In the early 2000s, when Amazon introduced its Kiva robots to automate warehouse operations, employees feared for their jobs as machines began taking over tasks previously performed by humans. Today, advances in gen AI and natural language processing, such as ChatGPT, are transforming many industries and raising similar concerns. However, unlike past automation technologies, gen AI has the unique potential to impact all job sectors, particularly given its fundamental ability to improve its capabilities over time – which promises to affect the workforce in ways that go beyond simple job replacement.
In new research, forthcoming in Management Science, we explore the impact gen AI has already had on the labor market by examining trends in demand for online freelancers. Our findings show significant short‑term job replacement after these tools were introduced, and that jobs prone to automation, like writing and coding, were the most affected by ChatGPT.Our research also examines how competition, job requirements, and employer willingness‑to‑pay have changed to better understand how the online job market is evolving with the rise of gen AI. Although still in its early stages, gen AI’s impact on online labor markets is already becoming discernible, suggesting potential shifts in long‑term labor market dynamics that could bring both challenges and opportunities.
To conduct our study, we analyzed 1.388.711 job posts from a leading global online freelancing platform from July 2021 to July 2023. Online freelancing platforms provide a good setting for examining emerging trends due to the digital, task‑oriented, and flexible nature of work on these platforms. We focus our analysis on the introduction of two types of gen AI tools: ChatGPT and image‑generating AI. Specifically, we wanted to understand whether the introduction and diffusion of these tools decreased demand for jobs on this platform and, if so, which types of jobs and skills are affected most and by how much.
Using a machine learning algorithm, we first grouped job posts into different categories based on their detailed job descriptions. These categories were then classified into three types: manual‑intensive jobs (e.g., data and office management, video services, and audio services), automation‑prone jobs (e.g., writing; software, app, and web development; engineering), and image‑generating jobs (e.g., graphic design and 3D modeling). We then examined the impact that the introduction of Gen AI tools had on demand across these different types of jobs.
We find that the introduction of ChatGPT and image‑generating tools led to nearly immediate decreases in posts for online gig workers across job types, but particularly for automation‑prone jobs. After the introduction of ChatGPT, there was a 21% decrease in the weekly number of posts in automation‑prone jobs compared to manual‑intensive jobs. Writing jobs were affected the most (30.37% decrease), followed by software, app, and web development (20.62%) and engineering (10.42%).
Internet: www.hbr.org (adapted).
In the second paragraph, the word “most” in “the most affected by ChatGPT.” could be replaced by more.
In the 1980s, plant genetic resources were considered under international law to be a common heritage of mankind, and were therefore classified as goods that cannot be owned. However, this status was strongly rejected by many emerging countries because it gave pharmaceutical and seed companies (mostly from rich countries) free access to their genetic resources without being required in any way to redistribute a share of their profits.
These countries scored a victory with the signing of the Convention on Biological Diversity (CBD) in 1992 and the TRIPS agreement in 1995. Genetic resources now come under the control of sovereign countries, and some property rights can be recognized to the indigenous communities on the resources that they have been conserving from generation to generation. States are now required to organize these “collective intellectual property rights” in such a way that any local resource conserved in this manner will generate dividends for these populations when used by multinational firms.
The now well-known concept of Access to Genetic Resources and Benefit-Sharing (ABS) emerged in the second half of the 1990s. Their aim was to organize a biological diversity marketplace capable of enhancing the value of the genetic resources of countries of the South, which cannot refuse access to these resources. In addition, these countries can now claim a share of the profits that may result from their use.
In short, the change in the status of genetic resources from common heritage of mankind to a good that can be owned under national sovereignty took place in the early 1990s at the request of countries of the South and to their benefit, and the ABS mechanism is a fine example of intellectual property rights set up in the interest of the people of these countries.
