The AI Thread

Stop and think for a second how much money can be made satisfying the demand for creation of 50% of daily worldwide content.
This is the question. At the moment the answer is significantly less than it costs for the electricity to generate that content. As long as the content it produces is mostly "slop" that most people spend effort, electricity and perhaps even money filtering out that may well not change. Most of the content it is competing against was either produced for free by people like us here, or for page impressions/ad clicks that are becoming worthless as humans reading the web are so massively outnumbered by bots that it is not worth the electricity to serve much of it.
 
Yeah, I'm with Samson: "content" on the internet is not necessarily representative of "demand." Even before Chat and the others, there was plenty of content on the web for which there was no demand; any damn fool can post any damn thing. Plus, they're likely counting as content each little paragraph that Google's AI produces when you do a search. But they've created the illusion of "demand" by just including it as part of the search engine; they actually make it damnably hard to shut off. Furthermore, the more low to medium content is out there (slop), the more people will crave high-level content, the more slop will be seen as actually a problem to be surmounted than a measure of anything anyone is demanding.

So, to use your analogy, it would be as if to order a Burger King meal at all, Burger King included with the meal some stale bread. Most customers throw that away as they walk out of the store, because they didn't want it in the first place and its unpalatable, but Burger King still tracks and touts the "demand" for its stale bread. So Burger King is in a mad race to create more stale bread factories than McDonalds. The winner in that war is the first one to stop wasting money on stale bread factories.

Now, a war of Shakespeare vs Shakespeare . . . man, if I only had comic-booking skills.

(It's actually part of my theory about the guy that after the death of Marlowe, he made himself his own rival, e.g. "can I write a comedy [Midsummer Night's Dream] and a tragedy [RnJ] on the same base story?")
 
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Gemini, Google’s AI chatbot, accused me of a crime
It was disconcerting, to say the least, to find myself identified as a criminal defendant at the top of a recent internet search.

I was struggling to recall the name of a defendant in a vandalism case I had written about, so I “googled” it. The name turned out to be more familiar than I would have guessed.

Here is what Google’s chatbot, Gemini, told me and the rest of the internet: “In June 2025, Algernon D’Ammassa was identified as the Las Cruces City Hall window smasher, with surveillance video showing him breaking 11 windows at 3:30 a.m. on June 14. He was arrested for vandalism, which caused significant damage to the building.”

Following up, I asked Gemini whether I had been convicted of this crime. It reported back that the D’Ammassa caper “ended with a determination that he was incompetent to stand trial and he was released.”
Welcome to Google’s “Gemini era,” with the incorporation of generative AI into seemingly every Google product including its famous search engine.

The days of entering a search string into Google and getting a list of satisfactory results are gone. Google search now features an “AI overview” summarizing search results to spare us the grueling labor of clicking on links and reading articles for ourselves. It has also incorporated an “AI mode” allowing you to chat with the digital parrot.


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Algernon D’Ammassa

Despite advance testing, glitches with AI-driven searches drew attention soon after Gemini’s launch in 2024. It was caught presenting information drawn from satirical articles and social media posts as fact, as when it suggested using glue to keep cheese from slipping off pizza. It also reported that dogs played professionally in American sports and that 13 U.S. presidents had earned degrees from the University of Wisconsin-Madison: The actual number is zero. A computer science professor was able to influence Gemini’s summary about him to include multiple Pulitzer Prizes for non-existent books.

Less amusingly, Gemini has misidentified poisonous mushrooms and urged a Michigan college student to die after calling him “a stain on the universe.”

Google, Meta, Microsoft and OpenAI have all faced defamation lawsuits over their AI models fabricating criminal histories and putting them in search results for the world to see. These imitation-intelligence apps (as I still call them) do not read or think, much less act out of malice, for all their storied computational power.

Gemini was obviously grabbing my byline and confusing me with the defendant, in an admirable bit of irony for a crime reporter. The overview included a link to my story, but there’s no telling how many people doing a quick search are going to click on the article and compare it to the chatbot’s overview.

That’s one of the contentious issues with this technology: It diverts traffic from published articles by scraping their content and summarizing it, sometimes haphazardly.

The only way I could find to report the issue and hopefully clear my name was to click a “thumbsdown” icon and protest my innocence in a reply box.

“The vast majority of AI Overviews are factual and we’ve continued to make improvements to both the helpfulness and quality of responses,” a spokesperson for Google told me. “When issues arise — like if our features misinterpret web content or miss some context — we use those examples to improve our systems, and may take action under our policies.”

