Fears About AI Taking Our Jobs: A Real Concern

Fears About AI Taking Our Jobs: A Real Concern

A mechanic working in a dimly lit garage, inspecting a car’s undercarriage with a portable light source. by cottonbro studio via pexels

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Fears about AI taking our jobs are understandable – but harmful

The UN’s flagship platform on artificial intelligence opened in Geneva in July 2025, launching four days of high-level dialogue, cutting-edge demonstrations and urgent calls for inclusive AI governance.  The event comes as autonomous and generative systems evolve faster than regulatory frameworks can keep pace.  Read more .  But all concerns about AI kept on regardless.  Read below.

Fears about AI taking our jobs are understandable – but harmful
Marko Aliaksandr/Shutterstock

Abigail Marks, Newcastle University

As a professor of the future of work, the question I get asked most often is whether AI is going to take everyone’s jobs.

I hear it from students who worry that their degrees will be obsolete before they graduate.  I hear it from office workers watching new tools appear in their software.  And I hear it from people working in retail and logistics and hospitality and admin, who all suspect that their jobs put them most at risk.

The issue has become a widespread worry in the workplace.  And of course, I understand why people are worried.

Because for a very long time, technology has been sold to employers as a way of achieving more with a smaller workforce. When new tech arrives, it often means cutting costs.

So far though, AI has not led to mass unemployment, and society’s use of the technology is, and will probably continue to be, nuanced and complex.

Yet blunt headlines declaring that “AI will take your job” are hard to ignore. And they can place workers in a passive position, where they end up waiting fearfully to see whether they will be part of the technological cull.

But we also need to be wary of the fear itself. For fear is not just a private and unpleasant feeling – fear changes how people behave and how they relate to society.

Nor is AI-driven anxiety evenly distributed. Some professionals with stable contracts will have the luxury of treating AI as an efficiency tool, something that removes tedious tasks and speeds up routine work.

But others, who work in call centres or data entry, where tasks are repetitive, measurable and tightly monitored, often see AI as something that could remove the substance of their job. For these people, the AI revolution does not feel like an upgrade, it feels like a countdown to unemployment.

And this is why the perceived threat matters. Because even before jobs disappear, the fear of losing them can reshape lives. Research shows that people who believe their livelihoods are at risk are understandably less willing to plan for the future.

They may delay major decisions because they feels pointless or unaffordable. They may disengage from work because they assume loyalty will not be rewarded.

Anxiety goes up, morale falls and the workplace becomes a site of uncertainty.
And then the idea that AI will take over jobs becomes not just an economic problem but also a psychological one.

For work is not simply a way to pay the bills. To many people it is a vital source of identity, dignity and social connection. And when work feels under threat, people can feel personally diminished.

Transparency

After all, if the tasks you have built your life around are suddenly described as something AI could do, it is hard not to infer that your efforts are (and have been) of little value; that you are replaceable and that your contribution no longer matters.

This is where fear turns into alienation, and its effects move beyond the workplace. Over time, that loss of trust can harden into cynicism about society itself.

Anxiety about automation can then blend into wider questions about inequality. And if millions of workers believe they are one software update away from redundancy, that belief can be socially destabilising.

Fears about AI taking our jobs are understandable – but harmful Woman looking thoughtful surrounded by tech graphic.
AI and alienation.
Stock-Asso/Shutterstock

What matters then is how AI is integrated into workplaces, and whether that integration supports people’s ability to keep working on fair and predictable terms. This requires transparency and the involvement of the workers themselves. Above all, it is essential to give those workers a say in how AI affects their tasks, their pace of work, and the metrics by which they are assessed.

Because while AI will reshape work, the future should not be predetermined by the technology itself. And the greatest risk may not be that AI replaces everyone overnight, but that the fear of replacement becomes widespread and corrosive – damaging wellbeing, undermining dignity and building resentment.

So we should absolutely take the threat of AI seriously. But we should also stop treating AI as an unstoppable force, and start treating it as something that can be shaped by society.

And the next time someone asks me whether AI is going to take people’s jobs, I will still answer honestly – that without proper consideration, there is a chance that systems will be implemented which change the way we work and damage personal dignity and economic stability.

But I will also try to address the more important question about what society can do to mitigate this damage – and make sure that the fear of AI doesn’t become a major crisis in itself.The Conversation

Abigail Marks, Professor of the Future of Work, Newcastle University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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Integrating Natural Cycles for Strategic Stability in MENA

Integrating Natural Cycles for Strategic Stability in MENA

Scenic view of Muscat’s traditional architecture against rugged mountains during the day. by Uğurcan Özmen via pexels

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Building a Climate-Resilient MENA: Integrating Natural Cycles for Strategic Stability

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20 February 2026

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Building a Climate-Resilient MENA: Integrating Natural Cycles for Strategic Stability

Image credit: Taghit oasis in Algeria, North Africa. By CIA World Factbook

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Climate change is no longer a peripheral environmental concern; it is redefining economic, social, and strategic balances across the MENA (Middle East and North Africa) region. Rising temperatures, prolonged water stress, extreme rainfall events, and growing pressure on agricultural systems demonstrate the urgency of a comprehensive, systemic response.

For MENA countries, these shifts go beyond ecology: they directly affect water, food, energy, and territorial sovereignty. Solutions cannot remain sectoral. A climate doctrine must integrate resource mobilization, agricultural modernization, energy diversification, and territorial planning within a coherent framework—one that anticipates rather than reacts, protects rather than repairs, and organizes rather than fragments.

Strategic Implications for the 21st Century

Sovereignty in today’s world extends beyond military and economic power. It now includes:

  • Water security
  • Soil resilience
  • Infrastructure stability
  • Energy autonomy
  • Territorial balance

Investments across the region—desalination, hydraulic modernization, agricultural support, and renewable energy deployment—are essential, yet insufficient alone. They must be embedded in a strategic architecture capable of anticipating climate trajectories over the coming decades.

From Fragmented Management to Systemic Integration

An integrated climate doctrine is based on a single principle: natural cycles are interconnected. Water, soil, vegetation, energy, and urban planning form a unified system, where action in one area influences the others.

  • Healthy soils improve water infiltration.
  • Better infiltration reduces flooding.
  • Fewer floods lower infrastructure costs.
  • Strategic vegetation reduces urban heat islands.
  • Intelligent energy management eases pressure on natural resources.

Strategic coherence arises from aligning these dynamics.

Water Security: Beyond Mobilization

MENA countries have strengthened water mobilization through dams, transfers, and desalination. Yet true resilience also depends on:

  • Aquifer recharge
  • Smart stormwater management
  • Watershed protection
  • Efficient irrigation

Traditional knowledge, particularly in oasis and mountainous regions, emphasizes slowing and infiltrating water. Integrating these time-tested practices with modern technology enhances investment effectiveness and supports sustainable water governance.

Food Security and Soil Health

Food security relies not only on production volume but also on system stability. Climate projections encourage policies that:

  • Adapt crop varieties
  • Increase irrigation efficiency
  • Preserve soil fertility
  • Diversify production according to agro-climatic zones

Degraded soils compromise water storage and reduce yields, whereas living soils act as natural insurance. Integrating climate intelligence into agricultural policy enhances productivity while reinforcing sustainability.

Energy and a Managed Transition

The MENA region has some of the world’s highest solar potential. Gradual energy diversification:

  • Strengthens strategic autonomy
  • Reduces dependence on fossil fuels
  • Opens industrial and technological opportunities

Transition is most effective when phased and aligned with national development priorities.

Urban Adaptation for the Future Climate

Urban centers concentrate population, infrastructure, and economic activity. Climate-resilient urban planning requires:

  • Integrated stormwater management
  • Urban cooling strategies
  • Improved building energy efficiency
  • Climate-informed spatial planning

Proactive planning reduces future costs and protects public investments.

Integrating Science into Governance

An effective climate doctrine depends on:

  • Systematic climate impact assessments
  • National resilience indicators
  • Strong intersectoral coordination
  • Structured scientific support

Universities, research centers, and technical institutions are essential partners in ensuring decisions are informed by robust data and analysis.

Economic and Social Opportunities

Resilience creates:

  • Skilled employment
  • Industrial development
  • Stabilized rural economies
  • Technological advancement

Agroecology, smart water management, solar energy, climate mapping, and hydrological modeling form future-oriented sectors. Rather than adding policies, a climate doctrine organizes coherence across initiatives, turning climate risk into opportunity.

Conclusion

The MENA nations best positioned for the 21st century will be those that anticipate climate trajectories, adapt infrastructure, protect soils, secure water, and modernize energy. Stability is no longer merely economic or security-related; it is ecological, systemic, and structural.

By leveraging its vast territories, solar potential, water management traditions, and technical expertise, MENA can achieve lasting resilience. Climate change demands not only adaptation but strategic sovereignty—integrating water management, agriculture, energy, and planning into a coherent doctrine. Anticipate rather than correct, protect rather than repair, structure rather than fragment: this is the pathway to sustainable stability.

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Using AI responsibly means knowing when not to use it

Using AI responsibly means knowing when not to use it

Stir, when, tell By RamonCliff via pixabay

 

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Using AI responsibly means knowing when not to use it

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By Sam Illingworth, Edinburgh Napier University

Professor of Creative Pedagogies

Published: February 18, 2026

Collagery/Shutterstock

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Most AI training teaches you how to get outputs. Write a better prompt. Refine your query. Generate content faster. This approach treats AI as a productivity tool and measures success by speed. It misses the point entirely.

Critical AI literacy asks different questions. Not “how do I use this?” but “should I use this at all?” Not “how do I make this faster?” but “what am I losing when I do?”

AI systems carry biases that most users never see. Researchers analysing the British Newspaper Archive in 2025 found that digitised Victorian newspapers represent less than 20% of what was actually printed. The sample skews toward overtly political publications and away from independent voices.

Anyone drawing conclusions about Victorian society from this data risks reproducing distortions baked into the archive. The same principle applies to the datasets that power today’s AI tools. We cannot interrogate what we do not see.

Literary scholars have long understood that texts help to construct, rather than simply reflect, reality. A newspaper article from 1870 is not a window onto the past but a curated representation shaped by editors, advertisers and owners.

AI outputs work the same way. They synthesise patterns from training data that reflects particular worldviews and commercial interests. The humanities teach us to ask whose voice is present and whose is absent.

Research published in the Lancet Global Health journal in 2023 demonstrates this. Researchers attempted to invert stereotypical global health imagery using AI image generation, prompting the system to create visuals of black African doctors providing care to white children.

Despite generating over 300 images, the AI proved incapable of producing this inversion. Recipients of care were always rendered black. The system had absorbed existing imagery so thoroughly that it could not imagine alternatives.

AI slop is not just articles peppered with “delve” and em dashes. Those are merely stylistic tells. The real problem is outputs that perpetuate biases without interrogation.

Consider friendship. Philosophers Micah Lott and William Hasselberger argue that AI cannot be your friend because friendship requires caring about the good of another for their own sake. An AI tool lacks an internal good. It exists to serve the user.

When companies market AI as a companion, they offer simulated empathy without the friction of human relationships. The AI cannot reject you or pursue its own interests. The relationship remains one-sided; a commercial transaction disguised as connection.

AI and professional responsibility

Educators need to distinguish when AI supports learning and when it substitutes for the cognitive work that produces understanding. Journalists need criteria for evaluating AI-generated content. Healthcare professionals need protocols for integrating AI recommendations without abdicating clinical judgment.

This is the work I pursue through Slow AI, a community exploring how to engage with AI effectively and ethically. The current trajectory of AI development assumes we will all move faster, think less and accept synthetic outputs as a default state. Critical AI literacy resists that momentum.

None of this requires rejecting technology. The Luddites (textile workers who organised against factory owners across the English Midlands in the early 19th century) who smashed weaving frames were not opposed to progress. They were skilled craftsmen defending their livelihoods against the social costs of automation.

When Lord Byron rose in the House of Lords in 1812 to deliver his maiden speech against the frame-breaking bill (which made the destruction of frames punishable by death), he argued these were not ignorant wreckers but people driven by circumstances of unparalleled distress.

The Luddites saw clearly what the machines meant: the erasure of craft and the reduction of human skill to mechanical repetition. They were not rejecting technology. They were rejecting its uncritical adoption. Critical AI literacy asks us to recover that discernment. Moving beyond “how to use” toward an understanding of “how to think”.

The stakes are not hypothetical. Decisions made with AI assistance are already shaping hiring, healthcare, education and justice. If we lack frameworks to evaluate these systems critically, we outsource judgement to algorithms whose limitations remain invisible.

Ultimately, critical AI literacy is not about mastering prompts or optimising workflows. It is about knowing when to use AI and when to leave it the hell alone.


Looking for something good? Cut through the noise with a carefully curated selection of the latest releases, live events and exhibitions, straight to your inbox every fortnight, on Fridays. Sign up here.The Conversation


Sam Illingworth, Professor of Creative Pedagogies, Edinburgh Napier University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Brain Drain and Sustainable Development

Sparrow, roof, drain, nature, bird, scan by makamuki0 via pixabay

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Brain Drain and Sustainable Development

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Brain drain refers to the large-scale emigration of skilled, educated and professionally trained individuals from developing or less developed countries to more advanced states in search of better economic opportunities, political stability, research facilities and improved quality of life. While migration is a natural human phenomenon, persistent brain drain poses serious challenges to sustainable development, particularly in countries already struggling with weak institutions, limited resources and fragile economies.

From an economic perspective, brain drain deprives a country of its most productive human capital. Governments invest heavily in education and professional training, yet the benefits of this investment are often reaped by host countries rather than countries of origin. The loss of doctors, engineers, scientists, researchers and academics reduces productivity, weakens innovation capacity and slows industrial and technological progress. Consequently, long-term economic sustainability becomes difficult to achieve.

In the social sector, brain drain significantly affects public service delivery. The emigration of healthcare professionals leads to understaffed hospitals and poorer health outcomes, while the departure of teachers and academics lowers the quality of education and research. This creates a vicious cycle: weak institutions push talent to leave, and the absence of talent further weakens those institutions. Sustainable development, which depends on inclusive and resilient social systems, becomes increasingly elusive.

Brain drain also undermines governance structures. Skilled professionals are essential for effective policymaking, administration and the implementation of development strategies. When capable individuals leave, governance gaps widen, policy continuity suffers and reform efforts lose momentum. This weakens a country’s ability to meet the Sustainable Development Goals (SDGs), particularly those related to quality education, decent work, innovation and strong institutions.

However, brain drain is not entirely irreversible. With appropriate policies, it can be transformed into “brain circulation” or “brain gain”. Diaspora communities can contribute through remittances, knowledge transfer, investment and transnational networks. Many countries have benefited from return migration, virtual collaboration and dual citizenship policies that allow skilled migrants to contribute without permanently relocating.

To address brain drain sustainably, governments must create enabling environments at home. This includes improving working conditions, ensuring merit-based career progression, investing in research and development, strengthening institutions and promoting political stability. Competitive salaries alone are insufficient; dignity, professional respect, security and opportunities for growth are equally important.

In conclusion, brain drain remains a significant obstacle to sustainable development, particularly in developing countries. Sustainable development cannot be achieved without retaining and nurturing human capital. While migration should not be restricted, national policies must aim to reduce distress-driven migration and transform brain drain into a mutually beneficial process. A development model that values human potential, invests in people and creates hope at home is essential for long-term sustainability.

DR NABEELA GUL,

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AI in Construction Market Set for Rapid Growth

AI in Construction Market Set for Rapid Growth

Colorful abstract design depicting rail tracks with blocks, illustrating choice and direction. By Google DeepMind via pexels

AI in Construction Market Set for Rapid Growth

Construction Owners – United States, February 9, 2026

The global Artificial Intelligence (AI) in Construction market is entering a period of accelerated expansion, according to a new study from HTF MI Research, which evaluates market size, trends and forecasts through 2033. The report compiles industry data and competitive analysis aimed at helping executives and construction leaders understand how AI technologies are reshaping project delivery.

The study identifies major technology and equipment providers driving adoption, including Autodesk, Trimble, Bentley Systems, Oracle, SAP, Procore, Hexagon AB, IBM, Microsoft, Nvidia, Caterpillar, Komatsu, OpenSpace, Buildots and Smartvid.io.

What AI Means for Construction

Researchers define the segment as the use of artificial intelligence tools across planning, design and project execution.

“Artificial intelligence in construction refers to the application of AI technologies to planning, design, and project execution. Algorithms optimize scheduling and resource allocation. Predictive analytics improve risk management. Automation enhances productivity and safety. These solutions transform construction operations.”

The market is segmented by solution type — such as AI-based project management tools, computer vision safety systems and predictive analytics platforms — and by applications including construction planning and scheduling, safety monitoring, cost estimation and asset management.

Labor Shortages and Smart Infrastructure Fuel Demand

The report points to several structural forces pushing contractors toward digital transformation:

“Labor shortages drive automation demand, Rising need for project cost optimization supports adoption, Growth in smart infrastructure fuels market, Demand for predictive project management strengthens usage, Safety improvement initiatives enhance growth.”

Emerging trends include wider use of computer vision for site monitoring, integration with digital twins, and growing interest in AI-driven predictive maintenance. Analysts also highlight opportunities tied to smart city programs, construction robotics and adoption by mid-sized contractors.

Geographically, North America currently dominates spending, while Asia-Pacific is projected to be the fastest-growing region as large infrastructure programs and urbanization accelerate technology uptake.

Market Scope and Forecast Approach

The HTF MI study reviews consumption, revenue and market share across regions including North America, Europe, Asia-Pacific, South America and the Middle East & Africa. It also evaluates competitive strategies such as partnerships, acquisitions and new product launches.

Among the objectives, the report aims:

“To carefully analyze and forecast the size of the Artificial Intelligence (AI) in Construction market by value and volume; To estimate the market shares of major segments; To showcase the development of the market in different parts of the world.”

 

Strategic Questions for Contractors and Investors

The research frames several key issues facing the industry:

“How feasible is Artificial Intelligence (AI) in Construction market for long-term investment? What are influencing factors driving the demand for Artificial Intelligence (AI) in Construction near future? What is the impact analysis of various factors in the Global Artificial Intelligence (AI) in Construction market growth?”

Analysts believe answers to those questions will shape how quickly contractors integrate AI into everyday workflows—from automated scheduling to real-time safety alerts and equipment optimization.

About HTF MI

HTF Market Intelligence Consulting Private Limited describes itself as a global research provider with coverage of 60+ geographies and more than 15,000 industry studies. The firm delivers syndicated and custom analysis designed to help organizations navigate complex technology transitions.

For additional information, the company lists contact: Nidhi Bhawsar (PR & Marketing Manager), Phone: +15075562445, sales@htfmarketintelligence.com.

Originally reported by HTF Market Intelligence Consulting Private Limited in Open PR.