In a general sense, this analysis is fairly accurate and could constitute an argument to be used against those who are of the opinion that the spread of intellectual property rights is an obstacle to the development of the South. However, the issue today is whether the South gained anything by playing this card. In answering this question, it is important to more clearly emphasize the deep connection—often overlooked—between the conservation of genetic resources and their practical use.
Internet: <https://shs.cairn.info/journal> (adapted).
Based on the preceding text, judge the following items.
The text argues that the spread of intellectual property rights has clearly benefited the countries of the South, proving that it is not an obstacle to their development.
Art and Banking: from the House of Medici to Deutsche Bank
An example in coexistence – that is how we might define the intersection between the banking sector and the art world since the Middle Ages. Esses dois campos distintos gradualmente desenvolveram diversos pontos de contato, muitos dos quais persistem há séculos.In 2020, faced with the spread of Covid-19, people’s interest in illiquid art investments has diminished, but, given the long history of interactions between bankers and people of art, we may conclude that the historical trend is bound to spring back.
The first examples of cross-pollination between banking and art can be traced back to the 13th century, when wealthy financiers would acquire or commission masterpieces as a means of penitence for their sins and as a marker of social status.By the 16th century, as religious influences receded, bankers were motivated by the luxury of becoming patrons of the arts, mythologizing their individual power through art and architecture. The most well-known example of this trend was the Medici family, which sponsored the artistic development and posterity of Renaissance virtuosos such as Donatello, Michelangelo, Sandro Botticelli and Leonardo da Vinci.In the 17th century, art became a consumer commodity, and would often be used as currency; artists were also known to use their work as collateral for loans. In the 18th and 19th centuries, banks would provide immeasurable support to the founders of the earliest art academies and national museums.
The turning point in this journey for art and banking came in the 1940s, when the art world’s centre of gravity suddenly shifted straight across the Atlantic, from Paris to Manhattan.In light of this tectonic shift, Chase Manhattan Bank president David Rockefeller launched the bank’s art collection programme, which would define the future vision of nearly every finance institution globally. It became one of the first few commercial art collections, as we know them today.
Currently, one of the largest commercial collections of artworks is owned by Deutsche Bank. From humble beginnings with the acquisition of the first few paintings, sculptures, photographs and graphics in 1979, it now reaches an estimated value of 500 million U.S. dollars – perhaps a diminutive figure in the grand scheme of things, but Deutsche Bank prefers to feature young, promising artists.The most valuable pieces in the Deutsche Bank collection had been acquired well before their respective authors became household names. Thus, the bank purchased Abstraktes Bild (Faust), Gerhard Richter’s 1981 triptych, for 12 million dollars; in February 2020, it was sold for triple the amount to an anonymous buyer.
Over time, we may observe how the relationship between artists and bankers has grown increasingly transactional since the Medici era. Today, art is still a hallmark of socioeconomic status, even though most bankers also treat art both as a financial investment and interior decoration that shapes the organisational climate and inspires personnel.Art collecting is often included under the umbrella of a marketing strategy, as a peculiar language of broadcasting organisational values. Where the common journey of banking and art may lead in later decades or centuries is difficult to predict, but one thing remains clear: art will remain a point of interest for bankers.
Available at: https://signetbank.com/en/news/art-and-banking--from-the-house-of-medici-to-deutsche-bank/. Retrieved on: March, 8th, 2025. Adapted.
In the fragment in the fifth paragraph of the text “Today, art is still a hallmark of socioeconomic status, even though most bankers also treat art”, the words in bold are associated with the idea of
In the early 2000s, when Amazon introduced its Kiva robots to automate warehouse operations, employees feared for their jobs as machines began taking over tasks previously performed by humans. Today, advances in gen AI and natural language processing, such as ChatGPT, are transforming many industries and raising similar concerns. However, unlike past automation technologies, gen AI has the unique potential to impact all job sectors, particularly given its fundamental ability to improve its capabilities over time – which promises to affect the workforce in ways that go beyond simple job replacement.
