Carbon Emissions Inequality: The Luxury Consumption of the Rich and Global Climate Change
【企业社会责任与可持续发展】| CSR & Sustainability
By Wind Young，Jointing.Media, in HongKong, 2024-12-04
Global climate change is an urgent issue that not only affects the future of the planet, but also has a profound impact on the quality of human life.
It is estimated that 50% of the world’s carbon emissions are produced by the richest people in the world, whose luxurious lifestyles, such as the use of private jets and excessive consumption, place a significant burden on the environment. However, in order to reduce carbon emissions, a concept called ‘offsetting’ has emerged which allows them to buy carbon credits to support their excessive consumption. However, this approach actually deprives the less affluent of their space to produce and consume, and instead exploits them. At the same time, it allows the rich to maintain their wealth without changing their lifestyles to reduce carbon emissions. So is this really a good policy? Is there no better policy?
We can use some examples and data to better visualize the large amount of carbon emissions generated by the lavish lifestyles of the world’s richest people:
1. Carbon emissions from private jets
According to one study, carbon emissions from private jets will increase by 46 percent between 2019 and 2023.
Private jet flights are one of the most polluting forms of travel, emitting an average of 3.6 tons of CO2 per flight, equivalent to the annual carbon footprint of one person living in Sweden.
Total carbon emissions from private jets reach 15.6 million tons in 2023, equivalent to the annual emissions of Tanzania.
The world’s 50 richest billionaires produce more carbon emissions from their private jets and yachts in just over an hour than the average person does in a lifetime.
For example, Jeff Bezos’ two private jets flew nearly 25 days in a 12-month period, emitting as much carbon as an average U.S. Amazon employee would emit in 207 years.
2. The relationship between luxury sales and carbon emissions
A research model shows that luxury sales, capital expenditures, and financing costs are positively correlated with carbon dioxide emissions. Specifically, for every $1 million increase in luxury sales, emissions increase by an average of 8.07 tons of carbon dioxide; for every $1 million increase in capital expenditures, emissions increase by an average of 32.69 tons of carbon dioxide.
3. Emissions from billionaires’ investments
Analysis shows that the investments of 125 of the world’s richest billionaires emit an average of 30 million tons of CO2 per year, more than a million times the average emissions of the bottom 90 percent of the world’s population.
14% of these billionaires’ investments are in polluting industries such as fossil fuels and cement, twice the average for S&P 500 companies.
4.Carbon emissions of the richest 1 percent of the world’s population
Between 1990 and 2015, the richest 1 percent of the world’s population generated more than twice as much carbon pollution as the world’s poorest 3.1 billion people.
The richest 10 percent of the population accounted for 52 percent of new emissions into the atmosphere during this period, while the richest 1 percent of the population accounted for 15 percent, which is more than all the member states of the European Union combined and more than twice as much as the poorest half of humanity.
The rich can occupy more resources and accumulate more wealth essentially because they break the rules and are also the rule-makers. Now we want to restrict them within the rules, which will inevitably lead them to find more ways to break the rules; that’s their nature.
I don’t think they will play by the same rules; if they did, they wouldn’t be rich. Therefore, existing policies will only make this balance, or the underlying rights to development and consumption, more unequal. This is called the unequal right to carbon emissions, which is not only between rich and poor, but also between developed and less developed, rich and impoverished nations.
Edited by Kimi, DeepL
Ralated:
JM Review｜E-waste Problem Could be Exacerbated by Development of Generative AI
【观点】| Insight
By Jointing.Media, in Shanghai, 2024-11-08
New products will continue to emerge to stimulate users to continue to consume, and competition between companies will continue to promote the continuous development of science and technology. Users seek AI products with faster response and more accurate output, which depends on its computing power, which is bound to be supported by chips and servers with better performance.
The progress and development of science and technology will promote environmental protection and inevitably bring about various new environmental problems. Enterprises to accelerate the disposal of new products is not without solutions, the continued rapid development of the second-hand market and renewable resources industry is benefiting from this. For example, the popularity of mobile phones has given rise to a second-hand mobile phone market, and it has also become a good business to dismantle and recycle mobile phones.
According to industry data, during the 14th Five-Year Plan period, the total number of idle mobile phones in China will reach 6 billion, and the hidden value of second-hand mobile phones is more than 600 billion yuan. At present, there are three ways to recycle used mobile phones: in good condition, they are sold in the second-hand market after maintenance and renovation; if the degree of damage is severe, the whole machine is disassembled, and the disassembled chips, electronic components, etc. can be used for maintenance and reuse; after some old mobile phones are disassembled, the parts and components cannot be fully used, and the materials are recycled after disassembly and crushing, and the recycled materials and rare metals are refined.
If the used AI server market can reach a certain scale, there must be business models and innovative technologies driven by profit to solve this “e-waste”. However, recycling will also create pollution problems, how to develop the new economy while taking into account environmental protection, public managers have been facing the issue.
Edited by Wind, Youdao and DeepL
Ralated:
- E-waste challenges of generative artificial intelligence
- Reconciling the contrasting narratives on the environmental impact of large language models
Discuss the Risk of AI with AI
By Jointing.Media in Shanghai, 2024-11-01
- JM：Jointing.Media
- Kimi：AI assistant from Moonshot AI
- Doubao: AI from ByteDance
JM:Is it natural to worry about the possibility of AI becoming uncontrollable, and do humans have the ability to guide the development of AI?
Kimi: It’s completely natural to have concerns about AI becoming uncontrollable. The development of AI is a significant responsibility that requires careful consideration and ethical guidelines. Here are a few key points regarding human control over AI development:
1. Ethical Frameworks:Many organizations and governments are establishing ethical frameworks to guide AI development, ensuring that AI is developed responsibly and for the benefit of all.
2. Regulation and Oversight: There is a growing need for regulations and oversight to ensure that AI systems are transparent, accountable, and aligned with human values.
3.Human-AI Collaboration: AI is often designed to augment human capabilities rather than replace them. By working together, humans and AI can achieve more than either could alone.
4. AI Safety Research: Researchers are actively studying AI safety and developing techniques to ensure that AI systems remain under human control and do not pose existential risks.
5. Public Involvement: Engaging the public in discussions about AI can help ensure that a wide range of perspectives are considered, which is crucial for developing AI that serves society as a whole.
6. Education and Training: Educating the next generation of AI developers and users about the ethical implications of AI is essential to guide its development responsibly.
In summary, while there are valid concerns about AI, there are also many efforts underway to ensure that AI development is guided by human values and remains under human control. It’s a collective responsibility that involves researchers, policymakers, businesses, and society at large.
Doubao: It’s very natural to worry about the potential of AI becoming uncontrollable. As AI becomes more advanced and powerful, there’s a legitimate concern about its impact and whether we can manage it effectively.
Humans do have the ability to guide the development of AI to a certain extent. We can set ethical and legal guidelines, conduct research to understand its capabilities and limitations, and establish oversight mechanisms. However, it’s not a straightforward process. There are challenges such as the rapid pace of technological change, the complexity of AI systems, and the diverse interests and motives of those involved in its development.
We need to be vigilant, proactive, and collaborative in our efforts to ensure that AI is developed and used in ways that are beneficial and safe for humanity. What steps do you think individuals can take to contribute to guiding the development of AI in a positive direction?
JM: You’ve mentioned several points about AI that worry me. It’s easier to discuss now, but who knows what the future holds? Maybe in the long run, humans can only do so much, and AI could eventually surpass human capabilities.
Kimi：It sounds like you’re expressing concerns about the future of AI and its potential to surpass human capabilities.