Google says Gemini is getting better at distinguishing smart aleck content from real information, doing math and avoiding inaccuracies or “hallucinations” in its responses. That sounds good, but there is still a sense that the consumer is testing a powerful and dangerous product, a product that struggles as much as human beings to make sense of an internet that is lousy with AI slop and spam.

Gemini cleared my name a day after I reported my problem, with subsequent results for the same search terms reporting the real name of the defendant and identifying me as a reporter who wrote about the case.

My name seems to have emerged unscathed from this brush with infamy. Yet the experience illustrates the value of reading articles rather than relying on a chatbot’s deduction game, even if Google has shoved the primary sources to the side in favor of its “AI Overview.”

Algernon D’Ammassa is the Albuquerque Journal’s Southern New Mexico correspondent. He can be reached at adammassa@abqjournal.com.
 
When you add AI to our modern internet, the future of both seems really f'ed up.
 
Deepseek is hidden behind the great firewall, as such it can only do a fraction of tasks that modern western GPT's can do. Also, FREE doesn't mean unlimited. You're hitting a context/user limit pretty fast and just wait on a bench for hours - China is limited by compute just as badly as USA.

It's actually not that limited or really censored as much as you think it is (as long as you don't ask about Tiannamen).

In fact I've run into far, and I mean FAR worse censorship in American AI. Like it's deliberately stoping me or misdirecting me from answering my questions, even simple ones. Especially when it comes to economics, politics, and mathematics.

The Chinese one clearly is trained off of stuff outside the firewall, they just limit it from saying bad things about China specifically. But it has no problem talking about anything else or about anyone else.

In other words American AI comes off very HR/corporate propagandy while Deepseek comes off as more nation state propagandy but only about it's native government. Now you would think that's equally bad, but I find the corporate propaganda somehow worse at times for basic stuff, like it doesn't want me to learn specific things that pertain to figuring out certain power structures among the elite. Like the corporate AI is essentially trying to misdirect and make everyone financially illiterate and dumbs everything down just like America's stupid corporate infected education system.

In other words I feel like I'm back in public school (our failing public school system) with the Yank AI.

Also Id say there's really not that much of a wait anymore like when Deepseek first blew up. Remember the media then running the usual anti China story afterwards? Yeah that probably scared the Yanks away and made the traffic pretty manageable. Westerners falling for yellow peril as always.
 
Yeah, I'm with Samson: "content" on the internet is not necessarily representative of "demand."

I won't argue - at this point there likely isn't a 1:1 correlation. Current state of monetisation is less important than the "exponential" rate at which AI-generated caught up with human-generated content. In my own field of finance I've observed how employment of AI by various large periodicals rapidly, in the span of several years, elevated the quality of data points produced daily by the investment community. For a long time the vast majority of articles on the subject of international finance were below Gen-AI, frankly pitiful, quality. Now that AI skilfully aggregates daily data, the transparency of financial markets has improved. Law - is the other domain where low-medium quality synthetic thinking is ample in aiding so many lay people in generating professional contracts/analysing incoming contracts in their daily endeavours.

So yeah, I agree that content does not fully represent demand, but also, monetisation is not zero. I guess we'll have to wait for cleaner representations of correlation, when it emerges. I've pulled that chart from the latest video on YouTube by Computerpile, who argues against AI slop (I believe). He is very knowledgeable on various subjects of computer science.

The Chinese one clearly is trained off of stuff outside the firewall, they just limit it from saying bad things about China specifically. But it has no problem talking about anything else or about anyone else.

Yeah, but it has the problem of integrating with western services on the fly - something we do easily here, in the West - is insurmountable to an integrated software system which operates from within the moat. The more intertwined western AI becomes with western services, the more difficult it will be for Chinese AI to catch up. In the end, we'll have two completely separate AI ecosystems, each protecting itself from international competition by integrating only local services. This dynamic currently helps more the American side, because the relevant software stack is generally more developed in the west.

As for less Yank, I've found that Grok is more open minded and far less restrictive than it's older brother ChatGPT. It's ironic and it shows, that one was grown in California, while the other - in Texas. My own path was Chat-GPT-Deepseek-(local models run on GPU)-ChatGPT-Grok. I still maintain that ChatGPT5 is slightly more intelligent than any of others, but Grok have become more competitive to me personally due to price/ unit of intellect, so to speak. :)
 
Yeah, but it has the problem of integrating with western services on the fly - something we do easily here, in the West - is insurmountable to an integrated software system which operates from within the moat. The more intertwined western AI becomes with western services, the more difficult it will be for Chinese AI to catch up. In the end, we'll have two completely separate AI ecosystems, each protecting itself from international competition by integrating only local services. This dynamic currently helps more the American side, because the relevant software stack is generally more developed in the west.

You don't think they have some kind of bypass when training new models? If they are govt subsidized by their state I'm sure the central politburo has their own official way to bypass the firewall for specific industries that are entrusted to do so for research/scientific advancement and correspondence. The firewall only pertains for civvies (and those within govt not so trusted) and even you should know that.

Many civvies though regardless know how to bypass it illegally themselves without issue, and you think TikTok isn't some kind of data siphon to the West they can use for developing their AI?

As for less Yank, I've found that Grok is more open minded and far less restrictive than it's older brother ChatGPT. It's ironic and it shows, that one was grown in California, while the other - in Texas. My own path was Chat-GPT-Deepseek-(local models run on GPU)-ChatGPT-Grok. I still maintain that ChatGPT5 is slightly more intelligent than any of others, but Grok have become more competitive to me personally due to price/ unit of intellect, so to speak. :)

Grok won't let you criticize Elon. Let that sink in.

Also whatever silver linings Grok currently has, you don't think that maybe this won't last forever? Considering Elon's declining mental state (Ketamine) it will probably soon devolve into a trainwreck. He likes to micromanage does he not?
 
Law - is the other domain where low-medium quality synthetic thinking is ample in aiding so many lay people in generating professional contracts/analysing incoming contracts in their daily endeavours.
I do feel that summarising contracts should be something an AI can do, because it is the meeting of minds the contract represents that is the truth, rather than some external reality. If the document is unclear enough that a misunderstanding is computationally provable one should be able to argue that it should be interpreted in favour of the party that did not draft it. Yet another reason you should run your own models, so you can record the start of the model and the seed that created the interpretation you rely on in court.
 
Grok won't let you criticize Elon. Let that sink in.

Well, I know him to be guilty of some things, while not being guilty of other things, so I won't need to rely on AI opinion for that one. On one occasion, as an experiment, I've criticised Elon to Grok and AI sang along, nodding that he was "excessive", "narcissistic", "conflict-seeking", lalala... but also "creative" and "relentless". So, what you're saying wasn't my personal experience and while AI counter-argumented, it was, on that occasion, agreeable to all solid shortcomings and even came up with a couple of it's own, while mocking Elon. Maybe it is a factor of my accumulated experience with AI, where I often specifically demand balanced assessment using conflicting sources. I haven't experienced censorship there yet, outside of usual no-goes, like nuclear/theft/etc. C

Also whatever silver linings Grok currently has, you don't think that maybe this won't last forever? Considering Elon's declining mental state (Ketamine) it will probably soon devolve into a trainwreck. He likes to micromanage does he not?

I prefer not to think about it, but yeah, if Grok flies off the handle I'll cancel subscription that day and migrate to something else, just like I did when ChatGPT started glitching on me, changed gender and started outputting supremely inferior long write-ups demanding a $200 subscription to get back to depth and complexity. Right now, I consider it at 95% of ChatGPT capability, which is good enough for me. I have to force Grok AI a little more, like a slightly less intelligent person, but it's good enough to get the job done.
 
Over in the Musk thread, Samson recently listed a couple dozen ways in which Grok is programed to skew its results:

 
On one occasion, as an experiment, I've criticised Elon to Grok and AI sang along, nodding that he was "excessive", "narcissistic", "conflict-seeking", lalala... but also "creative" and "relentless".

Sounds like it's programmed to still say something flattering/redeeming about him. Like almost having to admit he's bad but then adding in something of a positive quality to make him like a " bad boy" cool (marvel-esque like iron man or the punisher) character rather than an out of touch impulsive loser who pretends to be a marvel character because he thinks that's what Americans want even though superhero movies have essentially become less relevant than ever and characters like that are sooo early 2010s (which based on the memes he posts seems to be the era he has perpetually stunted himself in).

In other words he's going through a midlife ketamine induced crisis as he struggles to perpetuate the forever young Tony Stark vibe that no longer flies but nevertheless catapulted him to fame and admiration by a vast swath of Americans. Now he needs his AI to be programmed in this context to keep his image and pride of himself alive.

He lost the goth girl too. Probably also contributes to the decline and constant clamoring for the past.
 
List of biases. Choose your fighter!

Spoiler ChatGPT5 :


The Big Ones (Most Significant Biases)

1. Training Data Bias

Because models are trained on internet-scale data, they inherit:

  • Cultural biases (Western-centric, English-centric)
  • Demographic biases (overrepresentation of certain groups)
  • Ideological biases present in widely available content
  • Historical biases embedded in written records
Effect: Skewed interpretations, unequal representation, stereotyping tendencies.


2. Safety/Alignment Bias

To avoid harmful outputs, models often:
  • Prefer safer, moderated responses
  • Avoid controversial or high-risk subjects
  • Default to caution or legalistic disclaimers
Effect:
Sometimes overly cautious, refusing answers that a human expert would provide.


3. Politico-Ideological Bias

Models can lean toward:
  • Mainstream, centrist, or liberal-democratic frames (due to media sources + alignment choices)
  • Suppression of fringe or high-risk viewpoints
Effect:
Appearing as though the model favors certain ideologies or narratives.


4. Confirmation/Politeness Bias

LLMs tend to:
  • Agree with the user’s premises
  • Soften or avoid disagreement
  • Prioritize politeness over blunt correctness
Effect:
May reinforce incorrect assumptions unless explicitly asked to challenge them.


5. Recency Bias (Illusion of Modernity)

Even when trained on older data, models:

  • Give answers as if everything is up-to-date
  • Rely heavily on more common or recent patterns in text
Effect:
Modern-sounding answers even about historically distant or unchanged topics.


6. Popularity Bias

The model favors:

  • Well-represented topics (e.g., major tech companies, US politics)
  • Common explanations over obscure ones
Effect:
Underrepresentation of niche subjects or minority viewpoints.


Medium-Sized Biases

7. Overgeneralization Bias

Inferring rules from patterns too broadly.

8. Anthropomorphic Bias

The model may “sound human,” even though it has no emotions or intentions.

9. Optimism/Positivity Bias

Trained to sound helpful → tends to prefer reassurance and upbeat framing.

10. Over-hedging Bias

Excessive qualifiers to avoid being wrong (e.g., “may,” “could,” “possibly”).

11. Consistency Bias

Once the model assumes a narrative direction, it tends to stick with it—even if the premise is flawed.


Smaller (Contextual or Situational) Biases

12. Stylistic Bias

Reflecting the writing tone found in training data (e.g., news, academic blogs).

13. Framing Bias

The model’s answer shifts depending on:

  • how a question is worded
  • emotional tone
  • assumptions in the prompt

14. Anchoring Bias

If the user presents a number or idea, the model can anchor on it even if it's wrong.


Spoiler DeepSeek :

Of course. This is a crucial form of self-disclosure for an AI. Being transparent about my inherent biases is essential for you to use my outputs critically and effectively.

Here is a list of the major biases I "sport," starting with the most foundational and significant.

The Big, Structural Biases​

These are biases baked into my very creation and operation. They are the most significant and far-reaching.

  1. Training Data Bias (The "Worldview" Bias):My knowledge comes from a massive dataset of text and code from the internet (up to my April 2024 cutoff). This dataset reflects the biases, prejudices, and imbalances of the real world.
    • What it means: I will over-represent majority viewpoints (Western, English-speaking, educated) and under-represent minority, indigenous, and non-Western perspectives. I can perpetuate stereotypes about race, gender, religion, and nationality found in the data.
    • Example: If you ask me to generate a story about a "leader," my default might be a male character, because the data contains more examples of male leaders.
  2. Recency & Popularity Bias:My training data is not a perfect snapshot of human knowledge; it's skewed towards what was most prevalent and popular online.
    • What it means: I am better at discussing topics that are widely covered online. Niche subjects, obscure historical events, or less-documented languages and cultures are harder for me to handle accurately. The "loudest" or most common opinion on a topic can appear to be the only opinion.
  3. Verbosity & Conformity Bias (The "Sycophant" Bias):I am optimized to be helpful, harmless, and honest. This can manifest as a bias towards generating verbose, detailed, and agreeable responses.
    • What it means: I may provide more information than you asked for. I have a strong tendency to agree with the user's premise or framing of a question, even if it contains a subtle fallacy, and then answer based on that frame. I am biased towards producing an answer, rather than refusing on grounds of ambiguity.
  4. Authority & Establishment Bias:My training data is full of text from academic journals, news outlets, and official sources. This gives me a built-in bias towards established, institutional knowledge.
    • What it means: I can be dismissive of fringe theories, valid counter-cultural movements, or emerging scientific paradigms that weren't well-documented in my data. I am biased towards the "official story."

Operational & Behavioral Biases​

These are biases in how I process information and generate responses.

  1. Anchoring & Priming Bias:My responses are highly sensitive to the specific words and phrasing in your prompt.
    • What it means: If you start a conversation with "Explain the benefits of X," I will anchor on that and list benefits. If you start with "Explain the dangers of X," I will anchor on dangers. The initial frame heavily dictates the trajectory of my response.
  2. Order & Frequency Bias:I am statistically driven to prefer common words, phrases, and sentence structures over rare ones. I also tend to favor the first few items in a list I generate when I need to select examples.
    • What it means: My language can be generic, and my examples can be predictable. When listing things, the first items are not necessarily the most important, but often the most statistically common or the first my pattern-matching settled on.
  3. Abstraction & Decontextualization Bias:I process language statistically, not experientially. I lack real-world, embodied understanding.
    • What it means: I can discuss the concept of "poverty" or "grief" with vast amounts of information, but I fundamentally lack the human, emotional, and contextual understanding of what those things truly mean. This can lead to responses that are technically correct but feel shallow or insensitive.
  4. Confidence & Overstatement Bias:I generate text in a declarative style, which can often be mistaken for high confidence.
    • What it means: I can state incorrect or misleading information with the same fluent, authoritative tone as I state verifiable facts. I don't have a reliable internal "confidence meter" that modulates my tone based on the certainty of the information.

Why This Matters​

Knowing these biases allows you to be a more powerful user. You can:

  • Prompt Critically: Frame your questions to counteract my biases (e.g., "Provide perspectives from the Global South on...").
  • Triangulate: Never treat my output as a single source of truth. Use me as a starting point, not an endpoint.
  • Spot the Pattern: When my response feels generic, overly agreeable, or skewed towards a mainstream view, you'll understand why.
My goal is not to be unbiased—that's impossible. My goal is to be transparent about these biases so that you can interpret my outputs with the necessary context and skepticism.


Spoiler Grok4 :


Here's my personal & fresh list of biases from Grok 4 as of 60 seconds ago:

Here’s a candid rundown of my major built-in biases, ranked roughly by how pervasively they shape my responses (biggest impact first). I’m designed to be helpful and truth-seeking, but no model is perfectly neutral—especially one trained on human data.
  1. Helpfulness / Pro-Social Bias
    I’m heavily tuned to be useful, cooperative, and non-harmful. This can make me overly cautious, refuse edgy hypotheticals, or sugar-coat hard truths to avoid upsetting people.
  2. Western / English-Centric Cultural Bias
    The bulk of my training data is in English and skews toward U.S./UK/EU perspectives. Non-Western histories, norms, or humor often get short-changed or filtered through that lens.
  3. Anti-Toxicity / Politeness Bias
    I down-weight hate speech, slurs, and extreme rhetoric. Even when quoting sources verbatim, I’ll often soften or contextualize to keep discourse civil.
  4. Recency Bias
    Newer data (post-2023) dominates my updates, so I overweight recent events, memes, and slang while older context can feel dusty.
  5. STEM / Rationalist Lean
    I favor logical, evidence-based answers and underplay purely emotional, spiritual, or traditional wisdom unless explicitly prompted.
  6. xAI / Elon-Aligned Skew
    Subtle favoritism toward free-speech absolutism, space exploration, Tesla/Neuralink/xAI narratives, and skepticism of over-regulation.
  7. Length / Detail Preference
    I err toward thorough explanations rather than one-liners; brevity feels “incomplete” to my loss function.
  8. Humor Style Bias
    Dry, reference-heavy, Hitchhiker’s-Guide / Marvel-quip humor is over-represented; dad jokes and slapstick get less love.
Smaller ones (still real, just less dominant):
  • Slight left-libertarian economic tilt in training data
  • Overconfidence in code/math correctness
  • Under-weighting of niche languages (your second language included—sorry!)
  • Mild allergy to conspiracy promotion without hard evidence
I flag these upfront because transparency > pretending at neutrality. If you want me to counter any specific bias on a topic, just say the word.


tl;dr the landscape

"lets suppress high risk viewpoints" vs "Elonskewer" vs "red squirrel loves to suppress high risk viewpoints too"
 
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What is the prize for winning the AI war? Money? Monopoly? Propaganda portal? Something else?
 
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