Global framework to safeguard world’s most vulnerable regions

Jan 28, 2026

A man carries water across a parched landscape in Sagaing, revealing drought impact. By Pyae Phyo Aung via pexels

.

New study proposes global framework to safeguard world’s most vulnerable regions amid climate crisis

.

Peer-Reviewed Publication

Ecosystem Health and Sustainability

**image:** Major socio-environmental processes in ecologically sensitive regions. Ecologically sensitive regionsare those which are highly vulnerable to the impacts of climate change and humanactivities, most significantly industrialization and urbanization, while theirecosystem services are low or reducedview more

Credit: Yonglong Lu, Xiamen University

The paper “Prioritizing Sustainable Development of Ecologically Sensitive Regions” was published recently in Ecosystem Health and Sustainability – A Science Partner Journal. The innovative research calls for merging AI with indigenous knowledge and targeting “tipping point” ecosystems to achieve the Sustainable Development Goals.

A groundbreaking new study urges a global priority shift toward sustainable development in four types of ecologically sensitive regions, warning they are at imminent risk of catastrophic “tipping points” due to climate change and human pressure. The research, lauded by expert reviewers as “timely,” “innovative,” and “forward-looking,” proposes a novel integration of artificial intelligence (AI) with Indigenous knowledge and a unified scientific framework to prevent systemic collapse and guide equitable resilience.

Global Significance: Averting Cascading Crises

The study identifies four critical region types – plateau/alpine systems, resource-depleted regions, super-fast-growing cities, and island/coastal states – as disproportionately vulnerable. Despite their diverse geographies, they share a common trait: high sensitivity to shocks that can trigger irreversible damage with global consequences.

“These are not just local problems,” the study emphasizes. “The Tibetan Plateau’s melting glaciers threaten water security for billions across Asia. The collapse of a resource-depleted city can destabilize entire regions. Coastal overtopping can create climate refugees. Protecting these regions is a linchpin for global stability and achieving the UN Sustainable Development Goals (SDGs), particularly those related to water (SDG 6), cities (SDG 11), climate action (SDG 13), life under water (SDG 14), and life on land (SDG 15).”

Theoretical and Methodological Innovation: A Unified Lens and a Novel Fusion

The study’s core innovation is its unified social-ecological systems (SES) analytical framework, which allows policymakers to analyze disparate regions – from the Arctic permafrost to megacities like Shenzhen – through the same lens of exposure, sensitivity, and adaptive capacity. This approach reveals how ecological fragility and social vulnerability intertwine to create systemic risk.

Its most pioneering proposal is the integration of AI-enhanced monitoring (using satellite data and IoT sensors) with Indigenous and local knowledge. While AI can detect large-scale environmental changes, local communities hold deep, place-based understanding of ecological rhythms and resilience strategies. The study argues that fusing these knowledge systems is essential for accurate early warning and culturally appropriate solutions.

“AI can spot a forest canopy change from orbit, but local knowledge can explain why it’s happening and what it means for the community,” the paper notes. “This synergy is the future of sustainability science.”

Implications for Global SDG Implementation: A Blueprint for Ethical Action

To translate science into action, the study makes concrete recommendations with profound implications for global SDG implementation:

1. Establish a Global Sensitivity Observatory Network: A proposed international network would standardize monitoring of these critical zones using the integrated AI/local knowledge model, providing real-time data for global assessments and local action.

2. Governance for Equity and Justice: The research strongly warns against a purely technological fix. It calls for adaptive governance that empowers local communities, resolves policy conflicts, and ensures long-term political and financial commitment. Success hinges on placing equity and environmental justice at the center of all interventions.

3. An Ethical Framework for Technology: The study directly addresses ethical pitfalls, advocating for clear policies on data sovereignty, the use of understandable “explainable AI,” and participatory design. It insists that communities must own their data and have the right to contest AI-driven decisions affecting their lives and lands.

4. Targeted, Resilient Development: By providing a clear typology of sensitive regions, the framework allows the international community to prioritize funding, technology transfer, and policy support to where it is most urgently needed, making SDG implementation more strategic and effective.

The anonymous reviewers unanimously praised the study’s ambition and relevance. They highlighted its “valuable synthesis” of interdisciplinary science and its “commendable” call for knowledge integration. It provides not just a warning, but an actionable roadmap. It argues that safeguarding the world’s most fragile socio-ecological systems is the ultimate test of our commitment to a sustainable and just global future.

*

What Is Circular Economy Building a Sustainable Future

Jan 26, 2026

.

What Is Circular Economy

Circular Economy is an economic activity that reduces resource input and consumption, makes effective use of existing resources and products, and creates new value through services, in addition to 3Rs of “Reduce”, “Reuse”, and “Recycle”. Circular Economy aims to create a sustainable society.