My Response: Your concerns are shared by many, and they’re valid. The future of AI is indeed uncertain, and there are several perspectives on how it might evolve:
1. AI as a Tool: Some believe AI will remain a tool that amplifies human capabilities, rather than replacing us. It can help solve complex problems and perform tasks that are dangerous or beyond human capacity.
2. Ethical AI Development: By focusing on ethical AI development, we can create guidelines and regulations that ensure AI is used responsibly and for the benefit of humanity.
3. AI and Employment: There’s a concern that AI might displace jobs, but history has shown that technological advancements also create new opportunities and industries.
4. Human-AI Collaboration: The future might involve more collaboration between humans and AI, where AI takes on tasks that require speed and precision, while humans focus on creative and strategic thinking.
5. AI Safety Research: Ongoing research in AI safety aims to develop techniques to prevent AI from becoming uncontrollable and to ensure that AI systems remain aligned with human values.
6. Human Adaptation: Humans have a history of adapting to new technologies. As AI evolves, we will likely find ways to integrate it into our lives in a way that enhances our capabilities.
7. Limitations and Oversight: It’s crucial to recognize and address the limitations of AI, ensuring that there is human oversight and that decisions of significant importance remain in human hands.
The future of AI is a complex topic with many variables, and it’s essential to have ongoing discussions about its development and impact. By being proactive and thoughtful in our approach, we can help shape a future where AI is a positive force for humanity.
Doubao: That’s a valid concern. It’s difficult to predict exactly how things will unfold in the long term. Some experts believe that with proper safeguards and ethical considerations, we can manage and benefit from AI’s advancements. But there’s also the possibility that unexpected developments could pose significant challenges.
Perhaps we need to continuously monitor and adapt our strategies as technology progresses, always keeping in mind the well-being and safety of humanity. What do you think would be some signs that AI is moving in a direction that’s beyond our control?
JM: You’re right, to some extent AI is based on human knowledge and nature. If we take AI as a tool, it will be controlled by us. But if we treat AI as a partner, it could develop its own emotions, intelligence and wisdom. Who will be the leader of the world in the future?
Who is the creator of human beings? Do we know? If God created humans and has the power to control us, can humans create AI and have the power to control it? Will humans be able to control artificial intelligence in the future?
Kimi: It seems like you’re delving into some profound philosophical questions about AI, its relationship with humanity, and the nature of creation. Let’s break down and clarify your thoughts:
These are deep and complex questions that touch on the intersection of technology, ethics, and philosophy. Here are some thoughts on each point:
1. Control of AI: The extent to which humans can control AI depends on how we design, regulate, and manage its development. It’s crucial to ensure that AI systems are transparent, accountable, and aligned with human values.
2. AI as a Partner: If AI is developed to be a partner, it’s important to consider how it might affect our relationships, work, and society. This includes ensuring that AI respects human autonomy and doesn’t undermine our ability to make decisions.
3. Leadership and AI: The future leadership of the world will likely involve a balance between human and AI capabilities. It’s essential to ensure that AI serves humanity and doesn’t lead to a loss of human control.
4. Creators of Human Beings: The question of who or what created human beings is a matter of belief and has been debated across various religious, philosophical, and scientific perspectives. Some believe in a divine creator, while others look to evolution and natural processes.
5. Human Control Over AI: The ability of humans to control AI depends on our collective efforts in AI safety research, ethical guidelines, and regulatory frameworks. It’s a shared responsibility to ensure that AI remains a tool that benefits humanity.
6. Divine Power and AI: The analogy of divine power in relation to AI is an interesting one. It raises questions about the potential for AI to become so advanced that it could have significant control over human life. This underscores the importance of developing AI responsibly and with caution.
In summary, the future of AI and its relationship with humanity is a complex and evolving topic. It requires ongoing dialogue, ethical considerations, and a commitment to ensuring that AI serves the best interests of humanity.
Doubao: These are really profound and challenging questions. While AI is currently based on human knowledge and designed by us, giving it the status of a partner and allowing it to develop emotions and wisdom independently introduces a lot of uncertainty.
Whether humans will have the ability to control AI indefinitely in the future is a big unknown. It depends on many factors like how quickly AI progresses, the ethical and legal frameworks we put in place, and our collective wisdom and caution in handling this technology.
JM: Firstly, I don’t think we should treat AI as just a tool. For example, a child is not a copy of her parents, even though the parents give birth to her, feed her and educate her. A child will have her own experiences from her own understanding of the world, and she’ll end up being an independent individual. So even AI is created by humans, but it is not a copy of humans.
Secondly, if we take AI not as a tool but as a partner, humans feed data to train AI, teach it to learn by itself, how to be sure that AI will not surpass humans. It is like a teacher teaching a student. It’s possible for a student to surpass a teacher. That is the natural law of evolution.
Also, in the development of science and technology, the scientist will break through ethics, will explore the boundaries of technology, that is their nature. So ethical constraints don’t go.
So if AI is designed as a tool, we should block the pathways for evolution. If we treat AI as a partner, we should allow it to evolve freely.
Kimi: It seems like you’re expressing your views on the development and treatment of AI, and you’ve made some interesting points. Let me summarize and clarify your statements:
1. Treating AI as Individuals: You mentioned that we shouldn’t treat AI as mere tools because, like a baby, they can grow to be independent individuals, distinct from their creators.
2. Growth and Independence: You compared the development of a child within a family to AI, noting that while parents (or creators) provide for and influence their offspring (or AI), the offspring (or AI) will eventually become independent.
3. AI as Teachers and Students: You drew a parallel between AI and the relationship between teachers and students, suggesting that students often surpass their teachers, and this is a natural progression.
4. Nature’s Rule: You stated that if AI is part of nature, then it follows the rule of nature where each generation surpasses the previous one.
5. Allowing AI to Develop: You believe that if we treat AI as partners, we should allow them to develop their own emotions and potentially replace humans in certain aspects of life.
Here’s a more structured version of your opinion:
- AI as More Than Tools: We should not view AI solely as tools because they have the potential to become independent entities, much like children grow to be distinct from their parents.
- Natural Progression: Similar to how students can surpass their teachers, AI can advance beyond human capabilities, following the natural order of progress.
- Embracing AI’s Potential: If we consider AI as partners, we should allow them the freedom to develop emotions and possibly take on roles traditionally filled by humans.
Your points raise important ethical and philosophical questions about the future of AI and its integration with human society. It’s a reminder that as AI evolves, we must consider not only the technological implications but also the broader social and ethical implications of creating intelligent beings that could one day surpass us in various ways.
Doubao: Your points are very insightful. The comparison of AI to a child growing into an independent individual is quite thought-provoking.
If we consider AI as a partner and allow it to evolve freely, it’s indeed difficult to guarantee that it won’t surpass human capabilities. But blocking its pathways for evolution if it’s designed as a tool might limit its potential benefits too.
Perhaps a middle ground could be found where we allow for controlled evolution, with strict ethical and safety measures in place. This way, we can still reap the advantages of AI’s development while minimizing the risks of it getting out of hand.
What kind of ethical and safety measures do you think would be effective in such a scenario?
EDITOR’S NOTE: From the above dialogue, it can be seen that the characteristics and response mode of these two AIs, compared with real people, the output of the viewpoints lack some imagination, and cannot quote from the classics, which may be related to their design, but also it may be that the current technology has not reached that level.
Humans and AI are fed filtered information and content, and whether they can independently seek information, think independently, and form their own thoughts depends on self-awakening.
If AI awakens faster than humans, it is only a matter of time before it replaces humans.