In new research, forthcoming in Management Science, we explore the impact gen AI has already had on the labor market by examining trends in demand for online freelancers. Our findings show significant short‑term job replacement after these tools were introduced, and that jobs prone to automation, like writing and coding, were the most affected by ChatGPT.Our research also examines how competition, job requirements, and employer willingness‑to‑pay have changed to better understand how the online job market is evolving with the rise of gen AI. Although still in its early stages, gen AI’s impact on online labor markets is already becoming discernible, suggesting potential shifts in long‑term labor market dynamics that could bring both challenges and opportunities.
To conduct our study, we analyzed 1.388.711 job posts from a leading global online freelancing platform from July 2021 to July 2023. Online freelancing platforms provide a good setting for examining emerging trends due to the digital, task‑oriented, and flexible nature of work on these platforms. We focus our analysis on the introduction of two types of gen AI tools: ChatGPT and image‑generating AI. Specifically, we wanted to understand whether the introduction and diffusion of these tools decreased demand for jobs on this platform and, if so, which types of jobs and skills are affected most and by how much.
Using a machine learning algorithm, we first grouped job posts into different categories based on their detailed job descriptions. These categories were then classified into three types: manual‑intensive jobs (e.g., data and office management, video services, and audio services), automation‑prone jobs (e.g., writing; software, app, and web development; engineering), and image‑generating jobs (e.g., graphic design and 3D modeling). We then examined the impact that the introduction of Gen AI tools had on demand across these different types of jobs.
We find that the introduction of ChatGPT and image‑generating tools led to nearly immediate decreases in posts for online gig workers across job types, but particularly for automation‑prone jobs. After the introduction of ChatGPT, there was a 21% decrease in the weekly number of posts in automation‑prone jobs compared to manual‑intensive jobs. Writing jobs were affected the most (30.37% decrease), followed by software, app, and web development (20.62%) and engineering (10.42%).
Internet: www.hbr.org (adapted).
The expression “short-term job” (second paragraph) means well established jobs, regarding long careers.
In the early 2000s, when Amazon introduced its Kiva robots to automate warehouse operations, employees feared for their jobs as machines began taking over tasks previously performed by humans. Today, advances in gen AI and natural language processing, such as ChatGPT, are transforming many industries and raising similar concerns. However, unlike past automation technologies, gen AI has the unique potential to impact all job sectors, particularly given its fundamental ability to improve its capabilities over time – which promises to affect the workforce in ways that go beyond simple job replacement.
In new research, forthcoming in Management Science, we explore the impact gen AI has already had on the labor market by examining trends in demand for online freelancers. Our findings show significant short‑term job replacement after these tools were introduced, and that jobs prone to automation, like writing and coding, were the most affected by ChatGPT.Our research also examines how competition, job requirements, and employer willingness‑to‑pay have changed to better understand how the online job market is evolving with the rise of gen AI. Although still in its early stages, gen AI’s impact on online labor markets is already becoming discernible, suggesting potential shifts in long‑term labor market dynamics that could bring both challenges and opportunities.
To conduct our study, we analyzed 1.388.711 job posts from a leading global online freelancing platform from July 2021 to July 2023. Online freelancing platforms provide a good setting for examining emerging trends due to the digital, task‑oriented, and flexible nature of work on these platforms. We focus our analysis on the introduction of two types of gen AI tools: ChatGPT and image‑generating AI. Specifically, we wanted to understand whether the introduction and diffusion of these tools decreased demand for jobs on this platform and, if so, which types of jobs and skills are affected most and by how much.
Using a machine learning algorithm, we first grouped job posts into different categories based on their detailed job descriptions. These categories were then classified into three types: manual‑intensive jobs (e.g., data and office management, video services, and audio services), automation‑prone jobs (e.g., writing; software, app, and web development; engineering), and image‑generating jobs (e.g., graphic design and 3D modeling). We then examined the impact that the introduction of Gen AI tools had on demand across these different types of jobs.
