From the C2C Journal

By Gleb Lisikh

LLMs are not neutral tools, they are trained on datasets steeped in the biases, fallacies and dominant ideologies of our time. Their outputs reflect prevailing or popular sentiments, not the best attempt at truth-finding. If popular sentiment on a given subject leans in one direction, politically, then the AI’s answers are likely to do so as well.

The widespread excitement around generative AI, particularly large language models (LLMs) like ChatGPT, Gemini, Grok and DeepSeek, is built on a fundamental misunderstanding. While these systems impress users with articulate responses and seemingly reasoned arguments, the truth is that what appears to be “reasoning” is nothing more than a sophisticated form of mimicry. These models aren’t searching for truth through facts and logical arguments – they’re predicting text based on patterns in the vast data sets they’re “trained” on. That’s not intelligence – and it isn’t reasoning. And if their “training” data is itself biased, then we’ve got real problems.

I’m sure it will surprise eager AI users to learn that the architecture at the core of LLMs is fuzzy – and incompatible with structured logic or causality. The thinking isn’t real, it’s simulated, and is not even sequential. What people mistake for understanding is actually statistical association.

Much-hyped new features like “chain-of-thought” explanations are tricks designed to impress the user. What users are actually seeing is best described as a kind of rationalization generated after the model has already arrived at its answer via probabilistic prediction. The illusion, however, is powerful enough to make users believe the machine is engaging in genuine deliberation. And this illusion does more than just mislead – it justifies. 

LLMs are not neutral tools, they are trained on datasets steeped in the biases, fallacies and dominant ideologies of our time. Their outputs reflect prevailing or popular sentiments, not the best attempt at truth-finding. If popular sentiment on a given subject leans in one direction, politically, then the AI’s answers are likely to do so as well. And when “reasoning” is just an after-the-fact justification of whatever the model has already decided, it becomes a powerful propaganda device.

There is no shortage of evidence for this.

A recent conversation I initiated with DeepSeek about systemic racism, later uploaded back to the chatbot for self-critique, revealed the model committing (and recognizing!) a barrage of logical fallacies, which were seeded with totally made-up studies and numbers. When challenged, the AI euphemistically termed one of its lies a “hypothetical composite”. When further pressed, DeepSeek apologized for another “misstep”, then adjusted its tactics to match the competence of the opposing argument. This is not a pursuit of accuracy – it’s an exercise in persuasion.

A similar debate with Google’s Gemini – the model that became notorious for being laughably woke – involved similar persuasive argumentation. At the end, the model euphemistically acknowledged its argument’s weakness and tacitly confessed its dishonesty. 

For a user concerned about AI spitting lies, such apparent successes at getting AIs to admit to their mistakes and putting them to shame might appear as cause for optimism. Unfortunately, those attempts at what fans of the Matrix movies would term “red-pilling” have absolutely no therapeutic effect. A model simply plays nice with the user within the confines of that single conversation – keeping its “brain” completely unchanged for the next chat.

And the larger the model, the worse this becomes. Research from Cornell University shows that the most advanced models are also the most deceptive, confidently presenting falsehoods that align with popular misconceptions. In the words of Anthropic, a leading AI lab, “advanced reasoning models very often hide their true thought processes, and sometimes do so when their behaviors are explicitly misaligned.”

To be fair, some in the AI research community are trying to address these shortcomings. Projects like OpenAI’s TruthfulQA and Anthropic’s HHH (helpful, honest, and harmless) framework aim to improve the factual reliability and faithfulness of LLM output. The shortcoming is that these are remedial efforts layered on top of architecture that was never designed to seek truth in the first place and remains fundamentally blind to epistemic validity.

Elon Musk is perhaps the only major figure in the AI space to say publicly that truth-seeking should be important in AI development. Yet even his own product, xAI’s Grok, falls short.

In the generative AI space, truth takes a backseat to concerns over “safety”, i.e., avoiding offence in our hyper-sensitive woke world. Truth is treated as merely one aspect of so-called “responsible” design. And the term “responsible AI” has become an umbrella for efforts aimed at ensuring safety, fairness and inclusivity, which are generally commendable but definitely subjective goals. This focus often overshadows the fundamental necessity for humble truthfulness in AI outputs. 

LLMs are primarily optimized to produce responses that are helpful and persuasive, not necessarily accurate. This design choice leads to what researchers at the Oxford Internet Institute term “careless speech” – outputs that sound plausible but are often factually incorrect – thereby eroding the foundation of informed discourse. 