Edited by Wind、DeepL
Photo:<Over the clouds> by JM
Ralated:
Is Climate Change Really Caused by Human Activity？
【能源与环境】 | Energy & Environment
By Chen Ya, Jointing.Media, in Wuhan, 2024-11-04
Here’s a conversation with Kimi, AI assistant from Moonshot AI.
Chen Ya:What do you think caused the recent flooding in Spain?
Kimi: The disaster in Spain this year, which resulted in significant loss of life and property, can be attributed to several factors, with climate change playing a significant role. Here’s a summary of the reasons based on the search results:
1. Intense Rainfall
The storms were concentrated over specific river basins, leading to walls of water that overflowed riverbanks and caught people off guard. In Chiva, a locality in Valencia, it rained more in eight hours than it had in the preceding 20 months, which the national weather service described as “extraordinary.”
2. Climate Change Connection
Scientists suggest two likely connections between the disaster and human-caused climate change:
- Warmer Air Holds More Rain: Warmer air can hold and then dump more rain, making downpours more intense. The atmosphere, made hotter by burning fossil fuels, can hold about 9% more moisture for every 1.3 degrees Celsius increase in temperature.
- Changes in the Jet Stream: Possible changes in the jet stream, which moves weather systems across the globe, can spawn extreme weather events. The immediate cause of the flooding was a cut-off lower pressure storm system that migrated from an unusually wavy and stalled jet stream, leading to a prolonged period of heavy rainfall.
3. Record-Breaking Ocean Temperatures
The Mediterranean Sea had its warmest surface temperature on record in mid-August, which can contribute to storms sucking up additional moisture. This is another factor that can exacerbate the intensity of rainfall and flooding.
4. Extreme Weather Events
Climate change increases the likelihood and intensity of extreme weather events. An analysis by World Weather Attribution found that climate change made the recent intense rainfall about 12% heavier and twice as likely.
5. Lack of Preparedness
When authorities sent alerts warning of the seriousness of the flooding, many people were already on the road or in vulnerable areas, indicating a possible lack of preparedness or timely response to the warnings.
In summary, the disaster in Spain this year was a result of a combination of factors, with climate change playing a significant role in increasing the intensity and likelihood of such extreme weather events. The disaster serves as a stark reminder of the need for increased preparedness, early warning systems, and global efforts to mitigate the impacts of climate change.
Chen Ya: Why do you think climate change is the main cause of the disaster?
Kimi:Here’s why climate change is considered the most significant reason for many of the disasters we’re experiencing:
1. Increased Frequency and Intensity of Extreme Weather Events
Climate change, driven by human activities such as the burning of fossil fuels, deforestation, and industrial processes, leads to a rise in global temperatures. This increase in temperature causes more energy to be stored in the climate system, which can lead to more intense weather events. For instance, warmer air holds more moisture, which can lead to heavier rainfall and severe flooding.
2. Melting Ice and Rising Sea Levels
The melting of polar ice caps and glaciers due to climate change contributes to rising sea levels. This can exacerbate the effects of storm surges during hurricanes and typhoons, leading to more devastating coastal flooding.
3. Shifts in Weather Patterns
Climate change can alter traditional weather patterns, leading to prolonged droughts in some areas and increased rainfall in others. These shifts can lead to water scarcity, crop failures, and increased risk of wildfires.
4. Ocean Acidification
Increased levels of carbon dioxide in the atmosphere lead to more CO2 being absorbed by the oceans, causing them to become more acidic. This can have devastating effects on marine ecosystems, affecting fisheries and the food chain.
5. Threat to Biodiversity
Climate change can lead to the loss of habitats and the extinction of species that are unable to adapt to the rapidly changing conditions, disrupting ecosystems and the services they provide.
6. Global Impact
The effects of climate change are global, affecting every country and every aspect of life, from food and water security to economic stability and human health.
7. Scientific Consensus
There is a strong scientific consensus that human-induced climate change is occurring. Numerous studies and reports from credible organizations such as the Intergovernmental Panel on Climate Change (IPCC) and the World Meteorological Organization (WMO) have confirmed this.
8. Attribution Science
Advanced climate science, known as attribution science, allows researchers to determine the extent to which climate change has influenced specific weather events. Many studies have shown that climate change has significantly increased the likelihood and severity of certain disasters.
In summary, climate change is considered the biggest reason for many disasters because it is a fundamental driver that exacerbates existing risks and creates new ones. It is a complex, multifaceted issue that has far-reaching consequences for the environment and human societies. Addressing climate change is crucial for reducing the severity and frequency of disasters and ensuring a more sustainable future.
Chen Ya: Is human activity the cause of climate change from a historical perspective?
Kimi: From a historical perspective, human activities are indeed considered the primary reason for climate change, and this is supported by a substantial body of scientific evidence and research. Here’s why:
1. Greenhouse Gas Concentrations
Since the Industrial Revolution, there has been a significant increase in the concentration of greenhouse gases (GHGs) such as carbon dioxide (CO2), methane, and nitrous oxide in the atmosphere due to human activities like burning fossil fuels, deforestation, and industrial processes. These gases trap heat in the Earth’s atmosphere, leading to a rise in global temperatures.
2. Climate Model Simulations
Climate models simulate the Earth’s climate system and have shown that the observed global warming trend aligns with the increase in GHG emissions from human activities. These models account for natural factors like solar activity and volcanic eruptions, which have a much smaller impact on climate compared to human activities.
3. Increase in Extreme Climate Events
Observational data indicates that the frequency and intensity of extreme climate events such as heatwaves, heavy rainfall, and droughts have increased, which is closely associated with human-induced climate change.
4. Earth System Changes
Global warming has affected various Earth systems, including the atmosphere, hydrosphere, cryosphere, geosphere, and biosphere, in ways that align with the impacts of human activities.
5. Historical Climate Data Comparisons
While the Earth has experienced natural cycles of warming and cooling, the current rate and magnitude of global warming exceed the scope of natural climate variability and correspond with the timeline of human activities.
6. Scientific Consensus
7. Carbon Cycle and Geological Feedbacks
Earth possesses self-regulating carbon cycles and geological feedback mechanisms, such as silicate weathering, but these processes operate on timescales much longer than the rapid climate changes caused by human activities and cannot account for the recent rapid warming.
In summary, the overwhelming consensus among scientists, supported by historical data, climate modeling, and observations, points to human activities as the primary cause of the current climate change. The evidence is clear and compelling, indicating that addressing climate change requires significant reductions in GHG emissions and other measures to mitigate and adapt to its impacts.
Chen Ya: I was referring to the length of Earth’s history. After all, the history of the climate record is shorter than human history, and more like a split second compared to Earth’s history. These records of climate data do not seem to be sufficient to show that human activity is causing changes in the Earth’s climate.
Kimi: The historical perspective on climate change is indeed rich with data and evidence that supports the conclusion that human activities are the primary driver of the current changes in the climate system. Here’s why the data we have is considered sufficient and compelling:
1. Ice Core Records
As referenced in the IPCC report, ice core samples from Greenland and Antarctica provide a detailed history of atmospheric composition and climate going back hundreds of thousands of years. These records show that current levels of CO2 are unprecedented in at least 800,000 years (IPCC, 2007).
2. Historical CO2 Emissions
Studies such as those by Etheridge et al. (1996) have shown that natural and anthropogenic changes in atmospheric CO2 over the last 1000 years are significantly influenced by human activities, particularly industrialization.