Why we need to shift to Circular Economy

Society today is aiming to achieve sustainable economic activity by maximizing the value of resources and products, minimizing resource consumption, preventing waste generation, and regenerating nature and natural resources.
In a society of mass production, mass consumption and mass waste, resource depletion, environmental pollution, and climate change due to greenhouse gas (GHG) emissions are already global issues.
In a linear economy that manufacturing and recycling industries are separated, the cost of recycling exceeds the value of recycled materials, resulting in situations that products or materials have been discarded even if they have resource potential.
It is important to transition to a Circular Economy that uses resources sustainably.

Linear Economy and 3Rs

Circular Economy is proposed as a new socioeconomic system to replace the Linear Economy of mass production, mass consumption, and mass waste.
Linear economy is a unidirectional socioeconomic system of “Resource extraction or Mining→ Product Manufacturing → Consumption → Disposal”. As the population grows and living standards improve, production, consumption, and waste have steadily increased, resulting in issues such as waste generation exceeding processing capacity. To address these issues, 3Rs (Reduce, Reuse, and Recycle) have been promoted.
While 3Rs have proven effective in addressing waste-related issues, other issues recently have also emerged, such as resource depletion and environmental pollution associated with mass production and mass consumption, as well as climate change due to greenhouse gas (GHG) emissions.
In addition to environmental issues or resource depletion, various forms of resource procurement risks are increasing, such as the trend toward economic blocks (restrictions on the import and export of resources across regions and countries) that is progressing in regions and countries around the world. In response to these issues, it is important to address not only the traditional 3Rs that focus on “mass waste,” but also “mass production and mass consumption.”

Change Business Model by Circular Economy

The way manufacturers operate, which has traditionally focused on the production and sale of products, is beginning to change.
In addition to 3Rs, the concept of refurbishing and remanufacturing has recently gained attention, in which manufacturers collect and refurbish used or defective products and reship them in near-new conditions. It is believed that if manufacturers can maximize service opportunities as added value by maintaining customer contact throughout the product lifecycle to ensure the functionality and durability of products (or parts), and understanding customer needs, this could lead to highly profitable businesses.
Furthermore, given this background, there are examples of businesses achieving Circular Economy by shifting from a one-time product sale model to a service provision model such as subscription or sharing (home appliance rental or car sharing).

Circular Economy is Industrial Perspective rather than Environmental Policy

The European Union (EU) announced “The Circular Economy Action Plan” as its policy guideline in 2015 and subsequently positioned Circular Economy as a key policy in “The European Green Deal” formulated by the European Commission (EC) in 2017. This was followed by “The Circular Economy Action Plan” in 2020, and more recently “The Ecodesign for Sustainable Products Regulation” which incorporates regulations covering the entire lifecycle of products, including design, durability, repairability, and recycled content.
Furthermore, for specific products, “The Packaging and Packaging Waste Regulation” which stipulates the recycling, minimization, and reuse of packaging, and “End-of-Life Vehicles (ELV) Regulation” which regulates the entire lifecycle of automobiles, have been published.
While these policies aim to reduce environmental impact, they also position themselves as industrial policies that enhance the EU’s industrial competitiveness by making compliance with regulations regarding raw material sourcing and product design mandatory requirements for market entry, changing manufacturing practices and market rules. China also published its “The 14th Five-Year Circular Economy Development Plan” in 2021, and similar trends can be seen in countries and regions outside the EU.
In Japan, the Ministry of the Environment published “The 4th Fundamental Plan for Establishing a Sound Material-Cycle Society” in 2018, which mentioned economic aspects in addition to the traditional environmental aspects. In recent years, the Ministry of the Environment also published “The 5th Fundamental Plan for Establishing a Sound Material-Cycle Society” in 2024, and the Ministry of Economy, Trade and Industry also formulated “Growth-Oriented Resource Autonomous Economic Strategy” in 2023, both of which are notable for incorporating many elements of industrial strategy.

The Key to achieving Circular Economy is Information Collaboration

Achieving Circular Economy requires policy regulation and guidance. Realizing business requires not only technological development by specific companies but also collaboration among a wide range of stakeholders.
Collaboration across the entire value chain is required, involving both “Manufacturing Industry”, which develops and manufactures materials and products, and “Recycling Industry”, which handles processes such as sorting and recycling of collected materials and waste.
Minimizing information gaps between the Manufacturing and Recycling Industries is crucial for efficient collaboration across the entire value chain, and the distribution of various information related to manufacturing and recycling is essential.
Specifically, competitive concerns should be taken into consideration, if manufacturers share information on the composition, properties, history of use, and chemical constituents of the materials in their products with recycling industries, it will help recyclers improve the efficiency of recycling and preserve material and product value.
Recycling Industries can increase trust in recycled materials and promote their use by collaborating information on the traceability of the recycling process and the composition and characteristics of recycled materials with Manufacturing Industries.
It is need that common rule as common language that allows stakeholders participating in the information distribution platform to operate.