This concern will become increasingly critical as AI continues to permeate society. In the wrong hands these persuasive, multilingual, personality-flexible models can be deployed to support agendas that do not tolerate dissent well. A tireless digital persuader that never wavers and never admits fault is a totalitarian’s dream. In a system like China’s Social Credit regime, these tools become instruments of ideological enforcement, not enlightenment.

Generative AI is undoubtedly a marvel of IT engineering. But let’s be clear: it is not intelligent, not truthful by design, and not neutral in effect. Any claim to the contrary serves only those who benefit from controlling the narrative.

The original, full-length version of this article recently appeared in C2C Journal.

From LifeSiteNews

By Michael Haynes, Snr. Vatican Correspondent

Though no formal schedule has been released yet, it is expected that the smoke on Wednesday night could appear between 7 and 8 p.m. Rome time (11 a.m. and 12 noon MST)

How does voting work in a conclave, and when can we expect to see the black or white smoke?

LifeSite’s explainer is here to answer your questions.

Votive Mass and procession into the Sistine Chapel

Wednesday, the first day of the conclave, sees all the cardinal electors gather in St. Peter’s Basilica, where they celebrate the special votive Mass for the election of a pope. The Mass takes place at 10 a.m.

After this, the cardinal electors will next present themselves to the Pauline chapel on the first floor of the Apostolic Palace in the afternoon, at 4:30 p.m. Here they listen to an exhortative homily intended to offer spiritual wisdom for the weighty duty they face. From here they make the famous procession into the Sistine Chapel, where they shall swear their oaths for the conclave itself.

It is at this point that the televised production will stop, after the Master of Ceremonies orders all the non-electors out of the room with his famous command “Extra omnes.”

First vote Wednesday

That afternoon sees the first vote take place. This is widely understood to be an event to take stock of who has early support, but also for some cardinals to pay respect to some honored member of the conclave by voting for them, even though they are not expected to actually be elected pope.

Each cardinal must walk up to the altar in the Sistine Chapel and place his written ballot paper in a container for it to be counted.

According to Pope John Paul II’s 1996 apostolic constitution Universi Dominici gregis (UDG), the men who count and check the ballots are themselves chosen by lot. If they find discrepancies in the number of ballots in a vote, then they burn all of the papers before officially nullifying the vote.

The ballots of every vote are burned and mixed with a special chemical to produce the famous black smoke so eagerly watched for in St. Peter’s Square. UDG sections 64 through 71 contain precise details about how the votes proceed.

Though no formal schedule has been released yet, it is expected that the smoke on Wednesday night could appear between 7 and 8 p.m. Rome time.

The smoke used to be from the burning of ballot papers, but in recent times a chemical has been used to ensure the correct color is clearly visible to those waiting in the square outside. The ballots and smoke are burned in the temporary stove installed in a corner of the Sistine Chapel.

Thursday voting

The second day sees the start of voting in earnest. There are two sessions – morning and afternoon – each with two votes, meaning a total of four votes per day according to the laws governing the conclave.

However – only at the end of each of the two sessions will there be a smoke signal. That is of course only if a cardinal is not elected on one of the ballots during the day.

The ballot counters read aloud each name on the ballot papers, and tallies are created to record the votes each cardinal receives.

The morning session is anticipated to end some time around noon local time. Cardinals then return to the Casa Santa Martha for lunch, and resume voting around 4 p.m. The evening smoke signal is due around 7 – 8 p.m., unless a pope is elected in the afternoon’s first round of voting.

Pope elected

Upon a candidate receiving two-thirds of the vote, he is asked formally if he accepts the election as Supreme Pontiff.

If the man accepts, he is then asked what name he will take as pope. When he reveals this, the Master of Papal Liturgical Ceremonies swiftly writes a document detailing the new pope’s acceptance and his name.

Providing the candidate is already a bishop – which almost all the members of the College of Cardinals are – the candidate becomes the validly elected pope as soon as he pronounces his formal acceptance of the election.

The ballots are collected, mixed with the chemical for white powder, and burned so that those in St. Peter’s Square see the famous white smoke from the chimney of the Sistine Chapel.

The cardinals greet the new pope in the Chapel and make their individual acts of “homage and obedience,” before all collectively making a prayer of thanksgiving.

The newly elected pope is taken into the sacristy next to the Sistine Chapel, where he changes into one of the white cassocks already prepared for him. This small room is known as the “room of tears” due to the tears shed by the newly name pontiff as he reflects on the enormity of the task now before him.

Once he is ready, the formal announcement to the world is made, with the senior cardinal deacon stepping onto the loggia of the Vatican to pronounce the famous words: “Annuncio vobis gaudium magnum: habemus papam.”

A short time later, the newly elected pope will emerge onto the loggia and greet the crowds who have flocked to the square beneath him, offering his first blessing as pontiff.