances of work, income and production.

From here, the idea of ​​smart social safety networks emerged, that is, systems that employ data, digital technologies, and artificial intelligence to ensure fair distribution and targeting, and to transform support from a tool for relief into a tool for human economic and cognitive empowerment.

Smart grids are embodied in three interconnected dimensions:

1. The digital dimension – precise and transparent targeting
Modern networks are built on unified databases that include income, work, health, and education, so that the groups affected by automation can be identified with high accuracy, and support can be directed to them quickly and effectively.
Digital ID systems and analytical intelligence can be employed here to dynamically estimate the needs of each family or individual.
This model ensures that assistance reaches the real beneficiaries without wastage, and prevents duplication of support or tampering with beneficiary records.

2. The economic dimension – from subsidy to empowerment
The purpose of smart grids is not only to compensate for losses, but to transform the beneficiary into a productive contributor.
Therefore, financial support should be integrated with vocational rehabilitation programs and digital skills training, allowing the unemployed to move to new jobs in the knowledge economy.
In other words, social security becomes a means to prepare a person to return to the market and not to remain outside it.
In this context, social investment funds could be established, financed by the government and the private sector, to cover the costs of training and professional transformation.

3. Social dimension – protecting human capital
Smart grids go beyond the idea of ​​“aid” to become a tool for protecting national human capital.
In the face of increasing automation that may threaten social cohesion, these networks contribute to preserving the middle class as a pillar of stability.
It also allows for the construction of a national database that helps decision-makers design policies directed towards enhancing equal opportunities and mitigating the effects of technological disparity between generations and regions.

Towards a Jordanian model for smart social security
In the Jordanian context, this idea can be translated into practice by developing the national aid system to transform it from a support tool into a digital human development platform, incorporating:
– Employment, education and training data to link beneficiaries to realistic economic opportunities.
– Multidimensional poverty indicators that include income, housing, skills, and access to technology.
– Early warning systems to identify groups at risk of losing their jobs due to digital transformation or the decline of traditional sectors.
– Partnerships with the private sector to provide training and employment paths within the new economy.

Smart social security in this sense not only addresses poverty, but also manages the risks resulting from technological transformations, and ensures that social justice remains present at the heart of the knowledge economy.

What we are witnessing today is not just an economic transformation, but a cultural transformation that redefines the role of man in production. As growth accelerates due to artificial intelligence, a fundamental question arises: Are we progressing economically while regressing humanly? The answer depends on our ability to transform automation from a threat to jobs into an opportunity to rebuild the work and knowledge system on more equitable and innovative foundations.