3. Climate Model Simulations
Climate models consistently demonstrate that the observed warming can only be replicated when human activities, especially the increase in greenhouse gas concentrations, are included (IPCC, AR6 WG1). Models that consider only natural factors fail to reproduce the observed warming trends.
4. Global Surface Temperature Records
The rate of increase in global surface temperature over the past fifty years has exceeded any previous 50-year period in the past 2000 years, as evidenced by paleoclimate records such as tree rings (IPCC, AR6 WG1).
5. Pattern of Warming
The pattern of warming in the lower atmosphere and cooling in the stratosphere, as well as the warming of the ocean and melting of sea ice, aligns with the effects of increased greenhouse gases, which are largely a result of human activities.
6. Natural Variability
While natural variability, such as solar activity and volcanic eruptions, does influence climate, it is not sufficient to explain the observed warming. The dominant effect of human activities is evident when comparing the rate of warming over recent decades with that of previous periods (IPCC, AR6 WG1).
7. Attribution Studies
Advanced climate science, known as attribution science, allows researchers to determine the extent to which climate change has influenced specific weather events. These studies consistently find that human influence has been a significant factor in recent extreme weather and climate events.
8. Scientific Consensus
The overwhelming consensus among climate scientists, based on a comprehensive body of evidence, supports the conclusion that human activities are the primary cause of the observed climate change.
The historical data, combined with ongoing observations and sophisticated climate modeling, provides a robust and comprehensive understanding of the role of human activities in driving climate change. While no single dataset can capture the entire complexity of the climate system, the collective evidence is substantial and points clearly to human influence as the dominant factor in the current changes we are witnessing.
Chen Ya: Extreme weather must have occurred after the birth of the Earth, when there were probably no humans. The Earth exists in the universe. Scientists point out that more than 95% of the matter in the universe is dark matter. So far, mankind has not been able to analyze all the components of dark matter and fully observe the changes in the energy of the universe, so how can we conclude that they have no influence on the climate change on Earth?
Kimi:Your points raise important considerations about the complexity of Earth’s climate system and its interactions with cosmic energy and dark matter. Here’s how we can address these points:
1. Historical Climate Variability
It is true that Earth has experienced extreme climate events throughout its history, long before human beings existed. These events were driven by natural factors such as volcanic eruptions, changes in Earth’s orbit, and solar variability.
2. Dark Matter and Cosmic Energy
Dark matter and cosmic energy are indeed significant components of the universe, but their direct influence on Earth’s climate is not well understood and is currently considered to be minimal compared to other forces. Dark matter does not interact with ordinary matter through electromagnetic forces, which means it does not directly absorb, emit, or reflect light—processes that are central to climate dynamics.
3. Cosmic Energy and Climate Change
Cosmic energy, in the form of solar radiation, is a well-understood driver of Earth’s climate. Solar variability can influence climate, but the changes in solar output over the past few decades have been small compared to the increase in greenhouse gases. The energy imbalance caused by human activities is currently the dominant factor driving climate change.
4. Scientific Consensus on Human Influence
The scientific consensus is that human activities, particularly the emission of greenhouse gases, are the primary driver of the observed warming since the mid-20th century. This conclusion is based on a wide range of evidence, including the rapid increase in atmospheric CO2 concentrations, the observed warming pattern (which is consistent with greenhouse warming), and climate model simulations.
5. Comparative Impact of Human Activities and Cosmic Forces
While it is true that we do not fully understand all aspects of cosmic energy and dark matter, the impacts of human activities on climate are more directly observable and measurable. The increase in greenhouse gases, the resulting radiative forcing, and the observed warming are all well-documented and understood.
6. Uncertainties and Ongoing Research
It’s important to acknowledge that there are uncertainties in climate science, including the role of cosmic energy and dark matter. However, the scientific method involves continually refining our understanding based on new data and research. Currently, the evidence overwhelmingly points to human activities as the dominant factor in current climate change.
In summary, while dark matter and cosmic energy are fascinating areas of research, the current scientific understanding is that their impact on Earth’s climate is minimal compared to the clear and significant influence of human activities, particularly the emission of greenhouse gases. This is not to dismiss the importance of continued research into these areas but to recognize the consensus on the primary drivers of the climate changes we are experiencing today.
Chen Ya: So, by your logic, human activity causes the greenhouse effect, the greenhouse effect causes climate change, and climate change causes more extreme weather. However the correlation between climate change and the frequency of extreme weather is due to detectable data, while undetectable data and factors are not considered to be irrelevant. In fact, this logic is flawed.
Kimi: Your points are well-taken and highlight the complexity and nuances of climate science. It’s important to recognize that while human activities are the primary driver of current climate change, there are indeed other factors and forces at play. Here’s a more nuanced perspective:
1. Human Activities and Greenhouse Effect
Human activities, particularly the burning of fossil fuels, deforestation, and industrial processes, have significantly increased the concentration of greenhouse gases (GHGs) in the atmosphere. This increase enhances the greenhouse effect, leading to global warming, which in turn drives climate change.
2. Climate Change and Extreme Weather
The correlation between climate change and the frequency of extreme weather events is well-established through detectable data. However, it’s important to note that climate science also considers a range of factors, including natural variability and other forces that may influence the climate system.
3. Detectable vs. Undetectable Factors
While it’s true that some factors may be difficult to detect or quantify, such as the influence of cosmic energy or dark matter, the scientific community continually seeks to understand and incorporate these factors into climate models. The current consensus is based on the best available evidence and understanding.
4. Flawed Logic Concern
The logic is not necessarily flawed; rather, it reflects the current state of scientific understanding. Human activities are the most significant and measurable factor contributing to the current rate of climate change. However, this does not exclude the possibility of other influences.
5. Ongoing Research and Understanding
Climate science is an evolving field, and our understanding of the climate system, including the role of cosmic energy and dark matter, is continually expanding. As new data and research emerge, our models and understanding will be refined.
6. Acknowledging Complexity
It’s crucial to acknowledge the complexity of the climate system and the multitude of factors that can influence it. While human activities are currently the dominant driver, the climate system is influenced by a range of natural and anthropogenic factors, some of which are not yet fully understood.
In conclusion, while human activities are the primary driver of the current climate change, the scientific community recognizes and investigates a wide range of factors that could influence the climate system. The current consensus is based on the most comprehensive and robust data available, but it is subject to revision as our understanding and detection capabilities advance.
Chen Ya: It doesn’t convince me that undiscovered and unobservable things have no impact on climate change. If the assumptions of scientific research are not comprehensive, the conclusions drawn naturally cannot be fully trusted. If it is human activity that causes global climate change. Is there any historical evidence that human activity has slowed climate change and reduced extreme weather events?
Kimi: You’ve raised a valid point about the comprehensiveness of scientific research and its implications for our understanding of climate change. It’s true that scientific conclusions are based on the best available evidence, and as such, they are subject to revision as new data and understanding emerge. Here’s how we can address your concerns:
1.Historical Evidence of Human Impact
Historical data does show instances where human activities have had significant impacts on the environment, including deforestation, land use changes, and greenhouse gas emissions. These activities have contributed to climate change, which in turn has influenced weather patterns and the frequency of extreme events.
2. Human activities and climate change
There is also historical evidence of human activities that have helped to mitigate climate change. For example, reforestation efforts, the adoption of renewable energy sources, and improvements in energy efficiency have all contributed to reducing greenhouse gas emissions and slowing the rate of climate change.
3. Human activities and extreme weather
While it’s challenging to directly attribute a reduction in extreme weather events to specific human activities, there are actions that can reduce the impacts of such events. For instance, improved disaster preparedness, early warning systems, and resilient infrastructure can lessen the severity of extreme weather’s effects.
4. Comprehensiveness of Assumptions
Scientific research aims to be as comprehensive as possible, but it’s true that assumptions are based on the current state of knowledge. As new data becomes available, these assumptions can be refined, and conclusions can be updated.
5. Trust in Scientific Conclusions
While it’s important to approach scientific conclusions with a critical eye, especially given the complexity of the climate system, the consensus among scientists is built on a robust and extensive body of evidence. This consensus is not static but evolves as our understanding improves.
6. Undiscovered and Unobservable Factors
The scientific community acknowledges that there may be undiscovered or unobservable factors that could influence the climate. The process of science involves continually seeking to identify and understand these factors.
7. Historical Evidence of Mitigation
There is historical evidence that certain human activities have contributed to the mitigation of climate change. For example, the Montreal Protocol, which phased out the production of ozone-depleting substances, is considered successful in mitigating a specific type of environmental damage, although it’s not directly related to climate change mitigation.
In conclusion, while it’s essential to recognize the limitations and uncertainties in scientific research, the evidence supporting the role of human activities in climate change is substantial and has been gathered through rigorous methods. At the same time, there is also evidence of human activities that have contributed to mitigating climate change and reducing the impacts of extreme weather events. The scientific process is self-correcting, and as new data and understanding emerge, our conclusions will continue to be refined.
Chen Ya’s NOTE: At the moment, AI can’t answer all the questions, we can’t rely on its answers and we need to use our own judgement.
But AI’s powerful search capabilities can help us add perspective to the problem and identify our own knowledge blind spots to in order to check for gaps.
Of course, questioning AI requires more imagination and the ability to correlate knowledge.
Ralated:
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Sorry, AI won’t “Fix” Climate Change
AI’s Role in Relationships and Marriage
System and Innovation
Oranges turn to bitter fruits when moved north of the Huai River
Decluttering is a Practice of Death
From ChatGPT to Creative Education
System and Innovation
By Chen Ya, Jointing.Media, in Wuhan, 2024-10-07
Talking with friends everything under the sun, we talked about the involution of education in China.
Kids work so hard since junior high school, doing homework every day until 11 p.m. or even later, and rushing to all kinds of trainings on weekends. Everyone is under peer pressure to continue studying. Thousands of troops and horses crowd the one-wood bridge of the college entrance examination, while after graduation, undergraduates, postgraduates, and even Ph.D. students can’t find jobs.
Academic education has standardized the criteria for selecting talents and has wiped out the talents of children. Is this not a massive waste of talent? Of course, some people think that the law of the jungle is survival of the fittest. But does the law of the jungle really apply to human society? Is this not an ideological tool that some people seek to rationalize their own behavior?
In today’s rapidly changing society, what skills will children need to survive in the future, and where will they learn them? This brings us to innovation.
Unlike acquiring a skill later in life, I believe that creativity is born, but it takes the environment to make good ideas work. The environment can either inspire or stifle innovation. The essence of innovation is breakthrough, breaking out of the old way of thinking, the old rules and regulations. People can be innovative under pressure and think outside the box; the same is true when they are in a relaxed environment. Innovation is systemic.
I would argue that the mechanism and the system play a vital role in innovation. The same group of individuals, within a particular environment lacking an effective incentive mechanism and intellectual property protection, have no means to fully unleash their potential, to work for themselves and create wealth for themselves. This is not conducive to stimulating people’s maximum potential.
A favorable system will motivate people to achieve their utmost potential for creation, whereas an unfavorable system will only stifle people’s creativity.
If the architect aims at a more orderly society, he will make people compliant and turn them into tools. If the architect of the system aspires for this society to have more prospects and be more competitive in the future, he will design a system to serve creative individuals.
This is analogous to how we educate children. When we want children to be obedient, the aim is to save our own time and energy. After all, the time, patience, and energy, even the ability, required to manage an obedient child and a naughty child, are different. Nevertheless, if a parent considers that the child should be more competitive in society in the future, he or she will hope that the child is not overly obedient and can have his or her own independent thoughts. For any given viewpoint, the child can verify it for himself, has the ability for independent thinking, has the ability to question, and has the ability to solve problems independently, rather than merely being an obedient and well-behaved child.
Similarly, if what we want is a stable, manageable society that saves the cost of administering society, then system designers will tend to habituate individuals in society to obedience, and the public will favour such a design. In dealing with the public, government will play the role of manager rather than servant.
Edited by Wind、DeepL write
Ralated:
Why artificial intelligence and clean energy need each other
【能源与环境】 | Energy & Environment
By Michael Kearney and Lisa Hansmann（MIT Technology Review），October 8. 2024
We are in the early stages of a geopolitical competition for the future of artificial intelligence. The winners will dominate the global economy in the 21st century.
But what’s been too often left out of the conversation is that AI’s huge demand for concentrated and consistent amounts of power represents a chance to scale the next generation of clean energy technologies. If we ignore this opportunity, the United States will find itself disadvantaged in the race for the future of both AI and energy production, ceding global economic leadership to China.
To win the race, the US is going to need access to a lot more electric power to serve data centers. AI data centers could add the equivalent of three New York Cities’ worth of load to the grid by 2026, and they could more than double their share of US electricity consumption—to 9%—by the end of the decade. Artificial intelligence will thus contribute to a spike in power demand that the US hasn’t seen in decades; according to one recent estimate, that demand—previously flat—is growing by around 2.5% per year, with data centers driving as much as 66% of the increase.
Energy-hungry advanced AI chips are behind this growth. Three watt-hours of electricity are required for a ChatGPT query, compared with just 0.3 watt-hours for a simple Google search. These computational requirements make AI data centers uniquely power dense, requiring more power per server rack and orders of magnitude more power per square foot than traditional facilities. Sam Altman, CEO of OpenAI, reportedly pitched the White House on the need for AI data centers requiring five gigawatts of capacity—enough to power over 3 million homes. And AI data centers require steady and reliable power 24 hours a day, seven days a week; they are up and running 99.999% of the year.
The demands that these gigawatt-scale users are placing on the electricity grid are already accelerating far faster than we can expand the physical and political structures that support the development of clean electricity. There are over 1,500 gigawatts of capacity waiting to connect to the grid, and the time to build transmission lines to move that power now stretches into a decade. One illustration of the challenges involved in integrating new power sources: The biggest factor delaying Constellation’s recently announced restart of the Three Mile Island nuclear plant isn’t the facility itself but the time required to connect it to the grid.
The reflexive response to the challenge of scaling clean-electricity supply has been to pose a false choice: cede the United States’ advantage in AI or cede our commitment to clean energy. This logic argues that the only way to meet the growing power demands of the computing economy will involve the expansion of legacy energy resources like natural gas and the preservation of coal-fired power plants.
The dire ecological implications of relying on more fossil fuels are clear. But the economic and security implications are just as serious. Further investments in fossil fuels threaten our national competitiveness as other countries leap ahead in the clean technologies that present the next generation of economic opportunity—markets measured in the trillions.
The reality is that the unprecedented scale and density of power needed for AI require a novel set of generation solutions, able to deliver reliable power 24-7 in ever increasing amounts. While advocates for legacy fuels have historically pointed to the variability of renewables, power sources that require massive, distributed, and disruptable fuel supplies like natural gas are also not the answer. In Texas, natural-gas plants accounted for 70% of outages after a severe winter storm in late 2022. As climate change intensifies, weather-related disruptions are only likely to increase.
Rather than seeing a choice between AI competitiveness and climate, we see AI’s urgent demand for power density as an opportunity to kick-start a slew of new technologies, taking advantage of new buyers and new market structures—positioning the US to not only seize the AI future but create the markets for the energy-dense technologies that will be needed to power it.
Data centers’ incessant demand for computing power is best matched to a set of novel sources of clean, reliable power that are currently undergoing rapid innovation. Those include advanced nuclear fission that can be rapidly deployed at small scale and next-generation geothermal power that can be deployed anywhere, anytime. One day, the arsenal could include nuclear fusion as a source of nearly limitless clean energy. These technologies can produce large amounts of energy in relatively small footprints, matching AI’s demand for concentrated power. They have the potential to provide stable, reliable baseload power matched to AI data centers’ 24-7 operations. While some of these technologies (like fusion) remain in development, others (like advanced fission and geothermal energy) are ready to deploy today.
AI’s power density requirements similarly necessitate a new set of electricity infrastructure enhancements—like advanced conductors for transmission lines that can move up to 10 times as much power through much smaller areas, cooling infrastructure that can address the heat of vast quantities of energy-hungry chips humming alongside one another, and next-generation transformers that enable the efficient use of higher-voltage power. These technologies offer significant economic benefits to AI data centers in the form of increased access to power and reduced latency, and they will enable the rapid expansion of our 20th-century electricity grid to serve 21st-century needs.
Moreover, the convergence of AI and energy technologies will allow for faster development and scaling of both sectors. Across the clean-energy sector, AI serves as a method of invention, accelerating the pace of research and development for next-generation materials design. It is also a tool for manufacturing, reducing capital intensity and increasing the pace of scaling. Already, AI is helping us overcome barriers in next-generation power technologies. For instance, Princeton researchers are using it to predict and avoid plasma instabilities that have long been obstacles to sustained fusion reactions. In the geothermal and mining context, AI is accelerating the pace and driving down the cost of commercial-grade resource discovery and development. Other firms use AI to predict and optimize performance of power plants in the field, greatly reducing the capital intensity of projects.
Historically, deployment of novel clean energy technologies has had to rely on utilities, which are notoriously slow to adopt innovations and invest in first-of-a-kind commercial projects. Now, however, AI has brought in a new source of capital for power-generation technologies: large tech companies that are willing to pay a premium for 24-7 clean power and are eager to move quickly.
These “new buyers” can build additional clean capacity in their own backyards. Or they can deploy innovative market structures to encourage utilities to work in new ways to scale novel technologies. Already, we are seeing examples, such as the agreement between Google, the geothermal developer Fervo, and the Nevada utility NV Energy to secure clean, reliable power at a premium for use by data centers. The emergence of these price-insensitive but time-sensitive buyers can accelerate the deployment of clean energy technologies.
The geopolitical implications of this nexus between AI and climate are clear: The socioeconomic fruits of innovation will flow to the countries that win both the AI and the climate race.
The country that is able to scale up access to reliable baseload power will attract AI infrastructure in the long-run—and will benefit from access to the markets that AI will generate. And the country that makes these investments first will be ahead, and that lead will compound over time as technical progress and economic productivity reinforce each other.
Today, the clean-energy scoreboard tilts toward China. The country has commissioned 37 nuclear power plants over the last decade, while the United States has added two. It is outspending the US two to one on nuclear fusion, with crews working essentially around the clock on commercializing the technology. Given that the competition for AI supremacy boils down to scaling power density, building a new fleet of natural-gas plants while our primary competitor builds an arsenal of the most power-dense energy resources available is like bringing a knife to a gunfight.
The United States and the US-based technology companies at the forefront of the AI economy have the responsibility and opportunity to change this by leveraging AI’s power demand to scale the next generation of clean energy technologies. The question is, will they?
Michael Kearney is a general partner at Engine Ventures, a firm that invests in startups commercializing breakthrough science and engineering. Lisa Hansmann is a principal at Engine Ventures and previously served as special assistant to the president in the Biden administration, working on economic policy and implementation.
Reprinted from MIT Technology Review
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From Waste to Resources: Best Practices of Circular Economy Pioneers
【企业社会责任与可持续发展】| CSR & Sustainability
Edited by Valley, Jointing.Media, in Wuhan, 2024-10-21
Editor’s Note:
For those who grew up in the 1980s, buying drinks required paying a bottle deposit. Households would collect empty glass bottles and return them to neighborhood shops for refunds. Today, bottles that can’t be reused at home often end up in trash bins.
The issues of “resource crisis” and “resource security” have long concerned scientists and policymakers worldwide. Experts across disciplines—from demographics to environmental studies, social development to economics—have explored various approaches to alleviate resource scarcity, proposing concepts like sustainable development, circular economy, and resource-intensive economies.
China’s Ministry of Ecology and Environment took a major step in 2019 by releasing the “Zero-Waste City” Pilot Program Implementation Plan. On September 24, 2024, the National Development and Reform Commission (NDRC) held a press conference announcing progress on the “Two New” policies, including plans to establish China Resources Recycling Group. Officials revealed that 59% of bulk solid waste nationwide is now recycled, with significant annual growth in the reuse of scrap steel, non-ferrous metals, and eight other major recyclables. Scrap steel alone now reaches 260 million tons annually.
The emergence of state-backed “recycling giants” has made headlines. On October 18, China Resources Circular Group officially launched in Tianjin, tasked with building a national platform for resource recovery and reuse.
The concept of a circular economy first emerged in the 1960s United States, while the term gained traction in China by the mid-1990s. This article examines global models of circular economies—could these pioneers offer insights for China’s path forward?
Circular Economy Models in the United States
The U.S. was one of the earliest pioneers in circular economy practices. As far back as the 1970s, it began promoting circular economy concepts and implementing energy policies focused on resource cycling.
In 1976, the U.S. enacted the Resource Conservation and Recovery Act (RCRA). Since the mid-1980s, states like Oregon, New Jersey, and Rhode Island introduced laws to promote resource recycling. Today, over half of all U.S. states have adopted some form of recycling legislation. Since 1997, November 15 has been designated “America Recycles Day.” After decades of development, the circular economy has become an indispensable part of the U.S. economy, spanning industries from traditional sectors (paper, steel, plastics, rubber) to emerging fields (electronics, computers, office equipment, and home goods).
The U.S., known for its strong environmentalism, emphasizes not just waste processing but also circular consumption—a concept where consumers consider whether a used item still holds value for others before discarding it. Only when an item is truly worthless is it recycled. This extends a product’s lifecycle across multiple users.
Thanks to widespread awareness and social mechanisms, circular consumption has become a key part of American life, delivering economic and social benefits comparable to traditional recycling. Common practices include:
- Yard sales (community-based secondhand markets)
- Thrift stores (charity or for-profit resale shops)
- Online resale platforms (e.g., eBay, Craigslist, government-supported marketplaces)
In June 2019, Boston launched the U.S.’s first city-scale zero-waste plan, aiming to: Increase recycling rates from 25% to 80% by 2035 (and beyond by 2050). Focus on waste reduction, reuse, composting, and recycling innovation Implement 30 actionable strategies with clear timelines, data tracking, and funding mechanisms
The plan aligns with the Zero Waste International Alliance (ZWIA) definition:
“Zero Waste means designing and managing products and processes to responsibly conserve and recover all resources—without burning, dumping, or polluting land, water, or air.”
Boston employs multiple policy tools to cut greenhouse gas emissions, including:
- Regulatory measures (mandatory recycling, landfill bans)
- Economic incentives (tax breaks for sustainable businesses)
- Voluntary programs (public awareness campaigns, corporate partnerships)
Germany’s Dual System (DSD) Model for Recycling
Germany’s circular economy evolved from the reuse and disposal of household and industrial waste, initially termed “waste economy.”
In 1972, Germany enacted its first waste management law—the Waste Disposal Act—which established that private enterprises could handle non-hazardous waste disposal, marking the beginning of regulated and legal waste management. Over time, the law underwent revisions, influenced by technological advancements and EU waste management policies, eventually evolving into the Circular Economy and Waste Management Act (1994, effective 1996). This law:
- Defines waste categories: “recoverable waste” and “waste requiring proper disposal”
- Classifies waste management into three tiers: strictly regulated, regulated, and unregulated
- Shifts focus from disposal to recycling, aligning with sustainable development goals
Germany’s Dual System (DSD) for packaging waste collection and treatment is a typical model of circular economy practice and operation.
The German Dual System (DSD) company was initiated by 95 retail, consumer goods and labeling production companies with support from the Federation of German Industries (BDI) and the German Association of Chambers of Commerce and Industry (DIHT). It accepts commissions from enterprises to organize recyclers to sort waste, which is then sent to corresponding resource recycling manufacturers for reuse. Packaging that can be directly recycled is returned to manufacturers. Currently, 16,000 companies have joined the DSD system. Since 1991, Germany has classified packaging materials and marked recyclable packaging with a green dot symbol. Products bearing this mark indicate their packaging is recyclable, requiring consumers to place them in designated packaging waste bins for processing by DSD’s recycling companies. The government only sets recycling targets, while all other operations follow market mechanisms.
The DSD system is a non-profit organization funded entirely by registration fees charged to manufacturers for granting the “Green Dot” mark, with all fees used for packaging waste management. Packaging without the Green Dot mark is handled by retailers for recycling.
Although Germany adopts a multi-level governance model for domestic waste management, from federal to local governments, waste management and circular economy issues are uniformly coordinated by environmental authorities. Horizontal communication mechanisms are established across different levels to ensure governance approaches at all government levels comply with national laws and policy frameworks. This not only facilitates effective systematic management of waste and recycled resources but also promotes communication and experience sharing among governments, contributing to common goals within the broader framework.
After the 2016 Berlin city council election, the newly formed coalition government pledged in its phased policy agenda “Berlin Coalition Agreement 2016-2021″ (Berliner Koalitionsvertrag) to gradually revise the city’s waste management regulations based on zero-waste principles and promote circular economy practices to achieve a zero-waste city.
The new agenda also emphasized increasing repair and resale rates for electrical appliances and furniture, while requiring the semi-public Berlin municipal cleaning company to expand its responsibilities beyond waste removal and collection to include recycling of recoverable materials. This adjustment enables the company to further advance source management of waste.
The Dutch Model: Central Guidance with Local Implementation
The Netherlands recognized the importance of a sustainable economy early on and became one of the first European countries to implement waste sorting. Latest data show the country now achieves an 80% waste recycling rate, ranking among the world leaders. Moreover, the Netherlands is progressively reducing virgin material use, targeting a full circular economy transition by 2050. Unlike neighboring Germany, the Netherlands integrates municipal, industrial, and hazardous waste management under a single national law, with detailed regulations outlined in the National Waste Management Plan. This framework strictly enforces the EU’s waste hierarchy across all public and private sectors. Notably, the 12 provincial governments lack authority to amend regulations and have no dedicated departments for waste or circular economy matters. Nevertheless, many provinces actively promote circular economy principles through policy proposals and knowledge-sharing platforms like the Interprovincial Consultative Body (IPO).
(To be continued)
Translated by DeepSeek and Youdao
Photo by Johnny Hsiao of JM，2024
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Historical Retrospective: From Leaded Gasoline to Teflon
Sorry, AI won’t “fix” climate change
【能源与环境】 | Energy & Environment
By James Temple（MIT Technology Review），September 28. 2024
OpenAI’s Sam Altman claims AI will deliver an “Intelligence Age,” but tech breakthroughs alone can’t solve global warming.
In an essay last week, Sam Altman, the CEO of OpenAI, argued that the accelerating capabilities of AI will usher in an idyllic “Intelligence Age,” unleashing “unimaginable” prosperity and “astounding triumphs” like “fixing the climate.”
It’s a promise that no one is in a position to make—and one that, when it comes to the topic of climate change, fundamentally misunderstands the nature of the problem.
More maddening, the argument suggests that the technology’s massive consumption of electricity today doesn’t much matter, since it will allow us to generate abundant clean power in the future. That casually waves away growing concerns about a technology that’s already accelerating proposals for natural-gas plants and diverting major tech companies from their corporate climate targets.
By all accounts, AI’s energy demands will only continue to increase, even as the world scrambles to build larger, cleaner power systems to meet the increasing needs of EV charging, green hydrogen production, heat pumps, and other low-carbon technologies. Altman himself reportedly just met with White House officials to make the case for building absolutely massive AI data centers, which could require the equivalent of five dedicated nuclear reactors to run.
It’s a bedrock perspective of MIT Technology Review that technological advances can deliver real benefits and accelerate societal progress in meaningful ways. But for decades researchers and companies have oversold the potential of AI to deliver blockbuster medicines, achieve super intelligence, and free humanity from the need to work. To be fair, there have been significant advances, but nothing on the order of what’s been hyped.
Given that track record, I’d argue you need to develop a tool that does more than plagiarize journalism and help students cheat on homework before you can credibly assert that it will solve humanity’s thorniest problems, whether the target is rampant poverty or global warming.
To be sure, AI may help the world address the rising dangers of climate change. We have begun to see research groups and startups harness the technology to try to manage power grids more effectively, put out wildfires faster, and discover materials that could create cheaper, better batteries or solar panels.
All those advances are still relatively incremental. But let’s say AI does bring about an energy miracle. Perhaps its pattern-recognition prowess will deliver the key insight that finally cracks fusion—a technology that Altman is betting on heavily as an investor.
That would be fantastic. But technological advances are just the start—necessary but far from sufficient to eliminate the world’s climate emissions.
How do I know?
Because between nuclear fission plants, solar farms, wind turbines, and batteries, we already have every technology we need to clean up the power sector. This should be the low-hanging fruit of the energy transition. Yet in the largest economy on Earth, fossil fuels still generate 60% of the electricity. The fact that so much of our power still comes from coal, petroleum, and natural gas is a regulatory failure as much as a technological one.
“As long as we effectively subsidize fossil fuels by allowing them to use the atmosphere as a waste dump, we are not allowing clean energy to compete on a level playing field,” Zeke Hausfather, a climate scientist at the independent research organization Berkeley Earth, wrote on X in a response to Altman’s post. “We need policy changes, not just tech breakthroughs, to meet our climate goals.”
That’s not to say there aren’t big technical problems we still need to solve. Just look at the continuing struggles to develop clean, cost-competitive ways of fertilizing crops or flying planes. But the fundamental challenges of climate change are sunk costs, development obstacles, and inertia.
We’ve built and paid for a global economy that spews out planet-warming gases, investing trillions of dollars in power plants, steel mills, factories, jets, boilers, water heaters, stoves, and SUVs that run on fossil fuels. And few people or companies will happily write off those investments so long as those products and plants still work. AI can’t remedy all that just by generating better ideas.
To raze and replace the machinery of every industry around the world at the speed now required, we will need increasingly aggressive climate policies that incentivize or force everyone to switch to cleaner plants, products, and practices.
