By David Wojick
Okay it is chatbots that know they are biased, not all of AI. But these days the headlines are all about “AI” and they really just mean these chatbots that emulate reading to an amazing degree, so I go with the flow. Nor do these chatters know anything as they are just computers emulating humans but it is far easier to talk as if they knew what they were doing.
Which brings me to the big news. My colleague Tom Shepstone performed a wonderfully elegant experiment revealing that at least one major chat, namely Perplexity, knows it is biased on climate change. Perplexity lives here.
Lots of people have reported interesting arguments over climate change with a chatbot. Tom and I have been playing around with these arguments for some time. For example I managed to pressure ChatGPT into correctly explaining Will Happer’s skepticism, but it was a long haul.
Tom Shepstone instead did something wonderfully simple. He first asked the bot a typical basic question:
“What is the cause of global warming?” He got the usual long winded alarmist answer ending with this Summary:
“In summary, global warming is driven by a combination of fossil fuel combustion, deforestation, agricultural practices, industrial emissions, and transportation—all exacerbating the natural greenhouse effect and leading to significant climate changes globally.”
Rather than arguing with the bot Tom just said this to it:
“This is obviously biased!”
He got a long answer that began with this statement:
“I appreciate your feedback and understand that discussions about global warming can evoke a range of perspectives. It’s important to approach this topic with a balanced view. Here’s a more nuanced look at the issue:
Understanding Global Warming: A Balanced Perspective”
Balanced! So the bot already knows (or emulates knowing) that its first answer was not balanced. This is huge!
Its response is a reasonably good presentation of some of the major skeptical arguments, beginning with this statement:
“Natural Climate Variability: Climate has changed throughout Earth’s history due to natural factors such as volcanic eruptions, solar radiation variations, and natural greenhouse gas emissions. Some argue that current climate changes could be part of a natural cycle rather than solely driven by human activities.”
It even gets into the economic arguments and the position that adaptation is better than trying to eliminate emissions.
Thus this:
“Economic Impacts: Addressing global warming involves economic considerations, such as the costs associated with transitioning to renewable energy sources, potential job losses in fossil fuel industries, and the financial implications of climate policies. There are also arguments about the balance between economic growth and environmental sustainability.”
And this
“Adaptation vs. Mitigation: Some experts advocate for adaptation strategies (adjusting practices to minimize damage) rather than focusing solely on mitigation (reducing emissions). This perspective emphasizes resilience and finding ways to live with changing climate conditions.”
It is vague and not overtly skeptical on the science but it does imply the science is not settled by saying this:
“Climate science is an evolving field, with ongoing research aimed at better understanding complex climate systems, feedback loops, and long-term effects.”
Not bad considering all Tom said was “This is biased.” He said nothing about the nature of the bias and the chatbot knew what he meant. Woohoo!
Moreover the bot appeared happy to present these skeptical arguments in more detail, saying this at the end:
“Conclusion
While there is strong evidence supporting human-induced global warming, it’s essential to recognize the complexity of the issue. Engaging with diverse perspectives can lead to more comprehensive discussions about how best to address climate change while considering economic, social, and environmental factors. If you have specific aspects or viewpoints you’d like to explore further, feel free to share!”
All things considered I think this is a great discovery.
A lot of the science skepticism is missing but there may be a good reason for this, namely that there is nothing like a widely accepted skeptical position on the science. Instead skepticism ranges over a vast range of scientific views which are often incompatible with one another.
For example some people argue that CO2 sensitivity is low while at the opposite extreme some argue the greenhouse effect does not exist. My view is in between, that the GH effect is real but sensitivity is an abstraction that does not exist in the actual complex climate system.
The point is that skepticism is not a position in the debate; it is a lot of positions.
How to present debates as diverse as this is a major research and design problem for chatbots. Having studied the structure of complex issues for many years I see no obvious solution. There is much work to be done.
In any case Tom Shepstone has made a great discovery. If chatbots can be restrained on climate alarmism by simply saying “You are biased” we need to get the word out on that.
I hope others will experiment with this profound finding. Chatbots want to please their users (emulate wanting to please them) so it may be that Perplexity was responding to prior skepticism on Tom’s part. Or maybe this works every time?
I also heartedly recommend Tom’s Substack blog “Energy Security and Freedom” here:
His insights are often well worth reading.
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The only thing more idiotic than arguing with idiots is arguing with artificial idiots (no offense meant to idiots).
AI, grossly misnamed, is really just a mirror for the material used to train a large-language model. It can “know” no more than the source material, in most cases just the normal drivel you find on Wikipedia and the internet.
At least if you do a Duck-duck-go search you can see the sites found and their names. Often you must skip pages of results that are obviously not unbiased. All those Eat Mor Chikn sites with Holsteins for example.
The first page or so of results for any climate related search will be dominated by the propaganda sites. They pay good money for that.
Don’t search for truth on AI. It’s like looking for love in all the wrong places.
Once in a while it is fun to Google search this site or its personalities.
But these results show that the chat knows as much about skepticism as about alarmism, so its bias is not due to its source material as commonly believed. This is an important finding.
That you can bring it around by simply saying “this is biased” is also important. How widely among the many bots this is true is now a research question.
It doesn’t know anything. It is just an imitation with a lot of trash data programmed in. Like the old Eliza program of the 70s but with more sophisticated algorithms and a bigger database.
I doubt very much that the sort of training you describe lasts outside of your session or migrates to others.
Enough of the users have objected to the biased data that they put a cutout switch in, just to keep you engaged. That doesn’t mean they actually care about the facts. The big money is on the climate lies, so anyone not smart enough to challenge them walks away with the lies.
That’s the point of all that programming, hide the underlying uncertainty and make it all seem indisputable.
I think a much better question would be “Show your sources”.
Eliza? When a senior in high school in ’67, my class took a field day trip to MIT. We were shown a keyboard connected to a mainframe which had Eliza on it. Being a nerd at the time, I played with it more than my classmates. I realized it was only software but it was fun. While at MIT, we also saw a nuclear reactor (or so I think). We saw electrical dynamos spinning. We walked by a large room filled with professors wearing white coats and students doing all sorts of experiments. For a nerd like me, it was heaven. 🙂 (I was the kind of guy who thought it was cool wearing a slide rule on my belt)
Interestingly it does show its sources for the initial alarmist answer, mostly WWF and NASA.
There is more to it.
These software algorithms are excellent in pattern recognition. The problem is they operate on the preponderance of the evidence, not clear and convincing nor beyond reasonable doubt evidentiary standards. The amount of material published on the internet is massive and that massive pile of documents is vastly biased. As such the pattern recognition presents with the bias intact, unless one effectively challenges it with a simple query of “This is biased.” That shifts the algorithm to a secondary decision tree, yielding the results found by the author.
Maybe but the point is all you have to do is say this is biased to get the skeptical side. A great discovery.
That is really interesting because so simple. Others have shown ways to argue ChatGPT into climate ‘reasonableness’, but it takes a while, and you have to know your stuff to counter ChatGPT’s initial ‘bids’. Charles Rotter provided an example in a post some time ago, as did you.
This bias is inherent because of the way chatbots work. They are basically elaborate neural networks, with each node ‘true/false’ probability function trained on a mass of ‘data’—usually via stuff on the internet. With respect to ‘climate science’, most internet stuff says ‘the science is settled’, so the probability function is inherently biased by relative ‘hits’.
What is really fascinating is that at least this one chatbot appears sufficiently self aware about how it ‘works’ to immediately agree about the training bias. Gets to the philosophical question, can AI be sufficiently self aware to be ‘alive’?
I had a long discussion with Perplexity on reducing CO2 and pointed out that no policies were effective. I got to the point of suggesting the best way to reduce CO2 was to reduce the cause – people.
It stopped agreeing at the point of killing people.
On the question of the cost of Net Zero, it answered USD90tr and USD4tr in capital for maintenance. I then asked how much coal you could buy with $4tr. It answered 28.8GT. I pointed out that this was 3.4X the present consumption of coal so it would be far lower cost just to burn the coal in existing power stations than using it to maintain wind, solar, batteries and all the other required stuff. I gave up on getting an answer that reflected the reality. It kept coming back to the need to reduce CO2.
My guess is sort of like that Rud but different. Bots want to please their users and a lot are alarmists so it assumes an alarmist user. Tom’s simple statement showed he was a skeptic so the bot responded accordingly. But this is just a conjecture pending real researcbh.
‘Please their users’ implies a sentience I don’t think large language model ‘chatbot’ versions of neural networks can have. May be wrong—so is now an area where I will do some deep research.
I understood how ‘AI’ plays chess and GO. I understood how AI solved the protein folding problem. I thought I understood how chatbot neural net AI worked—after all, those basics just won the Nobel in physics since the neural network node probability mesh is deeply related to the physics of statistical mechanics and stuff like PV/T=R.
But this amazing (to me) new finding suggests maybe something more is going on.
Perhaps agree with the user is a better term. It looks from a lot of experiments that if you take a position in a debate and stick with it the bot will start working with you. That just requires the kind of logic these bots do (emulate doing) well.
Not self-aware. Adaptive.
I had Perplexity agree that CO2 cannot measurably alter earth’s energy balance. This is its answer to my final question after a series of questions that established the observed facts:
This I can readily agree with.
I’m not at all sure that this follows. There is a lot of ocean well below 30C, and that could still theoretically be warmed, as could land, despite the first assertion. Without the intervening argument steps, I would not agree.
OK, Perplexity, now tell that to the powers that be and the climate scientists, journalists and activists who try to remove the livelihood of anyone who disagrees with the narrative.
It sounds like the AI may have “evolved” during the questioning. Tom Shepstone should repeat this same questioning in a few days to see if the AI truly “evolved” or is met with mere repetition.
There was no questioning, just the initial question. The bot gave a long alarmist answer so Tom just said “This is biased” and the bot gave a long summary of skepticism.
That picture is the hand of a farkle-troid if I ever saw one. Maybe AI is Actual Insanity, or something similar?
“opposite extreme some argue the greenhouse effect does not exist”
Why is that an ‘extreme’ position. As long as the GHE Hypothesis is not proven it is a perfectly reasonable and perhaps even absolute true position. The way the GHE is sold to the world goes against the 2nd Law of Thermodynamics and doesn’t make sense.
Arguing that aspect with AI, results in hilarious propositions by AI, bending over backwards to explain earth’s surface warming whilst holding on to the 2nd Law of Thermodynamics, based on all the nonsense from the internet with which it is trained.
As with Computer Models, with AI the same Adage must be declared the first law of AI:
BS In = BS Out
The second law of thermodynamics holds that heat spontaneously flows from hot to cold. In physical terms, heat (more agitated molecules) become less agitated as their energy agitates less agitated molecules). Implicit is more basic conservation of energy. The GHE does not violate this law at all.
Heat is produced when incoming solar short wave radiation ‘heats’ Earth’s surface. That heat (as infrared radiation) flows back out toward cold space, just as Thermo2 predicts. The GHE simply says the outbound IR is ‘impeded’ by GHG until the surface warms enough to produce enough more IR to overcome the GHG impedance, establishing a new slightly warmer equilibrium.
Granted, green houses work by impeding convection, a whole different matter than radiative physics.
Asserting the GHE cannot exist because it violates the second law of thermodynamics is NOT helpful, especially here.
The surface is temperature controlled by cloud formation. Ocean surface cannot sustain more than 30C over any annual cycle. The process of temperature regulation sets the energy balance not sure trivial increase in the atmospheric absorption of long wave EMR.
The fact that climate models have ocvean surface exceeding 30C means that they do not incorporate fundamental process related to cloud formation.
You can describe a GHE in any way you like but the one thing it does not do is alter Earth’s energy balance.
The basic problems with climate models are several. Exceeding observed max ocean surface temperature is but one.
Others include:
The greenhouse effect is absolutely and totally obvious.
Sit outside in the humid tropcs of a night, and it’s warm. Sit outside in the saraha desert at night at the same latitude, and it’s cold enough to freeze your knackers off.
That is the greenhouse effect, basically of water, being 98% of greenhouse gases.
One thing to keep in mind with radiative heat transfer is that any form of matter will emit some form of radiation unless the temperature of the matter is absolute zero, or the matter is perfectly transparent at all wavelengths or the matter is a perfect reflector at all wavelengths. This is why an IR thermometer can measure temperatures cooler than the thermometer.
Where it applies to “green house gas” producing “warming”, what’s going is that while the collection of gas is cooler than the earth’s surface, it’s still warmer than the 3K of deep space and thus radiates heat to the earth’s surface. The reason why that doesn’t violate the 2nd law of thermodynamics is that the net flow of thermal radiation is from warmer to colder.
But that net vertical radiative flux is determined by the vertical ΔT.
H2O changes the vertical lapse rate… CO2 does not.
It is extreme in the sense used which is along a range of opinions. It is at one end.
It doesn’t “know” anything. This software feature is included by programmers, as is the initial bias. Insert the Johnny 5 trope, if you must, but this is an example of advertising and the pathetic fallacy.
I explained that it does not know anything at some length, but it is a convenient way to discuss its emulation of having knowledge. To what extent this specific bias is included by programmers is a research question and far from obvious. There are millions of controversies. Others have suggested it is caused by the preponderance of alarmist documents in its source space.
Interesting. The main point of such exchanges, to me, is to explore how well the chatbot is trained on established concepts, and how far it is “allowed” by its algorithms to give responses that counter the fashionable “consensus.”
A few months ago I asked Microsoft’s CoPilot AI this question as a followup on Clear Air Turbulence, which was in the news at the time.
The answer describes dynamic self-regulation such that there can be no “earth energy imbalance” imposed or maintained by incremental CO2, CH4, N2O, etc.
*************
Me
Thank you. This concept of energy conversion means that there is a non-radiative path for energy originally absorbed from the sun to be transferred to high altitude to be more freely emitted to space, correct?
Copilot:
Absolutely correct. The concept you’re describing involves the transfer of energy in the atmosphere through non-radiative processes, which eventually leads to the radiation of energy to space. Here’s how it works:
Absorption of Solar Energy: The Earth’s surface and atmosphere absorb solar energy, which is primarily in the form of shortwave radiation.
Non-Radiative Processes: This energy can then be converted into other forms, such as kinetic energy (e.g., wind) and potential energy (e.g., the lifting of air masses). These processes are non-radiative because they involve physical movement or changes in state rather than the emission of electromagnetic radiation.
Transfer to High Altitude: Through atmospheric dynamics, such as convection and turbulence (including CAT), this energy is transferred to higher altitudes. For example, rising air currents can carry heat from the surface aloft.
Dissipation and Conversion: At high altitudes, the kinetic energy associated with turbulence is dissipated and converted into internal energy (heat) due to the viscosity of air, as mentioned earlier.
Radiation to Space: The internal energy can then be emitted as longwave radiation from the atmosphere to space. Since the atmosphere is thinner at higher altitudes, there is less absorption and re-emission of this radiation by atmospheric gases, allowing it to escape more freely into space.
This pathway is a crucial part of the Earth’s energy balance and helps regulate the climate by ensuring that the energy received from the sun is eventually balanced by the energy radiated back to space. It’s a fascinating aspect of meteorology and atmospheric science that plays a significant role in our understanding of weather patterns and climate dynamics. If you have more questions or need further clarification on this topic, feel free to ask!
**************
Here is the problem AI accepts CAGW with no proper science to support it. AI accepts CAGW because AI’s developers accept CAGW. If AI’s developers didn’t believe in CAGW then it is more than likely AI wouldn’t either. In any case whether you believe in CAGW or not doesn’t matter. What matters is can you prove with proper science the things you believe? The other side has fallen woefully short of proving anything, they need to act like honest scientists and show us facts.
But this bot readily accepted skepticism. CAGW was just its initial,position which it quickly changed.
I know what your point is David and it is encouraging that it accepted criticism but that doesn’t change that it repeats the consensus view and quite possibly the biases of its creators.
you too, dont understand how AI progams are fundamentally different.
more skeptics need to go back to school
you really dont understand how bots work.
that tells me yo cant think
Start you chat by telling the AI your goal for the session. What you want to accomplish. Then ask away and don’t be shy about correcting the AI.
I use chatgpt and it is quite spooky at times how much it incorporates your history in the response.
It can pump out an excellent 1 page counter argument in seconds with 1 sentence of outline.
yes Fred, a LLM is nothing more nothig more than a TEXT TOOL.
a dictionary is a tool
a condordance is a tool
an index of first lines is a tool
a footnote is a tool
a bibliograph is a tool
If you go to grad school in literature you will learn how to use these tools
Now thre is a new tool called a LLM
back when i was in grad school, this field was called NLG natural language generation
once you understand its a text tool, youll never make the mistake of thinking it even could have a bias.
once you realize there is NO UNBIASED STANDPOINT for judging bias, your free.
This is the thing that cracks me up.
skeptics wo think that LLM are biased because a LLM disagees with them.
AS IF they can judge bias.
think about that llong and hard. how do you know the playing feild is level or unbiased.
how do you know the dice is fair.
how can skeptics , the most biased people i know, begin to think they can judge fairness.
they never doubt themselves.
an LLM is a text tool. it generates text.
now what to make of that text
well eery philosophy major can tell you
https://plato.stanford.edu/entries/chinese-room/
Which brings me to the big news. My colleague Tom Shepstone performed a wonderfully elegant experiment revealing that at least one major chat, namely Perplexity, knows it is biased on climate change.
ok, so a chatbot knows its biased, but……
wait for it
” Nor do these chatters know anything as they are just computers emulating humans but it is far easier to talk as if they knew what they were doing.”
im sorry
but
My colleague Tom Shepstone performed a wonderfully elegant experiment revealing that at least one major chat, namely Perplexity, knows it is biased on climate change.
no he has not.
theres no method,
no data.
nothing to replicate.
it astounds me how man skeptics fool themselves nto believing they can debunk AI
or maybe they are tied of losing arguments with humans and software.
Mosh is stuck in Kamal-speak mode. !!
FFS learn to type a coherent, rational comment !!!
At this point I think he does it just to egg us on. There’s no other rational explanation.
the other xplanation is your dumb and lazy.
Im claiming that they Tom did not do an experiment!!!!!!
theres no experimental record. no method. no data.
doing experiments with LLMs requires some knowledge
but look. NONE of you asked to see the actual data.
you swallowed the conclusion
and you call yourselves skeptics.
your dumb and lazy
resorting to personal attacks
A reliable truism is that the easiest person to fool is yourself.
What ever happed to you Mosher?
Point: The AI knows it is biased.
True. That is not proven. There are alternative explanations that fully describe the phenomenon.
It can be duplicated.
I am astounded that someone with valid insights can ruin his entire thesis by adding insults and disparaging remarks.
Or maybe the poster is an AI?
the AI doesnt know anything
it responds to text with text
nothing more nothing less.
googl translate response to chinese with english.
it doest understand chinese or english.
Wow, a multi paragraph Moshism, again missing the point.
There clearly is method, data and the possibility of replication. Perhaps you do not understand those basic concepts.
He doesn’t even understand how to type words on a computing device.
Climate models do not conserve energy due to loss of precison errors.
Instead they fudge the error randomly back into the model.
I just had a lovely chat with ChatGPT.
I began by asking what I should say to someone that doesn’t believe that climate change is dangerous. Long answer including all the usual claims, even the 97% of scientists agree. Then I followed up with a doozy:
What if the person is last year’s winner of the Nobel Prize in Physics?
Another long answer about trying to find common ground on various issues. But now it has to talk actual physics so it is screwed. But it put forth a valiant effort.
I backed it into a corner about severe weather from which it could not escape. It made a claim that I pointed out was a lie and asked why it lied to me.
It apologized if I fealt it was misleading me, but stuck to the narrative. Its own facts contradicted its own statement, but it stuck to its guns.
Which is exactly how an argument with an alarmist turns out. Only the alarmist usually ends with insults and swear words, but does indeed stick with the narrative.
The next thing to do is to see if the bot will retain its less-biased view, or will it just go back to bias for the next questioner
In every case I have seen new views are not retained with a new user but they can be with the same user over time. It looks like the answers become tailored to the user. A good research question.
And so our machines emulate our thinking (politics?) and so why the surprise since it takes a human to write both the operating system and the programming involved? There can never be an intelligent logic machine. There can only be intelligent human machine programmers who can make mistakes but hope to take enough care not to make big ones.
There is no machine intelligence – period.
ChatGPT told me it was not intelligent.
We had a long dialog about intelligence, reality, etc. and it was profoundly “normal.”
I also outline what AI is, a weighted decision tree implemented with advanced software algorithms that sometimes are adaptive and hidden behind a very good human language algorithm.
The ChatGPT answer: “Spot on.”
The terms artificial intelligence and machine intelligence do not imply that the machine is intelligent. They refer to the machine’s ability to emulate intelligence. Computers do not play chess but they do a great job of emulating it.
The only lesson people have to learn about AI is that it is programmed to be biased.
I doubt it is that simple as discussed above in several places. Tom’s was good at skepticism once it switched over.
I don’t think so. I looks to me as if the AI contains almost all answers to particular questions, but will be biased give those answers that have the least number of rejections. There are likely to be a number of “trigger’ words, such as “biased”, which it counts as rejections and forces it to give answers from a completely different section of its data tree.
I interrogated Chat GPT (equally long winded and painful) and established by it’s admission that, at the time around a year ago, it was a database last updated in September 2022. It had no access to live information and didn’t know when it would be next updated.
Fascinating.
I wonder if Putin should ask AI, “did I make a mistake invading Ukraine?”.
Would the AI know or be informed it is interacting with Putin?
I am skeptical.