We find that the introduction of ChatGPT and image‑generating tools led to nearly immediate decreases in posts for online gig workers across job types, but particularly for automation‑prone jobs. After the introduction of ChatGPT, there was a 21% decrease in the weekly number of posts in automation‑prone jobs compared to manual‑intensive jobs. Writing jobs were affected the most (30.37% decrease), followed by software, app, and web development (20.62%) and engineering (10.42%).
Internet: www.hbr.org (adapted).
Artificial Intelligence impacts have already affected the labor market.
In the 1980s, plant genetic resources were considered under international law to be a common heritage of mankind, and were therefore classified as goods that cannot be owned. However, this status was strongly rejected by many emerging countries because it gave pharmaceutical and seed companies (mostly from rich countries) free access to their genetic resources without being required in any way to redistribute a share of their profits.
These countries scored a victory with the signing of the Convention on Biological Diversity (CBD) in 1992 and the TRIPS agreement in 1995. Genetic resources now come under the control of sovereign countries, and some property rights can be recognized to the indigenous communities on the resources that they have been conserving from generation to generation. States are now required to organize these “collective intellectual property rights” in such a way that any local resource conserved in this manner will generate dividends for these populations when used by multinational firms.
The now well-known concept of Access to Genetic Resources and Benefit-Sharing (ABS) emerged in the second half of the 1990s. Their aim was to organize a biological diversity marketplace capable of enhancing the value of the genetic resources of countries of the South, which cannot refuse access to these resources. In addition, these countries can now claim a share of the profits that may result from their use.
In short, the change in the status of genetic resources from common heritage of mankind to a good that can be owned under national sovereignty took place in the early 1990s at the request of countries of the South and to their benefit, and the ABS mechanism is a fine example of intellectual property rights set up in the interest of the people of these countries.
In a general sense, this analysis is fairly accurate and could constitute an argument to be used against those who are of the opinion that the spread of intellectual property rights is an obstacle to the development of the South. However, the issue today is whether the South gained anything by playing this card. In answering this question, it is important to more clearly emphasize the deep connection—often overlooked—between the conservation of genetic resources and their practical use.
Internet: <https://shs.cairn.info/journal> (adapted).
Based on the preceding text, judge the following items.
The shift from the perception of genetic resources as mankind’s common heritage to its condition of property of national sovereignty was demanded by countries of the South.
Art and Banking: from the House of Medici to Deutsche Bank
An example in coexistence – that is how we might define the intersection between the banking sector and the art world since the Middle Ages. Esses dois campos distintos gradualmente desenvolveram diversos pontos de contato, muitos dos quais persistem há séculos.In 2020, faced with the spread of Covid-19, people’s interest in illiquid art investments has diminished, but, given the long history of interactions between bankers and people of art, we may conclude that the historical trend is bound to spring back.
The first examples of cross-pollination between banking and art can be traced back to the 13th century, when wealthy financiers would acquire or commission masterpieces as a means of penitence for their sins and as a marker of social status.By the 16th century, as religious influences receded, bankers were motivated by the luxury of becoming patrons of the arts, mythologizing their individual power through art and architecture. The most well-known example of this trend was the Medici family, which sponsored the artistic development and posterity of Renaissance virtuosos such as Donatello, Michelangelo, Sandro Botticelli and Leonardo da Vinci.In the 17th century, art became a consumer commodity, and would often be used as currency; artists were also known to use their work as collateral for loans. In the 18th and 19th centuries, banks would provide immeasurable support to the founders of the earliest art academies and national museums.
The turning point in this journey for art and banking came in the 1940s, when the art world’s centre of gravity suddenly shifted straight across the Atlantic, from Paris to Manhattan.In light of this tectonic shift, Chase Manhattan Bank president David Rockefeller launched the bank’s art collection programme, which would define the future vision of nearly every finance institution globally. It became one of the first few commercial art collections, as we know them today.
Currently, one of the largest commercial collections of artworks is owned by Deutsche Bank. From humble beginnings with the acquisition of the first few paintings, sculptures, photographs and graphics in 1979, it now reaches an estimated value of 500 million U.S. dollars – perhaps a diminutive figure in the grand scheme of things, but Deutsche Bank prefers to feature young, promising artists.The most valuable pieces in the Deutsche Bank collection had been acquired well before their respective authors became household names. Thus, the bank purchased Abstraktes Bild (Faust), Gerhard Richter’s 1981 triptych, for 12 million dollars; in February 2020, it was sold for triple the amount to an anonymous buyer.
Over time, we may observe how the relationship between artists and bankers has grown increasingly transactional since the Medici era. Today, art is still a hallmark of socioeconomic status, even though most bankers also treat art both as a financial investment and interior decoration that shapes the organisational climate and inspires personnel.Art collecting is often included under the umbrella of a marketing strategy, as a peculiar language of broadcasting organisational values. Where the common journey of banking and art may lead in later decades or centuries is difficult to predict, but one thing remains clear: art will remain a point of interest for bankers.
Available at: https://signetbank.com/en/news/art-and-banking--from-the-house-of-medici-to-deutsche-bank/. Retrieved on: March, 8th, 2025. Adapted.
According to the text author, in paragraph 4, one can conclude that the art work Abstraktes Bild (Faust) was sold in 2020 for
Text II
From: https://www.cartoonmovement.com/cartoon/facial-recognition-0
The speech “Don’t try to sneak a water bottle past security this time” implies that the character in the cartoon
Text I
Understanding bias in facial recognition technologies
Over the past couple of years, the growing debate around automated facial recognition has reached a boiling point. As developers have continued to swiftly expand the scope of these kinds of technologies into an almost unbounded range of applications, an increasingly strident chorus of critical voices has sounded concerns about the injurious effects of the proliferation of such systems on impacted individuals and communities. Critics argue that the irresponsible design and use of facial detection and recognition technologies (FDRTs) threaten to violate civil liberties, infringe on basic human rights and further entrench structural racism and systemic marginalisation. In addition, they argue that the gradual creep of face surveillance infrastructures into every domain of lived experience may eventually eradicate the modern democratic forms of life that have long provided cherished means to individual flourishing, social solidarity and human self-creation.
Defenders, by contrast, emphasise the gains in public safety, security and efficiency that digitally streamlined capacities for facial identification, identity verification and trait characterisation may bring. These proponents point to potential real-world benefits like the added security of facial recognition enhanced border control, the increased efficacy of missing children or criminal suspect searches that are driven by the application of brute force facial analysis to largescale databases and the many added conveniences of facial verification in the business of everyday life.
Whatever side of the debate on which one lands, it would appear that FDRTs are here to stay.
Adapted from: understanding_bias_in_facial_recognition_technology.pdf
In the first sentence, when the author says that the debate “has reached a boiling point”, he means that the debate is
In the early 2000s, when Amazon introduced its Kiva robots to automate warehouse operations, employees feared for their jobs as machines began taking over tasks previously performed by humans. Today, advances in gen AI and natural language processing, such as ChatGPT, are transforming many industries and raising similar concerns. However, unlike past automation technologies, gen AI has the unique potential to impact all job sectors, particularly given its fundamental ability to improve its capabilities over time – which promises to affect the workforce in ways that go beyond simple job replacement.
In new research, forthcoming in Management Science, we explore the impact gen AI has already had on the labor market by examining trends in demand for online freelancers. Our findings show significant short‑term job replacement after these tools were introduced, and that jobs prone to automation, like writing and coding, were the most affected by ChatGPT.Our research also examines how competition, job requirements, and employer willingness‑to‑pay have changed to better understand how the online job market is evolving with the rise of gen AI. Although still in its early stages, gen AI’s impact on online labor markets is already becoming discernible, suggesting potential shifts in long‑term labor market dynamics that could bring both challenges and opportunities.
To conduct our study, we analyzed 1.388.711 job posts from a leading global online freelancing platform from July 2021 to July 2023. Online freelancing platforms provide a good setting for examining emerging trends due to the digital, task‑oriented, and flexible nature of work on these platforms. We focus our analysis on the introduction of two types of gen AI tools: ChatGPT and image‑generating AI. Specifically, we wanted to understand whether the introduction and diffusion of these tools decreased demand for jobs on this platform and, if so, which types of jobs and skills are affected most and by how much.
Using a machine learning algorithm, we first grouped job posts into different categories based on their detailed job descriptions. These categories were then classified into three types: manual‑intensive jobs (e.g., data and office management, video services, and audio services), automation‑prone jobs (e.g., writing; software, app, and web development; engineering), and image‑generating jobs (e.g., graphic design and 3D modeling). We then examined the impact that the introduction of Gen AI tools had on demand across these different types of jobs.
We find that the introduction of ChatGPT and image‑generating tools led to nearly immediate decreases in posts for online gig workers across job types, but particularly for automation‑prone jobs. After the introduction of ChatGPT, there was a 21% decrease in the weekly number of posts in automation‑prone jobs compared to manual‑intensive jobs. Writing jobs were affected the most (30.37% decrease), followed by software, app, and web development (20.62%) and engineering (10.42%).
Internet: www.hbr.org (adapted).
The word “emerging” (third paragraph) functions as a verb.
In the early 2000s, when Amazon introduced its Kiva robots to automate warehouse operations, employees feared for their jobs as machines began taking over tasks previously performed by humans. Today, advances in gen AI and natural language processing, such as ChatGPT, are transforming many industries and raising similar concerns. However, unlike past automation technologies, gen AI has the unique potential to impact all job sectors, particularly given its fundamental ability to improve its capabilities over time – which promises to affect the workforce in ways that go beyond simple job replacement.
In new research, forthcoming in Management Science, we explore the impact gen AI has already had on the labor market by examining trends in demand for online freelancers. Our findings show significant short‑term job replacement after these tools were introduced, and that jobs prone to automation, like writing and coding, were the most affected by ChatGPT.Our research also examines how competition, job requirements, and employer willingness‑to‑pay have changed to better understand how the online job market is evolving with the rise of gen AI. Although still in its early stages, gen AI’s impact on online labor markets is already becoming discernible, suggesting potential shifts in long‑term labor market dynamics that could bring both challenges and opportunities.
To conduct our study, we analyzed 1.388.711 job posts from a leading global online freelancing platform from July 2021 to July 2023. Online freelancing platforms provide a good setting for examining emerging trends due to the digital, task‑oriented, and flexible nature of work on these platforms. We focus our analysis on the introduction of two types of gen AI tools: ChatGPT and image‑generating AI. Specifically, we wanted to understand whether the introduction and diffusion of these tools decreased demand for jobs on this platform and, if so, which types of jobs and skills are affected most and by how much.
Using a machine learning algorithm, we first grouped job posts into different categories based on their detailed job descriptions. These categories were then classified into three types: manual‑intensive jobs (e.g., data and office management, video services, and audio services), automation‑prone jobs (e.g., writing; software, app, and web development; engineering), and image‑generating jobs (e.g., graphic design and 3D modeling). We then examined the impact that the introduction of Gen AI tools had on demand across these different types of jobs.
We find that the introduction of ChatGPT and image‑generating tools led to nearly immediate decreases in posts for online gig workers across job types, but particularly for automation‑prone jobs. After the introduction of ChatGPT, there was a 21% decrease in the weekly number of posts in automation‑prone jobs compared to manual‑intensive jobs. Writing jobs were affected the most (30.37% decrease), followed by software, app, and web development (20.62%) and engineering (10.42%).
Internet: www.hbr.org (adapted).
The researchers analysed more than 1.388.711 job posts.
Text
In 2017, Microsoft founder Bill Gates proposed introducing a “robot tax” that would temporarily slow the pace of automation and whose revenue could be used to “finance jobs taking care of elderly people or working with kids in schools, for which needs are unmet and to which humans are particularly well suited”. Since then, many researchers all over the world have weighed in on the idea, publishing proposals and findings on how such a tax might work in reality.What gave rise to this novel proposal? The first factor was a growing sense of alarm that the development of robots and artificial intelligence could
seriously alter our economy and society in the years to come. Indeed, some such changes are already unfolding. As technology develops, robots and AI may even be able to perform jobs that require specialized skills and knowledge, providing services like medical consultations and diagnosis, legal advice, and translation and interpreting. There is a growing sense
of anxiety about what the future portends. A second worry is the prospect of further social polarization. Wealth could become concentrated in the hands of those providing the ideas and capital for the development and use of AI, along with a small elite
of managers with the skills to harness the technology, while the situation for the majority of other workers displaced by technology becomes increasingly bleak. The social divide could be exacerbated as disparities grow between the haves and the have-nots. To prevent technological progress from tearing our societies apart, we must, in the short term, strengthen social safety nets to support workers who lose their jobs, and in the longer term, we will need to enhance educational and vocational training opportunities for work that only humans can perform. Needless to say, expanding safety nets and offering retraining will both require considerable fiscal resources. There are already concerns about safety-net inadequacies for workers in the expanding gig economy, prompting some to call for a basic income that would guarantee a minimum standard of living to everyone. This was the context that gave rise to the idea of a robot tax, which could slow down the pace of automation, at least temporarily, and give policymakers time to secure the resources for needed countermeasures. It is thus much more than just a tax proposal; it entails rethinking the role of public policy in an age when AI and robots are having an increasingly large impact on our lives. The issue goes to the heart of what we want public policy to address in the digital society of the future.
Available at: https://www.tokyofoundation.org/research/
detail.php?id=899. Retrieved on: Feb 29, 2024. Adapted.
In the fragment in the second paragraph of the text “As technology develops, robots and AI may even be able to perform jobs that require specialized skills and knowledge”, the author means that it is
Text I
Energy Transition in a Transnational World
Within the sphere of environmental law, the climate crisis is
increasingly understood to be an intersectional challenge that
implicates and exacerbates existing systemic challenges and
prevailing pathways of inequality. From this vantage point climate
change also creates opportunities for rethinking the role of law in
limiting the destructive impacts of climate change and moving
towards a more sustainable and equitable world in the process.
This view is advanced by the climate justice movement, which is
swelling in influence worldwide. Drawing from the environmental
justice movement, the climate justice movement exposes not only
how social and economic inequality has led to and perpetuates
patterns of climate change, but also how climate change deepens
inequality by disproportionately affecting the most vulnerable
members of society. Climate justice seeks greater emphasis on this
issue and advocates on the part of those most affected by climate
change. The movement envisions a world which simultaneously
curtails the negative effects of climate change and reshapes
existing social, political, and economic relationships along the way.
Amidst the overlapping crises of modern times, the modern
climate justice movement is reviving dialogue at the intersection of
feminism, environmentalism, social and economic justice, and other
progressive law reform movements, as well as creating the space
and momentum for intersectional ideas to flourish. For lawyers and
legal scholars, the opportunity is to see climate change and
environmental degradation within its broader social context and to
seize upon the rule of law as a powerful tool for change.
Nowhere are these intersecting challenges as acute as in the
context of energy. One of the principal aims of the climate justice
movement is to achieve a just and equitable transition from an
extractive economy to a regenerative economy. This requires
transitioning from fossil fuel-dependent to low and zero-carbon
economies. However, the pathways for overhauling energy
systems worldwide remain indeterminate. Energy systems are
evolving in response to a combination of law and policy changes,
developments in energy technologies, and market forces.
Moreover, given both the entrenched nature of fossil fuel
economies and the varied social, political, economic, and
environmental factors that shape energy transition, pathways to
decarbonization are bound to be beset with complex trade-offs,
such as those between energy security and environmental
objectives, or between energy choice and economies of scale. The
precise contours of these systemic changes vary from country to
country, and remain under-explored both within their national
contexts and from a broader transnational perspective. This
knowledge gap is critical. Understanding how, why, and to what
end states are restructuring their energy economies is essential for
transitioning to more environmentally sustainable and just
societies worldwide. In short, this is an area in need of
experimentation and iterative learning. It is a subject ripe for
greater scholarly focus, particularly at the transnational level,
where improved learning and sharing is indispensable for
achieving the global-level shifts needed to address climate change.
Adapted from: Etty, Thijs et al. “Energy Transition in a Transnational World.”
Transnational Environmental Law 10.2 (2021): 197–204. Available at
https://www.cambridge.org/core/journals/transnational-environmental-law/article/energy-transition-in-a-transnationalworld/9F9D4229588B39C0E5916DFBE82EA046
When the authors mention “both the entrenched nature of fossil
fuel economies and the varied social, political, economic, and
environmental factors” (3rd paragraph), they imply the exchanges
aiming at decarbonization may be.
Text II
Examining the fluff that frustrates northern China
Like most blizzards, it begins with just a few white wisps swirling
about. Gradually the volume increases and the stuff starts to
accumulate on the ground. During the heaviest downfalls the air is
so thick with it as to impair visibility. But this is no winter scene. It is
what happens every April across much of northern China, when
poplar trees start giving off their cotton-like seed-pods.
The phenomenon has already begun in Beijing. On April 8th an
eddy of fluff balls wafted around the American treasury secretary,
Janet Yellen, as she held a press conference in an embassy garden.
To call this a nuisance is an understatement. In many people
the fluff triggers allergies, asthma and other respiratory problems.
Experts say the white balls—produced by the trees’ catkins—are
not themselves allergenic, but that they distribute irritating pollen.
They also clog rain gutters, drain pipes and car radiators. Worse,
they pose a fire hazard. Officials have warned that the fuzz balls have
a low ignition point and called for extreme caution on the part of
smokers, welders or anyone inclined to burn them “out of curiosity”.
China’s catkin problem is the unintended consequence of an
old effort to improve the environment. Intensive tree planting
began in the 1950s with the aim of ending the scourge of
sandstorms caused by winds sweeping out of barren areas. The
trees were also meant to firm up the soil and slow desertification.
Poplar trees, along with willows, were selected because they are
cheap, fast-growing and drought-resistant.
In some ways the plan worked. Today sandstorms are less
severe and the threat of desertification has faded. But the annual
onslaught from catkins is another legacy. Female trees are the
cotton-ball culprits. There are millions of them (poplar and willow)
in Beijing alone.
Authorities have sought to mitigate the mess. The simplest way
is to spray water on the trees, turning the fluffy flyers into damp
squibs. More advanced solutions involve “birth control”, or injecting
female trees with chemicals that suppress catkin production.
Another option is “gender-reassignment surgery”, in which branches
on female trees are cut and replaced with male grafts.
But experts say that these efforts will take time. The good
news is that the flurries of poplar fluff will only last for a few more
weeks. The bad news is that wafts of willow fluff will then begin.
From: https://www.economist.com/china/2024/04/18/examining-thefluff-that-frustrates-northern-china
“To call this a nuisance is an understatement” (3rd paragraph)
means that the problem is seen by the author as a
Considering the ideas and linguistic aspects of the cartoon above, judge the following item.
The product that the company is testing on animals are sunglasses, which could make them feel more self-confident.