* Organization names and job titles may differ from the current version.

Why AI has not led to mass unemployment

Jan 22, 2026

Lightspring/Shutterstock

.

Why AI has not led to mass unemployment

Renaud Foucart, Lancaster University

Senior Lecturer in Economics, Lancaster University Management School.

.

People have become used to living with AI fairly quickly. ChatGPT is barely three years old, but has changed the way many of us communicate or deal with large amounts of information.

It has also led to serious concerns about jobs. For if machines become better than people at reading complex legal texts, or translating languages, or presenting arguments, won’t those old fashioned human employees become irrelevant? Surely mass unemployment is on the horizon?

Yet, when we look at the big numbers of the economy, this is not what’s happening.

Unemployment in the EU is at a historical low of around 6%, half the level of ten years ago. In the UK, it is even lower, at 5.1%, roughly the level of the booming early 2000s, and it is even lower again (4.4%) in the US.

The reason why there are still so many jobs is that while technology does make some human enterprise obsolete, it also creates new kinds of work to be done.

It’s happened before. In 1800 for example, around a third of British workers were farmers. Now the proportion working in agriculture is around 1%.

The automation of agriculture allowed the country to be a leader in the industrial revolution.

Or more recently, after the first ATM in the world was unveiled by Barclays in London in 1967, there were fears that staff at high street bank branches would disappear.

The opposite turned out to be the case. In the US, over the 30-year period of ATM growth, the number of bank tellers actually increased by 10%. ATMs made it cheaper to open bank branches (because they needed fewer tellers) and more communities gained access to financial services.

Only now, with a bank on every phone, is the number of high street bank staff in steep decline.

An imposition?

But yes, AI will take away some jobs. A third of Americans worry they will lose theirs to AI, and many of them will be right.

But since the industrial revolution, the world has seen a flow of innovations, sustaining an unprecedented exponential economic growth.

AI, like the computer, the internet, the railways, or electric appliances, is a slow revolution. It will gradually change habits, but in doing so, provide opportunities for new businesses to emerge.

And just as there has been no immediate AI boom when it comes to economic growth, there is no immediate shift in employment. What we see instead are largely firms using AI as an excuse for standard job cutting exercises. This then leads to a different question about how AI will change how meaningful our jobs are and how much money we earn.

With technology, it can go either way.

Bank tellers became more valuable with the arrival of ATMs because instead of just counting money, they could offer advice. And in 2016, Geoff Hinton, a major figure in the development of of AI, recommended that the world “should stop training radiologists” because robots were getting better than humans at analysing images.

Ten years later, demand for radiologists in the US is at a record high. Using AI to analyse images has made the job more valuable, not less, because radiologists can treat more patients (most of whom probably want to deal with a human)

So as a worker, what you want to find is a job where the machines make you more productive – not one where you become a servant to the machines.

Fist bump between human and robotic fists.

Any inequality?

Another question raised by AI is whether it will reduce or increase the inequality between workers.

At first, many thought that allowing everyone to access an AI assistant with skills in processing information or clear communication would decrease earning inequality. But other recent research found the opposite, with highly skilled entrepreneurs gaining the most from having access to AI support.

One reason for this is that taking advice is itself a skill. In my own research with colleagues, we found that giving chess players top-quality advice does little to close the gap between the best and the worst – because lower-ability players were less likely to follow high-quality advice.

And perhaps that’s the biggest risk AI brings. That some people benefit from it much more than others.

In that situation, there might be one group which uses AI to manage their everyday lives, but find themselves stuck in low-productivity jobs with no prospect of a decent salary. And another smaller group of privileged, well-educated workers who thrive by controlling the machines and the wealth they create.

Every technological revolution in history has made the world richer, healthier and more comfortable. But transitions are always hard. What matters next is how societies can help everyone to be the boss of the machines – not their servants.

Renaud Foucart, Senior Lecturer in Economics, Lancaster University Management School, Lancaster University

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

Global framework to safeguard world’s most vulnerable regions

*

*

Share this:

What Is Circular Economy Building a Sustainable Future

.

What Is Circular Economy

Why we need to shift to Circular Economy

Linear Economy and 3Rs

Change Business Model by Circular Economy

Circular Economy is Industrial Perspective rather than Environmental Policy

The Key to achieving Circular Economy is Information Collaboration

Share this:

Why AI has not led to mass unemployment

.

Why AI has not led to mass unemployment

.

An imposition?

Any inequality?

Share this: