by Leigh Haugen
AI’s role in amplifying dominant narratives will continue to stifle dissent, limit open debate, and impose restrictive controls on society. If we allow this to continue unchecked, AI will become a tool for shaping thought, controlling discourse, and eroding the very freedoms it was meant to empower.
This article originally appeared on LinkedIn, and is reproduced here with the author’s permission
The development of large language models (LLMs) has transformed our world in many ways, making artificial intelligence (AI) a powerful tool capable of generating and interpreting massive amounts of information. These models, however, are fundamentally shaped by the data that feeds them—data taken from the internet, which is itself a collection of human input. While AI has the potential to aid in a variety of fields, there is a glaring flaw inherent to its very design: its reliance on human data. If this data is corrupted, biased, or fundamentally flawed, then the AI simply echoes and amplifies those same distortions.
One of the clearest examples of this issue is the topic of climate change. Whether you use a search engine or consult AI for information on climate change, the overwhelming majority of the data you will find supports the concept of catastrophic anthropogenic climate change (CACC). This is no coincidence—it is a reflection of the sheer volume of information that has been generated by those who have accepted this hypothesis, compounded by the biases of institutions and corporations that build the algorithms responsible for curating and ranking this information.
AI and the Dangers of Entrenched Misinformation
Artificial intelligence, by its very nature, is designed to draw conclusions from existing data. However, when that data is overwhelmingly one-sided or biased, AI becomes a tool for amplifying misinformation rather than a mechanism for critical analysis. In the case of climate change, AI is unlikely to offer nuanced perspectives or promote healthy skepticism. Instead, it mirrors the consensus-driven model that has been artificially constructed by political, financial, and globalist interests.
The danger here extends far beyond the academic realm. As LLMs and AI increasingly become integrated into decision-making processes—whether in government, business, or education—this flaw in their design becomes a genuine threat to freedom. The ability to challenge prevailing wisdom and to question powerful institutions is fundamental to a free society. However, if AI consistently promotes only one perspective, it serves to stifle dissent, limit critical thought, and bolster the authority of those in power.
The Problem of Consensus-Based AI
When LLMs are trained on vast amounts of data, their primary objective is to provide responses that align with established facts, most of which are based on widespread human consensus. But what happens when this consensus is wrong? What if the narrative that dominates the conversation is one-sided, incomplete, or even deceptive? In the case of climate change, the dominance of a singular perspective is not the result of an impartial, objective review of all evidence but rather the product of institutional biases, political agendas, and economic incentives.
Every major search engine and AI tool tends to default to sources such as NASA, the IPCC, and the United Nations—organizations that have become synonymous with the promotion of catastrophic climate change narratives. AI, in turn, reflects this consensus, presenting it as incontrovertible truth. In doing so, it stifles genuine debate and prevents alternative viewpoints from receiving fair representation. In reality, there are numerous scientists from a variety of disciplines—including climatology—who question the data, methods, and conclusions drawn by climate change alarmists. Yet their voices are often marginalized, and their work is frequently excluded from mainstream discussions.
The Financial and Institutional Bias Behind the Climate Change Narrative
To understand why LLMs produce biased information on climate change, one must first understand the incentives at play. The climate change movement is backed by powerful political and financial interests. Institutions that support the climate change narrative—whether they be governments, international organizations, or corporations—are heavily invested in maintaining the status quo. For them, the promotion of climate change fear is an opportunity to secure funding, expand influence, and push through policy changes that may not otherwise be politically feasible.
The scale of financial gain is staggering. Climate change research is one of the most well-funded scientific disciplines, with billions of dollars flowing into research grants, green energy subsidies, and carbon credit schemes. Those who control the flow of this money—the climate change advocates in power—stand to gain from perpetuating the belief that climate change is the most pressing threat facing humanity.
The Origins of the Climate Change Scam: A Tool for Control
The origins of the climate change agenda trace back to the 1950s and 1960s, when powerful organizations like the Club of Rome and the Club of Budapest began to lay the foundations for what would become one of the most effective tools for controlling humanity. These elite organizations, composed of influential politicians, business leaders, and academics, sought a way to unite the world under a common cause—a cause that could justify unprecedented levels of government control, wealth redistribution, and societal restructuring.
In their 1972 report The Limits to Growth, the Club of Rome made a striking declaration that would set the tone for the environmental movement:
“In searching for a new enemy to unite us, we came up with the idea that pollution, the threat of global warming, water shortages, famine, and the like would fit the bill… All these dangers are caused by human intervention, and it is only through changed attitudes and behavior that they can be overcome. The real enemy, then, is humanity itself.”
This quote reveals the underlying motive behind the climate change agenda: it was not simply about saving the environment, but about creating a global narrative that could be used to justify control over the masses. By positioning humanity as the enemy, these organizations laid the groundwork for a global environmental crisis that would allow governments and powerful elites to increase their influence over virtually every aspect of life—from energy production and consumption to economic policies and personal freedoms.
Admissions from Climate Change Profiteers
Over the decades, numerous leaders and profiteers of the climate change agenda have made candid admissions about the true purpose of the movement. Far from being a purely scientific endeavor, the climate change narrative has been openly described as a tool for wealth redistribution and centralized control.
Ottmar Edenhofer, a co-chair of the IPCC’s Working Group on Mitigation of Climate Change, admitted in 2010:
“One has to free oneself from the illusion that international climate policy is environmental policy. This has almost nothing to do with environmental policy anymore. We redistribute de facto the world’s wealth by climate policy.”
Christine Stewart, former Canadian Minister of the Environment, went even further when she said:
“No matter if the science of global warming is all phony… climate change provides the greatest opportunity to bring about justice and equality in the world.”
These statements expose the climate change movement for what it truly is: not a scientifically grounded effort to save the planet, but a political tool designed to redistribute wealth, grow government power, and consolidate control in the hands of a few elites. By presenting climate change as an existential threat, they have created a justification for implementing sweeping economic and political changes that benefit the global ruling class while imposing new burdens on ordinary citizens.
Academia’s Addiction to Climate Change Grants
The academic world has not been immune to the allure of the climate change agenda. In fact, academia has become one of the most crucial players in perpetuating the climate change narrative, largely because of its dependence on government funding. In many cases, universities and research institutions are financially reliant on grants from governments and foundations that have a vested interest in promoting the climate change crisis. As a result, all of the scientific research that gets funded and published today is tailored to support the prevailing climate change narrative.
Scientists who express skepticism or who attempt to publish research that challenges the consensus often find themselves blacklisted and ostracized from the academic community. Funding for such research is virtually non-existent, and in many cases, these scientists face career-ending consequences. As a result, academia and the scientific research institutions and publications have become an echo chamber, where the only research that receives financial backing is that which aligns with the climate change alarmism promoted by global institutions.
This relationship between academia and government funding has created a dangerous cycle: scientists and universities receive grants to produce research that supports climate change alarmism, which in turn bolsters the political and economic agendas of the powerful elites and populates the internet with only supporting information. Those same elites then funnel more money back into academic institutions to keep the cycle going.
The Role of Globalist Families and Foundations
It’s no secret that some of the world’s most powerful families and foundations are heavily invested in the climate change narrative. The Rockefeller’s, Rothschild’s, Bloomberg, Ballmer, Bezos, Gates, and other globalist families have positioned themselves to profit immensely from the climate change agenda, while also consolidating power and influence on a global scale. These families and their associated foundations fund climate change research, support activist groups, and even help shape policy through their extensive networks of influence in both public and private sectors.
The Rockefeller family, for example, has long been involved in the environmental movement, using their foundation to fund climate change initiatives and push for policy changes that benefit their investments in green energy. The Rockefeller Brothers Fund has donated millions to climate change advocacy groups and their immense political influence has been instrumental in driving the divestment movement, encouraging institutions to pull their investments out of fossil fuels and redirect them into renewable energy projects—a sector in which they are heavily invested.
Similarly, the Gates Foundation, one of the most powerful philanthropic organizations in the world, has committed billions of dollars to fighting climate change, positioning itself as a key player in global climate policy. Bill Gates himself has been an outspoken advocate for drastic changes in energy policy, pushing for massive investments in alternative energy solutions that align with his own financial interests.
The Rothschild family, known for its vast global financial empire, has also played a significant role in the climate change movement. The Rothschild’s have long been involved in the promotion of carbon trading schemes, which allow companies to “offset” their carbon emissions by purchasing carbon credits. These schemes have become a massive industry, generating billions in profits for financial institutions while doing little to actually reduce emissions.
The Ford Foundation has similarly positioned itself as a major player in the climate change space, funding environmental NGOs and research institutions that promote the climate change agenda. Like the Rockefeller’s, the Fords have used their foundation’s influence to shape policy and push for regulations that benefit their interests in the burgeoning green energy sector.
These globalist families and their foundations are not just passive observers of the climate change movement—they are active participants, using their wealth and influence to shape the narrative, control the flow of information, and profit from the policies they promote. By positioning themselves as champions of the environment, they have managed to secure lucrative investments in green energy, carbon trading, and other climate-related industries, all while consolidating their power on the global stage.
The Climate Change Narrative: A Masterstroke of Global Control
The climate change agenda, far from being a grassroots movement to protect the planet, is a carefully orchestrated o redistribute wealth, consolidate power, and generate massive profits for a small group of global elites. From the Club of Rome’s early declarations to the admissions of modern-day climate profiteers, it is clear that the climate change narrative has always been about control—control over the economy, control over political systems, and ultimately, control over people’s lives.
Academia, dependent on government grants, has become complicit in perpetuating this agenda, churning out research that supports the climate change consensus while suppressing dissenting voices. And powerful globalist families and foundations have seized the opportunity to exploit the crisis, using their influence to profit from the very policies they help shape.
The climate change agenda is not just an attack on scientific integrity; it is an attack on freedom, truth, and the future of humanity. By continuing to promote this false crisis, the elites behind it ensure that resources are diverted from real problems, governments grow ever more intrusive, and the people are kept in a constant state of fear and dependence.
The Carbon Credits Market: A Global Goldmine
One of the most lucrative aspects of the climate change agenda is the carbon credits market, which would quickly become a multi-billion-dollar industry with the potential to generate unprecedented profits for governments, financial institutions, and the wealthiest elites. By commodifying carbon emissions, governments and their allies in the financial world have created an entirely new market where companies can buy and sell the “right” to pollute. This system, which allows corporations to “offset” their carbon footprint by purchasing credits, does little to actually reduce emissions, but it opens the door to vast financial gains for those controlling the market.
At the center of this push towards a carbon credit market is Goldman Sachs, one of the most powerful and influential financial institutions in the world. With its deep ties to governments, central banks, and political leaders globally, Goldman Sachs is driving the financialization of climate change, turning it into an opportunity to generate massive profits. The firm’s influence within the U.S. government and beyond is well documented, with its alumni occupying key positions in the Treasury, the Federal Reserve, and numerous other financial regulatory bodies.
Goldman Sachs, along with other major financial players, stands to profit enormously from the trading of carbon credits. By infiltrating both government and the finance world, they are helping to create the regulatory frameworks and market structures that will allow them to dominate this new financial frontier. Their global reach and unparalleled influence ensure that they are positioned to benefit from the widespread adoption of carbon trading schemes, which, far from being about environmental protection, are about maximizing returns for Wall Street.
Politicians like Al Gore, Barack Obama, Bill Clinton, Joe Biden, and many others in the highest echelons of power have been deeply involved in this scheme. Their advocacy for climate change policies is not solely driven by environmental concerns but also by the incredible opportunity to profit from taxing something as fundamental as the air we breathe. These figures, along with Goldman Sachs and other Wall Street giants, are poised to make trillions through carbon trading schemes. By manipulating regulations, they effectively tax emissions and create massive investment opportunities in green industries—many of which they are already financially tied to.
This is not about saving the planet; it’s about exploiting a manufactured crisis to create a market that benefits a select few at the expense of the public. The carbon credits market is a thinly veiled tax on life itself, and those with the most influence and power are lining up to get their hands in the cookie jar, eager to cash in on the fear and hysteria they have helped create.
The Truth About Funding: Who Benefits?
One of the most common accusations leveled against climate change skeptics is that they are funded by fossil fuel corporations. This is a claim often made by alarmists in an attempt to discredit those who question the prevailing climate change narrative. However, the reality is far more complex, and the truth is often the exact opposite of what alarmists claim.
Fossil fuel corporations, far from being the defenders of climate skepticism, have been largely coerced into parroting the climate change consensus. Under pressure from powerful governments and global institutions, these corporations have been forced to create entire divisions that pretend to support climate change mitigation efforts, aligning themselves with the so-called solutions to an “imaginary crisis.” These corporations are not acting out of genuine concern for the climate, but rather out of fear of retribution.
No corporation wants to risk the wrath of their respective governments. The threat of punitive regulations, new laws, and crippling taxes hangs over their heads. By positioning themselves as being “part of the solution” and pretending to go along with the consensus, they hope to avoid being targeted by politically motivated legislation that could devastate their businesses. In reality, they are playing a strategic game of survival in a climate of governmental intimidation and pressure.
Meanwhile, many of the most vocal proponents of the climate change narrative are heavily funded by governments, NGOs, and other entities that have a vested interest in promoting climate alarmism. These organizations benefit from the fear they spread, whether through securing additional funding, expanding their influence, or advancing global political agendas. The claim that skeptics are the ones influenced by financial incentives is a deliberate misdirection—a tactic designed to hide the fact that the alarmists themselves are the ones profiting from the climate change narrative.
The Suppression of Dissenting Voices
Thousands of scientists across various disciplines have raised serious concerns about the assumptions underlying catastrophic climate change predictions. Some dispute the models used to predict future warming, while others point to historical climate patterns that suggest the earth’s climate is far more complex than the simple narrative of human-caused disaster allows. Yet these voices are rarely heard in public discourse. Why?
The answer lies in the systematic suppression of dissent by those who stand to profit from the climate change narrative. For decades, we’ve seen scientists, politicians, and business leaders pushing policies and technologies that serve their own interests under the guise of “saving the planet.” The result is a dangerous concentration of power in the hands of those who benefit from fear-mongering and a near-total exclusion of voices that challenge this orthodoxy.
The risk AI poses here cannot be overstated. As AI tools are trained on data that has already been curated to reflect one side of the debate, they inevitably perpetuate that bias. This leaves very little room for critical analysis or open debate. By giving the appearance of impartiality, AI can, in fact, contribute to the suppression of legitimate skepticism and alternative theories.
The Real Threat: A Loss of Freedom
The climate change debate, when viewed through the lens of AI-generated information, reveals a much larger and more insidious threat—the erosion of freedom. If AI, which is increasingly relied upon to shape public opinion, policy, and discourse, can only produce answers that align with entrenched narratives, we risk creating a world where dissent is impossible. The suppression of climate change skepticism is not just a scientific issue; it’s a matter of freedom of speech, freedom of thought, and the ability to hold power to account.
In a world where AI dominates the production and dissemination of information, the control of data becomes the control of truth itself. Those who feed the AI their data, whether through search engines, research institutions, or government bodies, hold immense power. If that data is biased, incomplete, or misleading, the AI will echo those distortions to an unsuspecting public. This is the fatal flaw in AI—it cannot rise above the limitations of the data on which it is trained, and as long as that data is influenced by corruptible human interests, AI will remain a tool that mirrors and magnifies the errors, biases, and deceptions of its human creators.
In the case of climate change, this flaw is especially dangerous. The powerful interests that have built the climate change narrative are not only distorting science but also restricting our freedoms. The solution is not more AI-generated consensus but a renewed commitment to open inquiry, dissenting views, and a recognition that human data—and by extension, human institutions—are fallible.
The Opportunity Cost of the Climate Change Agenda
Perhaps one of the most egregious aspects of the climate change agenda is the vast opportunity cost associated with the trillions of dollars being funneled into flawed alternative energy solutions that are incapable of meeting the energy needs of modern civilization. From inefficient wind and solar farms to unproven carbon capture technologies, the world has been led into a costly dead-end that squanders resources without providing the reliable energy required for industrialized societies to function and grow.
If even a fraction of the hundreds of billions of dollars wasted on climate change initiatives were reallocated to solving real, tangible problems, the impact could be profound. Consider the pressing global issues that are often sidelined in favor of the climate agenda—problems like pollution, hunger, disease, and homelessness. These are not hypothetical crises; they are realities faced by millions of people every day, and they are issues that can be addressed with direct action.
Take pollution, for example. While climate alarmists fixate on reducing carbon dioxide—a gas essential for life—far more immediate threats like toxic waste in our oceans, harmful emissions in developing countries, and deforestation remain underfunded and understudied. The obsession with carbon has diverted attention and resources away from these real pollution problems that directly harm human health and ecosystems.
Hunger and disease are other areas where the misallocation of resources is painfully evident. Instead of funneling vast sums into climate change mitigation projects, these funds could be used to build sustainable agriculture, provide clean drinking water, and invest in medical research that saves lives. Diseases like malaria and tuberculosis, which still kill millions of people every year, could see significant progress with a proper infusion of capital. Similarly, homelessness is a growing crisis in both developed and developing nations, but it remains a lower priority while politicians and corporations chase green energy subsidies.
The truth is that solving these real-world problems would have a far more immediate and lasting impact on humanity than the speculative and often illogical crusade against climate change. Yet, the political and financial forces behind the climate change narrative ensure that the vast sums of money and political will are continually diverted towards projects with dubious efficacy. The world is effectively neglecting genuine human suffering in favor of an exaggerated crisis that serves the interests of the powerful and wealthy, leaving the most vulnerable to fend for themselves.
In summary, the climate change agenda is not only a scientific and political farce; it is also an economic disaster with staggering opportunity costs. AI bias is playing a pivotal role in propping up this narrative, influencing both people and the media to accept and promote a one-sided view that serves the interests of the powerful. But climate change is just the beginning. The same inherent flaws in AI—its reliance on biased data, institutional agendas, and consensus-driven information—will extend into many other major subjects that directly impact our freedom and future. From public health and economic policies to energy production and social governance, AI’s role in amplifying dominant narratives will continue to stifle dissent, limit open debate, and impose restrictive controls on society. If we allow this to continue unchecked, AI will become a tool for shaping thought, controlling discourse, and eroding the very freedoms it was meant to empower.
In its present form, AI information is very superficial and currently heavily biased in favor of the preference of the designer of the application
Its very similar to the search engines such as google.
A prime example is the gas stove linked to Asthma study, an agenda driven study that is borderline academic fraud.
do a google search for Gas stove asthma fraud and you will get 200-300 pro hit and maybe 2 or 3 hits actually pointing the the study’s errors.
These are text processors and the designer has to specify which texts to use at least generally. In the present systems alarmist texts are mandated. The NYT, IPCC, EPA, NAS, etc.
This is likely done but training the system on such texts and since alarmism has its own language the system can then select for that language, praising the energy transition for example.
That these systems can be trained that way is a big AI achievement. They flaw is with the trainers not AI. One solution is to build skeptical systems. Musk might do that.
I have a recent article on this issue. The real solution to bias is for the system to describe the debate, not pick a side.
https://wattsupwiththat.com/2024/09/27/ai-could-take-your-computer-from-search-to-research/
“One solution is to build skeptical systems. Musk might do that”
<- Musk is not a skeptic on AGW, and he's besotted with solar power. Peter Thiel is more likely to fund a skeptical AI.
I’m a little confused about whether AI is the problem or whether it is information on which the AI is trained. Is it the volume of information itself or is it the quality of information.
There certainly is a volume of information. Some of it shows that global temperatures are increasing. Some of it shows that there is an increasing energy imbalance between the incoming solar radiation absorbed by the earth and the outgoing thermal radiation emitted by the earth. Apparently the fraction of incoming radiation which gets absorbed is increasing and the fraction of thermal energy that gets emitted is decreasing. Is this the information that is “fundamentally flawed”? There is also volumes of information implicating humans for affecting both of these fractions. Is this the information which is biased?
Is AI the problem or is it scientists publishing too much uncomfortable data?
Horatio – It may be a case of too much publishing
The expert Abraham testifying on Mann’s loss of reputation In Mann V Steryn/simberg trial published and peer reviewed an average of 150-250 studies per year over the last 8-10 years along with his teaching duties. Seems to be a lot of desk research and dearth of actual field work research.
Just an observation
A lie repeated ten thousand times becomes a truth. [Dr. Joseph Goebbels, maybe]
Remember black Founding Fathers?
IA is an expensive BS generator.
From 6 fingured hands to totally fabricated legal case law, all looks very credible, with well formed phrases, all the right jargon and fake refs if needed.
All very convincing UNLESS you know the subject.
I tried chat GTP on El Nino. It got it all backwards. After five failed attempts, I told it there was no point in continuing because it had been wrong 5/5 . It promissed to better next time.
I’ve tested it with simple programming questions , it’s the same. It will provide correctly written lines of code, it just does not do what you asked .
Horatio, the problem with reading is one should do it at a pace that optimizes for comprehension. Your questions are addressed in the piece, some may argue, even answered.
In truth, there are multiple papers that add to the uncertainty of the mainstream science and doubly so if we include the level of understanding your questions evoke. There are others that debunk the models completely (and rightfully so). So yes, scientists publish mucho data that some would find uncomfortable.
Gracias, amigo, por muy buena risa. I’ll try to follow your advice to improve my comprehension.
Sorry, my fault. Red wine im afraid. I enjoyed your comment on my second, slower read
Some people have difficulty with scientific comprehension no matter what speed they read. It seems to me that willful ignorance, personal bias, undereducation, and basic mental capacity; not reading speed, are what limit comprehension.
In my opinion there is a difference between LLM’s used for generating online content, ie news articles, websites, legal contracts, stories, and using ai/ml/remote sensing to track above/below ground water movement, soil carbon sequestration, tree cover, plant health, bio-diversity.
Yes, what Leigh Haugen brings up here about AI is very important in the fight to be able to maintain free debate and free thinking. Examples of this are the quotes below:
“AI’s role in amplifying dominant narratives will continue to stifle dissent, limit open debate, and impose restrictive controls on society. If we allow this to continue unchecked, AI will become a tool for shaping thought, controlling discourse, and eroding the very freedoms it was meant to empower”
AI is just the electronic tool that operates on ready data in an LLM. What is returned to a question can be a simple answer, or a reformulated text based on what is in the database (LLM). Mind you, an LLM is inherently as static as an encyclopedia in book form. There is no thinking, it is just an electronic system that returns only what is requested. But the problematic thing in this context is that an answer in a certain area can depend on a massive one-sidedness in stored data, so the result is a reinforcement of a dominant narrative.
While I accept the idea that there is much virtue signalling in the climate change narrative and many believe that they may need to exaggerate the risk to get a response, thus causing a serious bias in the data that Gen AI will use, this article comes across as a bit of a conspiracy theory from the start – “The climate change movement is backed by powerful political and financial interests. Institutions that support the climate change narrative—whether they be governments, international organizations, or corporations—are heavily invested in maintaining the status quo. For them, the promotion of climate change fear is an opportunity to secure funding, expand influence, and push through policy changes that may not otherwise be politically feasible.” – perhaps the Illuminati – but more likely individuals who want to be liked. Let me know if there were some good points made later – succinctly if possible.
Have you every heard of ESG? AI says …
Government Institutions:
Office of Management and Budget (OMB): By providing more comprehensive climate change funding reports and assessments, OMB can help policymakers make informed decisions and allocate resources effectively.
Environmental Protection Agency (EPA): The EPA’s $27 billion Greenhouse Gas Reduction Fund and initiatives like the Justice40 Initiative can benefit disadvantaged communities and drive emissions reductions.
National Climate Task Force: As a whole-of-government effort, the National Climate Task Force can coordinate and mobilize various agencies to achieve President Biden’s climate goals, creating economic opportunities, health benefits, and household savings.
Private Institutions:
Renewable Energy Companies: Investments in clean energy production and deployment, as mentioned in the National Climate Task Force’s initiatives, can benefit companies like solar and wind farm operators, turbine manufacturers, and energy storage providers.
Climate-Resilient Infrastructure Contractors: By investing in climate-resilient infrastructure, such as sea walls, levees, and green roofs, private contractors can secure contracts and generate revenue.
Climate-Adaptation Consulting Firms: As governments and private companies seek to adapt to climate change, consulting firms specializing in climate resilience and adaptation can provide expertise and services, generating revenue.
Insurance Companies: By investing in climate risk assessments and mitigation measures, insurance companies can reduce their exposure to climate-related losses and generate new revenue streams.
Infrastructure and construction companies: Climate change spending and subsidies may also benefit companies involved in infrastructure development, such as:
Road builders: Companies like Bechtel, Jacobs Engineering, and AECOM
Power plant constructors: Companies like Siemens, GE Power, and Mitsubishi Heavy Industries
Port and terminal operators: Companies like DP World, APM Terminals, and Maersk
Financial institutions: Banks and other financial institutions may benefit from climate change spending and subsidies through:
Providing financial services to governments and infrastructure projects
Investing in climate-related bonds and securities
Examples of financial institutions that may benefit include:
JPMorgan Chase
Bank of America
Citigroup
Goldman Sachs
Morgan Stanley
Brian –
Do you think there’s no “virtue signaling” in the climate change “skeptic” narrative? Do you think no “skeptics” exaggerate the risks of aCO2 mitigation?
Just look at how the Climate etc. host and denizens ate up post after post from Nic Lewis providing a “scientific” analysis to prove Sweden had reached COVID herd immunity in the early Spring of 2020, and how a lack of faith in that exaggeration demonstrated a lack of virtue.
And. That. Proves. Nothing.
It shows that the distinctions between “skeptics” and “alarmists” are bs. Humans are all (in a broad sense) affected by the same cognitive biases and tribalistic tendencies, including the tendency to think that “virtue signaling” is disproportionately distributed across the great climate change debate divide.
It shows no such thing. I’m guessing you have been wrong before. Does that mean you will be wrong on everthing?
OK. It shows that climate “skeptics” aren’t immune from virtue signaling and exaggerated science.
Of course, there’s also a lot of science that would suggest that identity-groups like climate change “skeptics” and climate “realists” would mistakenly think phenomena like virtue signaling and exaggerated science are disproportionately distributed across the great climate change debate divide, and just by coincidence be far, far more prevalent in the group to which the don’t belong.
Sorry, Joshua, I misread. On the point of “virtue signaling and exaggerated science”, you are assuming Nick was doing that, if I am interpreting that correctly. He may (or may not) have been wrong (IDK), but if wrong, it was probably simply an honest mistake.
Josh – you remain obsessed with harping on Nic Lewis premature assessment of Sweden’s herd immunity.
He remained correct on the concept that the only solution for covid was developing broad immunity throughout the general population. A concept that remains lost on all the advocates for mitigation protocols that would never work and did not work.
Joe –
Josh – you remain obsessed with harping on Nic Lewis premature assessment of Sweden’s herd immunity.
Lol. There’s nothing particularly remarkable about the warm embrace at Climate Etc of Nic’s flawed modeling of COVID that was based on over-confident and under-informed assumptions in a context of high uncertainty.
But it’s a convenient and clear example of a broader phenomenon: the subjectivity in how people identify “virtue signaling” and scientific exaggeration.
Josh – you keep demonstrating your obsession.
In the broader context – he remains correct
Get over it
Get a life
Joe –
Lol. OK. Will do.
Why can we not use AI to clarify why blogs like Climate Etc, WUWT, Climate Audit, Jo Nova are not getting the sought penetration of the reading market? Can AI suggest ways to counter the suppression of climate change scepticism? Can AI distinguish between actions that benefit scientific progress versus those that impede it?
I am too busy to fool around with AI scenarios so I have no feel for these questions. Has anyone here tested them already? Geoff S
“Can AI suggest ways to counter the suppression of climate change scepticism?”
Perhaps dial 9-1-1 Musk to fund an AI operation to excise hardwired consensus leanings from itself—a split personality that argues with itself can’t be all bad.
Can AI suggest ways to counter the suppression of climate change skepticism?
ChatGPT said:
ChatGPT
Absolutely! Here are some constructive ways to counter the suppression of climate change skepticism while fostering open dialogue:
Promote Scientific Literacy: Encourage education that focuses on understanding scientific methods, critical thinking, and the importance of peer-reviewed research. This helps people evaluate claims more effectively.
Facilitate Open Dialogue: Create platforms where diverse viewpoints can be expressed respectfully. Encouraging discussions that include skepticism can help clarify misunderstandings and build a better understanding of climate science.
Highlight Diverse Voices: Share perspectives from scientists, activists, and communities that support climate action. Emphasizing a range of credible voices can counteract narratives that suggest a singular viewpoint.
Focus on Common Values: Frame climate action in terms of shared values like health, economic stability, and community well-being. This can resonate with skeptics and foster a collaborative approach.
Use Clear Communication: Simplify complex scientific concepts into relatable terms. Infographics, videos, and storytelling can make the science more accessible and engaging.
Address Misconceptions: Identify and directly address common misconceptions about climate change. Providing clear, evidence-based responses can help dispel myths.
Encourage Local Action: Empower communities to engage in local climate initiatives. When people see tangible benefits in their own lives, they may be more open to understanding climate change.
Foster Critical Media Consumption: Encourage people to evaluate the sources of their information and be critical of sensationalism or misinformation. Media literacy is key in navigating conflicting narratives.
Support Research and Innovation: Advocate for funding and support of research that explores the impacts of climate change and potential solutions. Highlighting innovative approaches can inspire more constructive conversations.
Engage in Policy Discussions: Participate in policy debates and advocate for science-based decision-making. Engaging skeptics in discussions about practical solutions can lead to more productive outcomes.
By combining these approaches, you can create a more informed and engaged public discourse around climate change.
Dan Hughes | October 7, 2024 at 7:31 am |
Can AI suggest ways to counter the suppression of climate change skepticism?
ChatGPT said:
ChatGPT
Dan H – the ChatGPT response is effectively follow the consensus, believe in group think , abandon skepticism, etc.
Ignore all the red flags
The demand to follow the Trofim Lysenko version of science.
Fore Dan Hughes who asked AI a Q and posted several answers, one containing an assertion by AI that “Media literacy is key in navigating conflicting narratives.”
Dan, please ask Chat how it gained its own media literacy. Next, ask Chat how it determined that media literacy is KEY. (Hypothesis, Experimental design, Methods, Results, Interpretation, Uncertainty, References, Publisher.)
What a load of popular delusions and madness of crowds, to borrow an 1841 concept!
Geoff S
Two key AI concepts here (which need to be continually reinforced for all humans) are that (1) AI is heavily consensus-based vs. correctness-based and (2) AI is highly dependent on human-created algorithms which weigh the values of the data. Climate change is only one of a multitude of very critical issues where we should see red flags when using AI. Good article.
I think the problem is a little more complex than what you suggest. I have tested both ChatGPT and Copilot. What I have discovered is that when asked questions about various aspects of the relationship between CO2 and global warming, the initial response has been to produce boiler plate dogma. However, when challenged with counter facts, they readily admit to being wrong. Why didn’t they come to that conclusion on their own without me challenging them? They have access to the same information that I do. Apparently, logic does not take priority over simple facts.
A related problem is that after getting the AI ‘bot to admit that everything it originally said was wrong, it doesn’t save the information and update its programming. Presumably, the next time I ask a similar question I can expect to get the same response as I got initially. There does not appear to be automatic learning such as a child goes through when it discovers that something it believed was wrong. These programs are not sentient, are logic-impaired, and therefore don’t try to logically resolve contradictions. If one isn’t knowledgeable enough to know when they are being fed BS, they are likely to accept the consensus view unquestionably.
That’s quite right. AI is simply a tool. You have to know how to properly use it. And it can be properly used to produce valuable output. A lot of the hysteria about AI comes from those ignorant of that fact.
clyde –
However, when challenged with counter facts, they readily admit to being wrong.
LLMs don’t “admit being wrong.” They’re trained to provide answers that meet expectations. They don’t argue facts. They produce strings of words in line with their training data.
Clyde’s comment – “If one isn’t knowledgeable enough to know when they are being fed BS, they are likely to accept the consensus view unquestionably.”
That is especially true of advocates of renewable energy both with engineering issues and costs. Most of the advocates are easily fooled because that lack an understanding of the basic fundamental concepts.
Joshua, if a human were to write the same words, I would consider it an acknowledgment of them being wrong. The important point is that they no longer assert that what they had just written is true, and diverge from that position. They show some flexibility during that particular session, but revert to their original position at its conclusion. However, as I remarked originally, it is possible to push the ‘bot to the point that it just starts repeating itself and it seems that no further progress is possible.
Clyde –
They show some flexibility during that particular session, but revert to their original position at its conclusion
That’s pretty much my point. There’s no substance to an “admission” of error. It’s just a programmed response with the goal of pleasing the interlocutor
Part quote “— the initial response has been to produce boiler plate dogma. However, when challenged with counter facts, they readily admit to being wrong. ”
A good parrot will come up with the last thing it heard. A bad parrot keeps repeating the most commonly profanity it hears/learns.
But even a rat can have its good uses: https://edition.cnn.com/science/giant-african-rat-wildlife-traffickers-spc/index.html
The issue has been the unrecognizable blending of climate change and weather pattern disruption.
Alpha Lo has a very intelligent substack about how and why our rain forms.
The small water cycle and the carbon cycle are linked.
Artificial intelligence and machine learning will be important tools for repairing small water/carbon cycles that have been impeded by unsustainable forest extraction, tilling up native grasslands, draining of wetlands, and more importantly the over use of salt based fertilizers and glyphosate on our agriculture lands.
Weather patterns stabilize when regenerative agriculture and forestry is practiced. The documentary’s “kiss the ground” and “common ground” are great resources.
As for carbon markets, they are a tool, and like any tool; what is the intent of the user?
Right now, they have been hijacked with an intent to stop co2 emissions in their entirety.
Though, with the reversal of the Chevron decision, the intent of the markets are changing.
My opinion is that the compliance carbon markets will exist, not for net zero, they will exist on the concept of applying exergy modeling for efficiency. Which is just common economic sense.
The voluntary carbon markets will exist for the restoration of our depleted and dying soils, forests, grasslands, and wetlands; stabilizing weather patterns.
Where’s the “currency” come from for this process to function?
BRICS is using gold, silver, petroleum, and voluntary carbon credits to back their currency.
Interesting times we live in.
“Artificial intelligence and machine learning will be important tools for repairing small water/carbon cycles that have been impeded by unsustainable forest extraction, tilling up native grasslands, draining of wetlands, and more importantly the over use of salt based fertilizers and glyphosate on our agriculture lands.”
There is a potential for that. However, the unstated assumption is that the AI will be working with facts that are actually true, in contrast to assumed facts that may well be wrong because they are based only based on a consensus view, rather than a thoroughly vetted analysis.
The problem with so called AI is as it has been with other so called climate informative sites, “GARBAGE IN EQUALS GARBAGE OUT”!
The author has a point.
Strikes me that AI is an ideal platform for the government to more-or-less brainwash the population into believing whatever particular narrative is being pushed by the elite and powerful. While climate change is an example, the implications are far more chilling for freedom, as the author observed.
Say the all-powerful government (and their cohorts in the press) decides to suppress the opposition by flooding cyberspace with lies and distortions for one candidate and glowing reviews for the other. AI, which uses consensus based information, then anoints the “favored” candidate, while the opposition is branded as more-or-less evil. That has already occurred, with the owners of the offending AI driven search engine claiming some form of “programming problem”. No, the result is exactly as intended by the government, press, AI company, and offending political party.
Or maybe the government decides to use a race or religion as the target to take the public’s attention off of the elite and powerful becoming ever more wealthy through various misdeeds. Pretty much what the Nazi did.
The authors fears are real while the threat grows greater every day.
So what to do? For openers, the government must be significantly pruned, with the rot cut out. The pruning must include vastly reducing government grants. The root-cause of the problem is money, so severely cut back the governments ability to raid the taxpayer’s wallet as well as print money.
As far as AI is concerned, make firms creating AI software and firms using AI legally liable for inflicted damages. The government would also be subject to being sued in court. The lawyers would have a field day, but that is OK. The point is to inject significant financial risk into the mindless or malicious use of AI.
“… whatever particular narrative is being pushed by the elite and powerful.”
I think that should be “rich and therefore powerful.” Elite, not so much.
The behavior of the AI ‘bots isn’t all that different from the ‘news’ media that provide opinion pieces and slide shows on politically contentious topics, and use censorship to suppress any countering facts offered by a reader. However, this is a matter of Artificial Stupidity because people are growing weary of such behavior, and Europe has recently introduced a mechanism to challenge censorship of ‘social media.’ Hopefully, ‘news media’ will be next.
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Asking ChatGPT the question:
“What are the arguments of those who deny climate change?”
I got the following answer:
“Those who deny climate change often present several arguments, including:
1. **Natural Variability**: They claim that the Earth’s climate has always fluctuated between warm and cold periods, suggesting that current changes are part of a natural cycle.
2. **Scientific Uncertainty**: Some argue that there are uncertainties in climate models and projections, implying that the conclusions drawn by scientists are not definitive.
3. **Data Skepticism**: They question the reliability of climate data, suggesting that it may be influenced by biases, errors, or misinterpretations.
4. **Economic Concerns**: Critics often argue that climate policies could harm the economy, particularly in industries reliant on fossil fuels, claiming that the costs of action outweigh the benefits.
5. **Solar Activity**: Some contend that changes in solar radiation, rather than human activity, are the primary drivers of recent climate changes.
6. **Political and Ideological Beliefs**: For some, opposition to climate change science is tied to broader political or ideological views, including a resistance to government intervention in markets.
While these arguments are common among climate change skeptics, they are largely dismissed by the scientific community, which overwhelmingly supports the view that climate change is real, significant, and primarily driven by human activities.”
… and this is exactly the current state of the problem.
The Planet Surface Rotational Warming Phenomenon:
(everything else equals)
(Tsat.planet.1) /(Tsat.planet.2) =
= [ (N1*cp1) /(N2*cp2) ]^1/16
–
https://www.cristos-vournas.com
It was asserted that Earth has an atmosphere, and Moon doesn’t have. It was said Earth’s atmosphere acts as a blanket, which keeps Earth’s surface warm.
–
What we have discovered, is that the warming-blanket-atmosphere theory is all mistaken. Earth’s atmosphere is very thin, and therefore Earth’s atmosphere is not capable to warm the surface to any significant extend.
–
Earth’s atmosphere doesn’t have any considerable greenhouse warming effect on the surface.
–
https://www.cristos-vournas.com
No, the Earth’s atmosphere is not very thin. We would not be here and alive if it was.
And, the atmosphere (and blankets) do not cause warming – what they do is slow down cooling. Try to understand the difference.
Thank you, BA Bushaw, for your response.
What is very important to accent to is that, at every given moment, lunar surface temperatures are very much differenciated.
Earth’s surface temperatures are also very much differenciated.
When comparing, though, the lunar and Earth’s surfaces’ temperature behaviors, we can clearly see that lunar surface temperatures are way much more differenciated than Earth’s surface temperatures are.
Because Earth’s and Moon’s the respective surface properties, both (N) and (cp), which are mutually compared by their respective (N*cp) products – they are very much different:
Earth(N*cp) /Moon(N*cp) = 155,42
Because Earth’s surface is 155,42 TIMES more prepared, when compared to lunar surface’s properties for the solar energy INPUT capasity.
–
https://www.cristos-vournas.com
Even more disturbing, the proliferation of AI is going to reinforce the beliefs that astrology is a fake science and that the moon landing was real.
A large language model relies upon statistical analysis, which a computer is very good at, to output text in a recognised human language with its many subtleties, which a computer can get hopelessly wrong in spite of decades of apparent machine learning.
How do we know the fails of the latter of these two situations?
If you can bear to suffer subtitles, as many deaf or hard of hearing people do, you will know how poor they can be at least a substantial portion of the time, certainly enough time to make it frustrating (or amusing) for the person using them. In my time sampling live subtitles words like c*** and n***** (that were never said) appeared in the released on screen text, not to mention the many other times the AI fails to understand spelling, tone, proper names, grammar, or even context. And once the AI loses it that bit of spoken language is often gone forever. Of course the AI isn’t failing here – it is the programmer’s attempt to find logic in human randomness and originality (which are available in boatloads in much that humans do) that is at fault.
The written word is more rule-bound and yet, for example, a great many people do not know when and how to use the apostrophe S among many other abuses of written language. At least AI should be able to sort the (really simple) apostrophe S rule out for us. The problem is the AI has to be expressly told what a proper name is and what is plural and what is not, and these are not easy to do in logical programming ways that can be relied upon.
The subtitle conundrum has been with us since computers were gifted word processor software over three decades ago and it isn’t getting easier or better since it doesn’t need power or extra memory. The software needs to understand originality, subtlety, creativity, pathos, humour and every other characteristic of the written word when it can do none of these things. A computer cannot cope with randomness whereas humans know what it is even if they do not always see why it interferes in logical consequences, meaning our programs will never be true to life although to be fair some computer games make a good attempt at parody within their restricted story lines.
There is far too much hype about artificial intelligence for my liking and I sense deeper and much more unpleasant and threatening reasons to what is going on. Putting names to faces and producing AI images for crime solving may appear be a godsend, but to root out the innocent everyday expression of counter argument would clearly be an abuse too far. The problem with computers is that they have no conscience and no sense of guilt or innocence or even limits. They do what they are told even in complete and utter error.
The abusers of AI, including the billionaire sponsors, may be much too like their computers (Do As I Say) for the safety of the average person in the street and I wouldn’t trust them as far as I could throw them. It is important that ordinary people really do understand that computers are Thick with the capital T and programming language creativity plus a lot of hype does not make that any less so.
Speech-to-Text translation is a lot simpler than Large Language Models and work best when trained on a particular person. Although, if Speech-to-Text translation is used in conjunction with an LLM, the predictive ability can also improve the translation. I suspect that TV stations are taking the cheap approach (or using human transcribers for whom English is a second language. :-) )
The original speech to text software were designed for the one user but even after voice training there was a tendency for a peak to be reached and then a steady fall away because the ‘word options’ the software was dealing with became unmanageable in processing numbers and probability selection terms. Professional readers would no doubt have better results than all other users.
The BBC have probably the best instant subtitle software on TV which is good in presentation as well as being superior in output but it still makes huge mistakes, often only a few seconds apart, and does not function as it says on the tin at least thirty percent of the time. Some of this is clearly down to some voices being easier to transcribe than others but there are several other factors (e.g. time taken to transcribe is too long). The good thing about the BBC is that, unlike the other stakeholders in UK TV, it does at least try to meet its legal responsibilities as far as the deaf and hard of hearing are concerned and makes a serious effort to provide a good service. Subscription channels are much worse when it comes to subtitle provision which seems illogical – what do they do with all that income obtained from both advertising and subscription? They certainly don’t think of their customers with any depth.
The issue really is why the translators cannot do better and that is because, as I said before, the whole art of transcription is lost to computer logic (language isn’t logical at depth). There are things computers are good for and there are things they simply find too much for there fragile software to cope. One day we might have a specific programming language for spoken language!!!
“language isn’t logical at depth”
AI is where artificial bears witness. Intelligence comes at the moment artificial is shed. AI is all algo, no “I”. Unfortunately too many believe AI language represents intellect; this makes AI a red herring for intelligence.
“AI is where artificial bears witness. Intelligence comes at the moment artificial is shed.”
Or, to put it another way, there is no real intelligence involved except for the software writer’s role in ensuring an algorithm does exactly what he/she intends it to do every time it runs. There is just far too much hype generated by those who have made billions out of the more mediocre everyday stuff we encounter and curse every day while using mostly eighties/nineties technology. If an algorithm worked thirty years ago, it’ll do just the same now. And if it didn’t work back then then it will not work now.
It makes you wonder how a certain now billionaire ever had the grey matter to invest in another person’s intellectual gifts for such a mediocre end product that has survived perhaps entirely by chance. I wonder what AI would predict if asked how likely that outcome would be given the wider picture?
My take on AI is that it is pure hype although there are many ingenious programs out there that actually really do their originators proud without once claiming intelligence of any kind or nature.
Yes, what Leigh Haugen brings up here about AI is very important in the fight to be able to maintain free debate and free thinking within the now clearly dominant climate issue.
AI is just the electronic tool that operates on ready data in an LLM. What is returned to a question can be a simple answer, or a reformulated text based on what is in the database (LLM). Mind you, an LLM is inherently as static as an encyclopedia in book form. There is nothing that thinks, but it is just an electronic tool that returns only what is requested. But the problematic thing in this context is that an answer in a certain area can depend on a massive one-sidedness in stored data, so the result is a reinforcement of a dominant narrative. The climate issue has precisely because of its one-sidedness converged to become a story or a narrative in LLMs.
“…in this context is that an answer in a certain area can depend on a massive one-sidedness in stored data…”
Which may be the reason why this exercise in AI hype is happening now. People with shallow minds have little need to understand how their, or other’s, opinions have been or are formed.
That delicious quotation about “searching for a new enemy to unite us” doesn’t come from the Club of Rome’s 1972 report, Limits to Growth, but rather from the 1991 book The First Global Revolution. Global warming hadn’t become a big concern in 1972; in fact, the global-cooling panic happened in 1975.
Peter Pearson: “…searching for a new enemy to unite us” doesn’t come from the Club of Rome’s 1972 report, Limits to Growth, but rather from the 1991 book The First Global Revolution. Global warming hadn’t become a big concern in 1972…”
I can’t speak to the provenance of the quote you reference, but I don’t think it’s relevant. The genesis for the AGW narrative began circa 1940, WW2, it was a big topic for many ecological influence peddlers in prewar Germany. AGW was among the ideas promulgated by the ecofascist green movement in the Third Reich. This period produced the first German paper on AGW by Hermann Flohn, in 1941, titled: Man’s Activity As A Factor In Climatic Change. He became chief meteorologist for Luftwaffe High Command the same year.
Regardless of the quote, the author is correct that further inspiration for AGW did come out of Club Rome’s 1972 report. Hermann Flohn was inspired by this report, it set the stage for the prognostic hyperbolic period we’ve witnessed since the turn of the 21st century.
https://mikehulme.org/the-first-climate-scenario-a-drama-in-three-acts/
“Flohn framed his analysis of future climate in the context of the 1970s energy crisis and took inspiration from the Club of Rome’s 1972 report The Limits to Growth. Although in the mid-1970s it was very far from agreed amongst scientists that the world was warming, let alone that the prognosis was for future warming (NDU, 1978), in a series of bold moves Flohn brought together concerns about future energy, economic and population growth and the presumed human influences on climate to speculate about the climatic future.” … “It is our generation which bears responsibility for a global scale problem facing our grandchildren – let us take care to match it”. His rhetoric was very reminiscent of prewar National Socialist ecological language.
Personally, I consider Hermann Flohn to be the father of the AGW movement; Flohn heavily influenced the prognostic playbook for climate that shaped political imagination for heavy handed, coercive government influence leading to the formation of the IPCC.
It’s not surprising that few have ever heard of Hermann Flohn, as a former N@zi he’ll remain hidden. I’ve noticed some web info has been cleansed; but more importantly, there are too many parallels of today’s left to prewar ecofascism to lift the curtain on its details.
Also see:
• Flohn H. 1977: Climate and Energy: A Scenario to a 21st Century Problem. Climatic Change, 1, 5-20
• Flohn H. 1979: Summary Review and Some Thoughts on Future Climatic Evolutions. In: NES Colleque International: Evolution des Atmosohères Planetaires et Climatologie de la Terre, Nice 16-20 Oct. 1978, 569-574.
• Umschau, 1980, (english translation: “C02-Induced Warmth More Dangerous than Nuclear Energy”
Here is a quote from my Blog https://climatesense-norpag.blogspot.com/
Thursday, October 13, 2022
The Rules of the Lebensraum game.
1. SUMMARY
A battle for Lebensraum, i.e. energy,land, and food resources, broke out when Russia invaded Crimea.An associated covid pandemic, and global poverty and income disparity increases now threaten the UN’s Sustainable Development Goals. During the last major influenza epidemic in 1919 world population was 1.9 billion. It is now 7.8 billion+/ – an approximate four fold increase.
The IPCC and UNFCCC post- modern science establishment’s “consensus” is that a modelled future increase in CO2 levels is the main threat to human civilization. This is an egregious error of scientific judgement. The length of time used in making the models is much too small .
A Millennial Solar ” Activity” Peak in 1991 correlates with the Millennial Temperature Peak at 2003/4 with a 12/13 year delay because of the thermal inertia of the oceans. Since that turning point Earth has entered a general cooling trend which will last for the next 700+/- years.
The amount of CO2 in the atmosphere is .058% by weight. That is one 1,720th of the whole. It is inconceivable thermodynamically that such a tiny tail could wag so big a dog.There is no anthropogenic CO2 caused climate crisis.
Because of the areal distribution and variability in the energy density of energy resources and the varying per capita use of energy in different countries, international power relationships have been transformed. The global free trade system and the global supply The global free trade system and the global supply chains have been disrupted.
Additionally, the worlds richest and most easily accessible key mineral deposits have been mined first and the lower quality resources which remain in the 21st century are distributed without regard to national boundaries and differential demand. As population grows,inflation inevitably skyrockets. War between states and violent conflicts between tribes and religious groups within states will continue to multiply…………………………….
6. CO2 -Temperature and Climate.
The whole COP Net Zero meme is founded on the flawed assumptions and algorithms which produced the IPCC- UNFCCC model forecasts of coming dangerous temperature increases.
The “consensus” IPCC models make the fundamental error of ignoring the long- term decline in solar activity and temperature following the Millennial Solar Activity Turning Point and activity peak which was reached in 1990/91 as shown in Figure 1
The amount of CO2 in the atmosphere is .058% by weight. That is one 1,720th of the whole. It is inconceivable thermodynamically that such a tiny tail could wag so big a dog. (13)
Stallinga 2020 (14) concludes: ” The atmosphere is close to thermodynamic equilibrium and based on that we……… find that the alleged greenhouse effect cannot explain the empirical data—orders of magnitude are missing. ……Henry’s Law—outgassing of oceans—easily can explain all observed phenomena.” CO2 levels follow temperature changes. CO2 is the dependent variable and there is no calculable consistent relationship between the two. The uncertainties and wide range of out-comes of model calculations of climate radiative forcing (RF) arise from the improbable basic assumption that anthropogenic CO2 is the major controller of global temperatures.
Miskolczi 2014 (15) in “The greenhouse effect and the Infrared Radiative Structure of the Earth’s Atmosphere “says “The stability and natural fluctuations of the global average surface temperature of the heterogeneous system are ultimately determined by the phase changes of water.”
AleksanderZhitomirskiy 2022,(16) says:
“The molar heat capacities of the main greenhouse and non-greenhouse gases are of the same order of magnitude. Given the low concentration of greenhouse gases in the atmosphere, their contribution to temperature change is below the measurement error. It seems that the role of various gases in the absorption of heat by the atmosphere is determined not by the ability of the gas to absorb infrared radiation, but by its heat capacity and concentration. ”
Zaichun Zhul et al 2016 (17) in Greening of the Earth and its drivers report “a persistent and widespread increase of growing season integrated Leaf Area Index (greening) over 25% to 50% of the global vegetated area from 1982 – 2009. ………. C02 fertilization effects explain 70% of the observed greening trend.”
Policies which limit CO2 emissions or even worse sequester CO2 in quixotic CCS green-washing schemes would decrease agricultural food production and are antithetical to the goals of feeding the increasing population and bringing people out of poverty.
The tropical rain forests and tropical oceans are the main source of the atmosphere’s water vapor and the rainfall essential to life and agriculture on land. Potable and agricultural water supplies are now stretched to their limits in many areas because of the differing national demographics of global population increase. Temperature limits and Net Zero CO2 targets as set in the Paris Accords to ameliorate future temperatures are completely useless when formulating policies relative to adaptation to the actual real world problems. These require more local inputs for particular regional ecosystems delineated by coastlines, major river basins and mountain range limited intra-continental divides.”
The recent 2023/4 peak is a temporary event cause3d by the January 2022 Hunga Tonga–Hunga Haʻapai eruption.
In a nutshell: can AI be programmed to entertain the possibility that it may be wrong.
It is easy to get them to admit being wrong. But they do not learn from that and change future answers because they are just text processors.
Lets assume AI gets it wrong and then is able to learn the correct answer. What is going to stop the next guy from teaching AI his version of the correct answer so that AI learns a “new ” correct answer? Same as random guy altering the Wiki page.
AI subject to the puppet master.
Joe K, I’m assuming that the LLM did not find the counter-fact in a quick search that was used to reduce the cost of the search in time and money. That is, I doubt that the LLMs do an exhaustive search for every question, but use some sort of hierarchical search strategy to be more efficient. Once it has been pointed out that the facts don’t support the initial claim, it should trust what it found in its database (If it was able to make logical inductions.) Thus, it could not be ‘trained’ by some random person with an agenda. However, from what I have seen so far, the LLMs are not good at logic or even mathematics, despite being able to do arithmetic and provide the integral of some function.
Hopefully, AI and the scientific method, ‘are complementary.’
A.I. is not the problem. Jonathan Turley questions whether objectivity is a myth. It’s a legitimate question given Western academia’s advocacy role in the global warming alarmism meme and the amount of censorship in the reporting of supposed ‘news’ in favor of advocacy journalism, all apparently based on the Left-wing political narrative of anti-Americanism.
This is not really about AI, it is about the major problems faced by humanity. At the end is refers scientific, political and economic disasters, but the real issue is on civilisation itself and how easy it is to use propaganda to influence people.
There is an issue not mentioned and I have not seen elsewhere. A number of families are mentioned by name and there are many other who benefit. They must assume that they have sufficient wealth to avoid the impact of the profit making decisions, but they will not avoid the consequences, no matter how big their guns are. It cannot be long before the western civilisation collapses and China, India and Russia will become the dominant nations because they have not fallen for any of the woke nonsense.
Former Google CEO Eric Schmidt says we should go all in on building AI data centers because ‘we are never going to meet our climate goals anyway’
Kenneth Niemeyer and Lakshmi Varanasi
Oct 6, 2024, 6:26 AM MST
https://www.businessinsider.com/eric-schmidt-google-ai-data-centers-energy-climate-goals-2024-10
I wonder how/if this will affect AI answers? ;-)
“…the overwhelming majority of the data you will find supports the concept of catastrophic anthropogenic climate change…This is no coincidence—it is a reflection of the sheer volume of information that has been generated by those who have accepted this hypothesis…”
Getting the atmosphere to cooperate was the hardest part.
Getting people to accept computer projection of the future that are not accurate was also difficult.
“…the overwhelming majority of the data ” is NOT data. It is computer output from failed, rigged climate models.
Enlightened absolutism, or benevolent despotism is not a new idea. The 18th century was peppered with such monarchs, Louis XIV being the prime example. Currently we seem to be in a position of enlightened oligarchs – people with much power, but not obviously the controllers. Apparent control still resides with elected politicians, but they are de facto puppets with restrictions imposed by huge public debts and a need to be able to borrow more. Their rhetoric, no matter their political hue, is merely a means to acquire and maintain office. Their ability to bring about change is restricted by those with real power.
Is absolute oligarchy desirable? Is neo-feudalism desirable? Who are the winners and the losers? Could we have a world in which everyone is a winner? In the words of Kris Kristofferson “freedom is just another word for nothing left to lose”. Has our freedom always been somewhat illusory? As adults we fear the loss of agency, but would you rather be a wild man scratching out an existence, or a domesticated one with lots of creature comforts? Of course we fear change, but change is always as certain as death and taxes. Perhaps our fear is that we will experience loss and the consequent grief that accompanies it?
In the 1920’s auto manufactures worried about over capacity in their industry. What happens when every family has a car? Edward Bernays (the father of public relations) said that wives need cars too. Henry Ford invented built-in-obsolescence. Now we don’t buy cars,we lease them. The bankers need paid,the shareholders need paid, so want is perpetually turned into need in order to keep consumption going. Unfortunately, by the seventies we were, as societies, pretty satiated. We had enough gadgets and were drowning in stuff, so China was brought on board, India was brought on board and the rest of the world is being taken down the path of “development”. We provide water and sewage systems and lots of medicine and this grows the world population. All this keeps the profits coming in, however satiation is still a problem, so we inject fear and invent emergencies to create a new, but unnecessary industrial revolution.
The rich and powerful know that there is a finite amount of time for conjuring tricks to work…
Oj Avon has a hilarious article about flywheels powering Britain. Just spell it backwards :)
Do you know how well the program is going to breed the giant hamsters to run in the flywheels to power them?
” and eroding the very freedoms it was meant to empower.”
Where did you get that strange idea from???
‘The climate science is settled’ will mutate into ‘AI settled this dispute’ or the like.
AI is no more likely to settle disputes than scientists to be honest. AI is an algorithm produced by human beings with ulterior motives. Anyone who says that AI producers don’t have ulterior motives is lying. All AI companies want to make money and they will produce algorithms to please their biggest clients. It won’t be objective truth.
Here are a few unanswered questions:
1. Does AI judge on concensus or will it judge in favour of the outlier who turns out to be right?
2. Is AI capable of detecting sarcasm, sneering, mild-mannered rebuke online? Can it distinguish between the forms of criticism espoused by US WASPs, Russian politicians, Japanese women etc etc?
3. Can AI interrogate an emotional, irrational human being and deduce underlying truths, despite the words being used being inaccurate, self-contradictory etc etc?
I have zero faith that AI will be beneficial to society, in fact in the near-to-medium term it is almost certain that it will be hugely harmful.
The only question is how long it takes the naive population to realise that AI is a con and whether they will still retain enough power to do anything about it?
What’s the chance of AI concluding that Klaus Schwab is a subliminal genocidal eugenicist who secretly admired Adolf Hitler, after all?
“2. Is AI capable of detecting sarcasm, sneering, mild-mannered rebuke online?”
My experience with the AI censors on MSN suggests that they still are having difficulty understanding sarcasm.
Not even one comment on Dr. Curry’s blog has tried to address the catastrophic effects of Hurricane Helene and Milton. NYT article on Gulf of Mexico’s temperatures: https://www.nytimes.com/interactive/2024/10/07/climate/gulf-mexico-ocean-temperature.html?unlocked_article_code=1.Qk4.XHJ_.6G_Xy7Jb-PAk&smid=url-share
Not so…
https://judithcurry.com/2024/08/25/extension-of-the-linear-carbon-sink-model-temperature-matters/#comment-1010668
Your comment was: “Hurricane Helene was not in itself that extraordinary”.
I am waiting to see if Milton has rapid intensification near landfall and shallower, warmer waters. It seems to be one of the effects characteristic of climate change/warmer SST. It happened with Helene: it was predicted to go 3->2 just before landfall, but actually went 3->4. Will Milton see a similar, unpredicted intensification near landfall?
Milton has had unprecedented (over 12 hours) increases in wind and decreases in pressure over open water in the Gulf.
But there is no escape from man-made climate change.
10/01/2024
https://www.realtor.com/news/trends/americans-moving-to-disaster-prone-areas/
“Most people are low-information homebuyers,” says real estate professional and attorney Bruce Ailion, of Re/Max Town & Country in Atlanta. “They do not seek out and are not provided information regarding the climate risks.”
Even if they did have the information, that wouldn’t necessarily stop them.
“I’m not sure people would not buy if they were fully aware of the risks,” Ailion continues. “It doesn’t seem to sink in until after disaster hits, and then, most choose to rebuild in the same spot.”
When a bullet is fired into the air, it lands somewhere.
That’s what a hurricane is- a bullet fired into the air!
I asked AI to critique my analogy, to wit-
Movement:
Both a bullet and a hurricane have a trajectory, meaning they move in a certain direction once propelled.
Unpredictable landing spot:
Similar to a bullet fired into the air, the exact spot where a hurricane will make landfall can be difficult to predict due to factors like wind patterns.
Potential for damage:
Just as a bullet can cause damage upon impact, a hurricane can cause significant destruction when it makes landfall.
Stephen – the hurricane has been discussed in other posts, such as …
https://judithcurry.com/2024/08/25/extension-of-the-linear-carbon-sink-model-temperature-matters/#comment-1010590
If you read the link I posted, you will see there were multiple factors that made Helene much worse over the SE mountains. The area had already been inundated with rain for a week before Helene hit, then there were other weather fronts active. It’s really trite to blame the destruction only on “warm water” or “carbon dioxide”.
Too much to ask for until the people who are paying for it demand that Western academia make America great again which begins with demanding that science respect the scientific method before pushing misinformation to advance a failed Eurocommie agenda– a proven social-economic failure.
Here is a hoot. The number of research articles centered on ChatGPT (with ChatGPT in their title) exceeds 40,000. No human can read all these but ChatGPT can if it has access to these journals. We can ask it about itself!
See https://scholar.google.com/scholar?hl=en&as_sdt=0%2C49&q=allintitle%3A+chatGPT&btnG=
David Wojick: “We can ask it about itself!”
Certainly AI has instant hubris, but its retort is equally quick with humility. This represents AI at peak intelligence.
Here is a technical overview if anyone wants to actually understand this stuff:
“A Brief Overview of ChatGPT: The History, Status Quo and Potential Future Development”
https://www.ieee-jas.net/article/exportPdf?id=a6074c7a-3ff1-4819-89e0-c22e88673a7c&language=en
Regarding LLM’s and science education one of the highest uses would be grade or knowledge level search. Under NGSS science study is activity based so students have to find relevant content that they can understand. Grade level search is impossible with today’s search engines but LLM’s should be able to do it easily as every grade level is a language level. First the bias has to be corrected.
By way of background, some years ago I developed a crude grade level search engine for DOE’s Office of Science. We were building ScienceEducation.gov to go with Science.gov but the project was stillborn. Along the way I mapped the language structure of science education. I studied under Herb Simon, an AI pioneer, and am on the I side of AI. David Wojick, Ph.D. The STEM Education Center http://www.stemed.info/
If AI ever evolves beyond simple regurgitation of data and develops certain human traits such as the BSD (Bulls*** Detector) found to exist in the rostral anterior cingulate cortex by researchers, then it might serve some useful purposes in climate science.
Hundreds of climate science studies have statements similar to the following, which, in their totality, should raise some questions about the consensus narrative.
“ The relative contributions of anthropogenic climate change and internal variability in sea level rise from the West Antarctic Ice Sheet are yet to be determined.” Bradley, 2024. Others, “little direct observational evidence exists”, “unconstrained”, “large gap in understanding”, “poorly represented by state of the art climate models”, “clouds induce largest uncertainty in climate parameters”, different techniques influence final reconstruction”, “considerable uncertainty about the impact from deforestation”, “poorly understood”, “Deforestation Induced Climate Change”, “systematic underestimations”, “large disagreement between observed and simulated ice flows”…..and on and on and on with reasons to be skeptical.
I don’t know what to make of AI. With all the hype and money being spent, it has all the earmarks of a technology that’s not going to pan out. I’ve seen some incredibly bad pictures generated by AI. There’s the classic mouse with the oversized sex organ. I saw an evolution progression of ape to man with two of the ape men being exactly the same. Does AI develop the ability to be lazy and slack off?
I suppose there’s a lot of intellectual grunt work that can be done by AI. Can it make a nice enumerated list of all the flaws in MBH’98? Could it bring dissembling to a whole new level? Could it get MBH’98 back into the IPCC assessment reports?
If you haven’t already used AI, you can use it free on the Brave browser or MS Bing. I find it quite useful for research questions.
Why Earth’s surface is warmer than Moon’s ?
Interesting…
–
https://www.cristos-vournas.com
In science, “you only find what you are looking for, and you only look for what you know.”
–
To be able to find the origin of this whole process, we had to think about the unthinkable. And we did it.
–
Link: https://www.cristos-vournas.com
The Rockefeller’s, Rothschild’s, Bloomberg
Does AI validate such apostrophe abuse?!
Testing AI:
Me: “Over the last century, has the net global uptake of CO2 by terrestrial and oceanic reservoirs been positive or negative?”
Chatgpt: “Over the last century, the net global uptake of CO2 by terrestrial and oceanic reservoirs has been positive. This means that both terrestrial ecosystems (like forests and soils) and oceanic systems (such as the oceans themselves) have absorbed more CO2 than they have released.
However, this uptake is not sufficient to offset the total emissions from human activities, primarily fossil fuel combustion and deforestation, leading to an overall increase in atmospheric CO2 levels. The oceans absorb a significant portion of anthropogenic CO2, and terrestrial ecosystems also act as carbon sinks, but the balance is shifting due to climate change, land-use changes, and other factors.”
This is a quite competent answer that Leigh Haugen and everyone else should agree with (except perhaps with the final “balance is shifting” clause). In no way does it exhibit a “fatal flaw” of AI. With that said, Geoff Hinton, called the “Godfather of AI” and awarded the physics Nobel last week, has his own well documented concerns about AI, even though his politics is miles removed from Haugen’s politics.
If solar is so cheap and nuclear is so expensive, why would Microsoft want nuclear for AI? Computing seems like a process that is not as dependent on a steady supply of energy like say an aluminum smelter. When the supply of electricity goes down, wouldn’t it just make all the multi-threaded computer tasks just run slower? I think the answer is that the steady supply of power allows for full utilization of servers and such. It makes for less redundant acquisition of materials for solar panels and computing machinery, not to mention extra land and transmission resources.
In the event of a blackout emergency, TMI power could easily be diverted from AI. It should still be an asset for grid reliability.
Mike Dombroski | October 12, 2024 at 11:02 pm | Reply
If solar is so cheap and nuclear is so expensive, why would Microsoft want nuclear for AI?
fwiw – one of the major selling points for renewables is the cost less – at least they cost less based on LCOE as reported by Lazards
Yet that advocates fail to notice the huge deceptions in LCOE as presented by Lazards some of which includes
a) comparison of gas combined (gas combined being baseload & Intermediate & peaker generation ) vs wind or solar which only produce in the intermediate demand space which also happens to be the least expensive demand space for electric generation.
b) lazards lcoe only includes the cost of generation, omitting the additional cost of maintaining consistent frequency.
c) LCOE omits the backup costs which include both storage and high levels of redundancy.
Yep, essentially you have to have a backup system with the same capacity as the “renewable” one. IOW, you have to have the same system we have now except it’s call the “backup” system. Batteries remain a possibility, but currently only a theoretical one.
Jim – what I meant by the term for “redundancy” was increasing the size/capacity of the wind farm 2x – 3x more than need for normal wind conditions to have sufficient wind turbine capacity for low wind conditions (plus the battery storage).
Because the extra redundancy, the LCOE needs to be measured on the total cost including the redundant wind capacity even though the redundant capacity is generating unused electricity during normal times. The denominator in the lcoe equation should be the electricity used instead the total electricity generated. ie the electricity that is flared off (that is an oil field term) and/or wasted should be excluded in the LCOE denominator.
When properly computed under normal cost accounting standards (and normal economic standards), the LCOE of wind skyrockets.
Joe – IIRC, LCOE for renewable didn’t take into account the cost of backup generation. Increasing capacity currently is worthless without huge battery farms, which currently is Vaporware.
Jim2,
Here is one of those “theoretical possibilities”. There are many more, and getting better all the time.
https://electrek.co/2023/08/03/worlds-largest-battery-storage-system-just-got-even-larger/
US utility scale generation in 2023: 4,178,000,000 MWh. So that 3,000 MWh is 0.0000718% of the total. Only 4,177,997,000 MWh to go! I wouldn’t hold my breath if I were you!
Jim2, I don’t need to hold my breath – It is happening, no matter what silly things you say.
Re: Adding nuclear power for AI (or crypto)
Looks like sweet deal for big tech (as most of the cost is on the consumer/government) but if something goes sideways and there is a serious radiation accident they bear none of the liability. The monopoly utilities love it because they get a guaranteed return on their investments regardless of who the customer is.
I’m not worried about a natural disaster or mechanical failure because we know how to plan for that. We just have to make sure it’s done up front. Nuclear fission’s fatal flaw is human malfeasance and the evil that lurks in the hearts of men. There is no way to fix that.
We need ultra deep geothermal for safe global base load power until nuclear fusion is practical.
I appreciate what the author of this thread has to say about the state and leaning of the current intelligentsia. I would add that AI, without original thoughts, merely mimics the intelligentsia. The “fatal flaw” therefore must originate with the intelligentsia.
That flaw in my view can be summarized by their belief that government directly or indirectly must be the final arbitrator in solving (actually attempting to solve since solutions are rare) society’s problems both real and imagined. If the intelligentsia view is to change it must be acknowledged at that level and countered with reasoned evidence of that view’s failures.
The combination of artificial intelligence and natural stupidity is a dangerous cocktail.
Artificial intelligences are for the most part oriented towards the development of a BELIEVABLE discourse.
You have to be BRILLIANT, and to be brilliant the recipes are simple; use jargon,
join a consensus (the reason for a consensus is to no longer allow alternative opinions to be expressed, in short “shut up!”), write well-constructed and clear sentences, and above all make the probable speech.
So chatgpt does not hesitate to provide you with bogus paper references because the majority of people (and unfortunately some “scientists” too) are careful not to open the links. A special mention for https://scite.ai/
which provides real references.
Here an article in French which simply explains how chatgpt (and many other products of this type) works
https://leclubcyber.com/le-travailnement-de-chatgpt/
As it is well written, the translation is excellent.
Maybe you could get AI to check if your second link exists.
I happen to be a “scientist” that opens links and at least give them a quick content scan.
I asked ChatGPT: When will the CO2 hoax be over?
ChatGPT said:
The idea that climate change and the role of CO2 are a “hoax” is a viewpoint that contradicts the overwhelming scientific consensus. The evidence for human-caused climate change is supported by extensive research and data from around the world. Addressing climate change is an ongoing challenge that requires collective action, and while some may hope for a quick resolution, it’s more about long-term adaptation and mitigation strategies. Open discussions and scientific literacy are essential for moving forward.
A couple of problems:
1) “Consensus” ain’t science.
2) “…extensive research and data…” refers to the correlation of warming and rising CO2, but correlation without science ain’t science. Recent warming also correlates with ice cream production and the growth in number of pizza restaurants.
3) “Collective action” is the “agenda”.
4) “Open discussions and scientific literacy” don’t exist, except on Skeptic blogs.
From the post:
“To understand why LLMs produce biased information on climate change, one must first understand the incentives at play. The climate change movement is backed by powerful political and financial interests. Institutions that support the climate change narrative–whether they be governments, international organizations, or corporations–are heavily invested in maintaining the status quo. For them, the promotion of climate change fear is an opportunity to secure funding, expand influence, and push through policy changes that may not otherwise be politically feasible.
“The scale of financial gain is staggering. Climate change research is one of the most well-funded scientific disciplines, with billions of dollars flowing into research grants, green energy subsidies, and carbon credit schemes. Those who control the flow of this money–the climate change advocates in power–stand to gain from perpetuating the belief that climate change is the most pressing threat facing humanity.”
And, to the “governments, international organizations, or corpotations”, we need to add “religious followers”.