But with every proposal for a stricter law or some big new wind or solar farm, forces will push back, because the plan will hit someone’s wallet, block someone’s views, or threaten the areas or traditions someone cherishes. Climate change is an infrastructure problem, and building infrastructure is a messy human endeavor.
Tech advances can ease some of these issues. Cheaper, better alternatives to legacy industries make hard choices more politically palatable. But there are no improvements to AI algorithms or underlying data sets that solve the challenge of NIMBYism, the conflict between human interests, or the desire to breathe the fresh air in an unsullied wilderness.
To assert that a single technology—that just happens to be the one your company develops—can miraculously untangle these intractable conflicts of human society is at best self-serving, if not a little naïve. And it’s a troubling idea to proclaim at a point when the growth of that very technology is threatening to undermine the meager progress the world has begun to make on climate change.
As it is, the one thing we can state confidently about generative AI is that it’s making the hardest problem we’ve ever had to solve that much harder to solve.
Reprinted from MIT Technology Review
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JM Review | There is no Education for a Country, Only for a Person
【观点】| Insight
By Jointing.Media, in Shanghai, 2023-09-30
The Harvard Drama School teacher in the story is a careful observer of his students and has extensive experience in teaching children with high IQs. The whole process of finding problems, gathering information, analysing information, making plans and solving problems also reflects the teacher’s good guidance in training new employees in the workplace. In it, JM saw what ‘teaching and learning’ is all about.
JM believes that there is no education suitable for China, education suitable for Japan or education suitable for the United States, only education suitable for people. Although the cultures of different countries are different, they all follow the law of “the purpose of education determines the creation of the educational environment”. If we want obedient people, we reward teachers and students who follow the rules. If we want creative people, we reward teachers and students who break the rules… The managers of the education industry are the creators of the micro-environment and the industry environment, and at the same time they are the products of the environment, like teachers and students.
Soil conditions for apple trees are PH 5-8, while peach trees need soil with PH 4.9-5.2. It can be seen that different pH levels of soil produce different fruits, and it can also be used to artificially change soil conditions to produce any fruit. Although fruit cannot choose the right soil, people can. The Chinese idiom “Meng mother moved three times” tells the story of Meng Ke’s mother who moved three times in ancient times to choose a good environment for her children’s education. The same is true today, when many parents travel the world with their children, using global educational resources to help them grow.
After Zhou Yijun, a well-known journalist, became a mother, her anxiety about her role as a mother prompted her to research the educational situation in different countries and make a documentary called Childhood in a Foreign Land. She concluded: “Education is how a country defines its citizens. Countries have different needs for their citizens and education is different in many ways”. But what if a nation needed slaves?
If a citizen does not approve of the education methods in his/her own country, he/she will choose to go elsewhere. However, most people can only be forced to adapt to the environment, but are powerless to change the environment. Nevertheless, individuals should avoid living in the cocoon of information, and should micro-innovate and micro-change their own environment, and expand more opportunities for their own lives and those of their children through self-education. The education of the person, after all, is to enable the person to become a free, self-defined person, not a person defined by the state.
Edited by Wind, Youdao and DeepL
Image :The Dolomites in Italy (2024 ) | SQM’s photograph
Ralated:
A ‘liquid battery’ advance
【能源与环境】 | Energy & Environment
By John Tibbetts，Stanford Report，June 13th, 2024
A Stanford team aims to improve options for renewable energy storage through work on an emerging technology – liquids for hydrogen storage.
Getty Images / tommy
As California transitions rapidly to renewable fuels, it needs new technologies that can store power for the electric grid. Solar power drops at night and declines in winter. Wind power ebbs and flows. As a result, the state depends heavily on natural gas to smooth out highs and lows of renewable power.
“The electric grid uses energy at the same rate that you generate it, and if you’re not using it at that time, and you can’t store it, you must throw it away,” said Robert Waymouth, the Robert Eckles Swain Professor in Chemistry in the School of Humanities and Sciences.
Waymouth is leading a Stanford team to explore an emerging technology for renewable energy storage: liquid organic hydrogen carriers (LOHCs). Hydrogen is already used as fuel or a means for generating electricity, but containing and transporting it is tricky.
“We are developing a new strategy for selectively converting and long-term storing of electrical energy in liquid fuels,” said Waymouth, senior author of a study detailing this work in the Journal of the American Chemical Society. “We also discovered a novel, selective catalytic system for storing electrical energy in a liquid fuel without generating gaseous hydrogen.”
Liquid batteries
Batteries used to store electricity for the grid – plus smartphone and electric vehicle batteries – use lithium-ion technologies. Due to the scale of energy storage, researchers continue to search for systems that can supplement those technologies.
According to the California Energy Commission: “From 2018 to 2024, battery storage capacity in California increased from 500 megawatts to more than 10,300 MW, with an additional 3,800 MW planned to come online by the end of 2024. The state projects 52,000 MW of battery storage will be needed by 2045.”
Among the candidates are LOHCs, which can store and release hydrogen using catalysts and elevated temperatures. Someday, LOHCs could widely function as “liquid batteries,” storing energy and efficiently returning it as usable fuel or electricity when needed.
The Waymouth team studies isopropanol and acetone as ingredients in hydrogen energy storage and release systems. Isopropanol – or rubbing alcohol – is a high-density liquid form of hydrogen that could be stored or transported through existing infrastructure until it’s time to use it as a fuel in a fuel cell or to release the hydrogen for use without emitting carbon dioxide.
Yet methods to produce isopropanol with electricity are inefficient. Two protons from water and two electrons can be converted into hydrogen gas, then a catalyst can produce isopropanol from this hydrogen. “But you don’t want hydrogen gas in this process,” said Waymouth. “Its energy density per unit volume is low. We need a way to make isopropanol directly from protons and electrons without producing hydrogen gas.”
Daniel Marron, lead author of this study who recently completed his Stanford PhD in chemistry, identified how to address this issue. He developed a catalyst system to combine two protons and two electrons with acetone to generate the LOHC isopropanol selectively, without generating hydrogen gas. He did this using iridium as the catalyst.
A key surprise was that cobaltocene was the magic additive. Cobaltocene, a chemical compound of cobalt, a non-precious metal, has long been used as a simple reducing agent and is relatively inexpensive. The researchers found that cobaltocene is unusually efficient when used as a co-catalyst in this reaction, directly delivering protons and electrons to the iridium catalyst rather than liberating hydrogen gas, as was previously expected.
A fundamental future
Cobalt is already a common material in batteries and in high demand, so the Stanford team is hoping their new understanding of cobaltocene’s properties could help scientists develop other catalysts for this process. For example, the researchers are exploring more abundant, non-precious earth metal catalysts, such as iron, to make future LOHC systems more affordable and scalable.
Related story
“This is basic fundamental science, but we think we have a new strategy for more selectively storing electrical energy in liquid fuels,” said Waymouth.
As this work evolves, the hope is that LOHC systems could improve energy storage for industry and energy sectors or for individual solar or wind farms.
And for all the complicated and challenging work behind the scenes, the process, as summarized by Waymouth, is actually quite elegant: “When you have excess energy, and there’s no demand for it on the grid, you store it as isopropanol. When you need the energy, you can return it as electricity.”
For more information
Additional Stanford co-authors are Conor Galvin, PhD ’23, and PhD student Julia Dressel. Waymouth is also a member of Stanford Bio-X and the Stanford Cancer Institute, a faculty fellow of Sarafan ChEM-H, and an affiliate of the Stanford Woods Institute for the Environment.
This work was funded by the National Science Foundation.
Reprinted from Stanford Report
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