ABC News99%

How tech execs are reacting to Pope Leo's warning about AI 14%

5/26/2026, 7:11:34 AM

Topics: Video
Keywords: Youtube

BS Summary: This video contains 33 faulty reasoning types, including Negativity Bias, Burden of Proof, and Hasty Generalization, with Appeal to Emotion as the most egregious example at 32.6% saturation with 296 hits. Analysis detected 2,211 faulty-reasoning hits from 909 analyzed words, generating a BS Score of 30.7% and a BS Rank of 14% (18,821 of 21,887 videos). This video is better (less manipulative) than 86.00% of the video peer group.

B News contributor, Google tech policy fellow Mike Muse is here for more. 
Hi Mike. 
So Anthropics co-founder was actually in the audience for the the Pope's comments. 
He also echoed the Pope's sentiments here. 
How are other AI companies and experts reacting to this? 
>> What Ola said was the co-founder of Anthropic is really in relationship to what Pope Leo mentioned. 
Pope Leo really leaned into the dignity of the worker and really talking about fair wage and making sure that humans are treated properly. 
Uh he talked about the young person who is collecting the data and doing content moderation. 
But he also too talked about the young person who is mining the essential minerals that are needed to power the compute. 
Just in contrast also the co-founder Anthropic Ola he discussed the idea of how to address the global poor and he said that entities and institutions such as the Vatican are important to their work. 
It's important to hold them accountable outside of the incentives that are not just about economic based and growthbased. 
So there is a welcoming of Silicon Valley of outsiders who will hold them accountable and keep them morally sound. 
The Pope says it's not enough to ask whether AI is used for good, but also about how it's designed. 
Can tech companies design AI systems to either be good or bad? 
>> That is what Ola said in his response is that often times what they're designing is in contrast to oftentimes what the core aspect of is for humanity and for the good of humanity. when they are in the race that we see right now with the major tech companies to be first in with the products. 
You have open AI, you have Anthropic, you have Google Gemini. 
What they're see what he was suggesting is that the incentives to win the race may go outside the boundaries of what is best for humanity. 
And so what he's saying is that oftentimes they're designing systems and specifically when they look inside the mysteriousness of the systems to what exactly what Ola said oftentimes shocks them and then that's what is important for entities like religious scholars people in the humanities to push back on them to make sure they stay within the boundaries and that they are not blinded by the incentives to win by incentives for economic gains and by the incentives to get their products out first. 
Poplio is calling for stronger regulation. 
He's warning that the power around all of this is concentrated in too few a few number of people, a few powerful companies and their leaders. 
How do you make a more democratic or inclusive setup for all of this? 
>> I like that Pope Leo is taking the lead and I often talk about that we need humanities. 
We often are so focused on getting individuals to major in STEMbased careers in order to advance the future. 
But with that, we need those who are in humanities. 
We need religious scholars. 
We need human rights activists to be no not only at the table to encourage conversations, but we actually need them at the design table. 
And I think the more that leaders like Pope Leo take this position, it can encourage and open up seats at the design tables inside these companies in order to create the products. 
So then when we do get into this idea of the mysteries inside the data sets that individuals at the design level in order to push back on questions and say, "Hold up, this could cause harm to humanity. 
We might want to think about how do we redesign it? 
we might want to pull from a different data set or we might want to ask the machine to ask a different question in order to get a different output. 
But you can't have those type of questions if you don't have people at the design phase. 
And so individuals like the pope and entities like the Vatican are important to bring a seat at the table for that. 
>> How much support is there for changes like that? 
>> There's an openness uh to it, right? 
But I think it takes this conversation to have like we're having right now to get people to go outside their biases, right? 
Like you don't know what you don't know, right? 
And so as researchers and data scientists, if their whole idea is collect the data sets, get the right data to get the right outcome that we need to meet the bottom line of this quarter or to compete with our competitor who just released a similar product. 
So we got to get out there first. 
They're tunnel vision. 
And so there is implicit biases that researchers and data scientists have which is why it's important that people from the outside disrupt those biases and come to the table in order to create collaboration. 
But it's important to note that the AI train has left the station and so there is no going back, there is no stopping, there is no pausing, but it's a matter of how do we get on the train while it's moving and then how do we make it better ride for everyone who is on the train. 
>> All right, Mike Muse, thank you. 
Thank you. 
Article reasoning-pattern comparisonThis article: 7.3%ABC News: 2.2%Confirmation Bias7.3%This article: 1.3%ABC News: 0.7%Anchoring Bias1.3%This article: 12.4%ABC News: 3.0%Availability Heuristic12.4%This article: 5.3%ABC News: 0.9%Representativeness Heuristic5.3%This article: 0.0%ABC News: 0.5%Hindsight Bias0.0%This article: 4.3%ABC News: 1.1%Overconfidence Bias4.3%This article: 3.0%ABC News: 6.8%Framing Effect3.0%This article: 0.0%ABC News: 0.3%Loss Aversion0.0%This article: 1.1%ABC News: 0.4%Status Quo Bias1.1%This article: 0.0%ABC News: 0.1%Sunk Cost Effect0.0%This article: 11.1%ABC News: 2.4%Optimism Bias11.1%This article: 7.7%ABC News: 1.0%Pessimism Bias7.7%This article: 18.9%ABC News: 7.7%Negativity Bias18.9%This article: 2.1%ABC News: 1.5%Self-Serving Bias2.1%This article: 5.6%ABC News: 0.7%Fundamental Attribution Error5.6%This article: 9.4%ABC News: 0.1%Actor-Observer Bias9.4%This article: 3.9%ABC News: 0.8%In-Group Bias3.9%This article: 13.2%ABC News: 0.4%Out-Group Homogeneity Bias13.2%This article: 10.0%ABC News: 2.2%Halo Effect10.0%This article: 0.0%ABC News: 0.1%Horn Effect0.0%This article: 0.0%ABC News: 0.0%Dunning-Kruger Effect0.0%This article: 0.0%ABC News: 1.3%Recency Bias0.0%This article: 1.4%ABC News: 0.4%Primacy Effect1.4%This article: 0.0%ABC News: 0.1%Blind-Spot Bias0.0%This article: 0.0%ABC News: 0.5%Ad Hominem0.0%This article: 1.8%ABC News: 0.1%Straw Man1.8%This article: 5.3%ABC News: 3.3%Appeal to Authority5.3%This article: 11.0%ABC News: 0.9%False Dilemma11.0%This article: 6.5%ABC News: 0.3%Slippery Slope6.5%This article: 2.5%ABC News: 0.1%Circular Reasoning2.5%This article: 15.2%ABC News: 2.8%Hasty Generalization15.2%This article: 0.0%ABC News: 0.4%Red Herring0.0%This article: 0.0%ABC News: 0.4%Bandwagon0.0%This article: 32.6%ABC News: 4.3%Appeal to Emotion32.6%This article: 2.4%ABC News: 0.7%Begging the Question2.4%This article: 7.8%ABC News: 2.1%Post Hoc (False Cause)7.8%This article: 0.0%ABC News: 0.0%Tu Quoque0.0%This article: 16.9%ABC News: 0.4%Burden of Proof16.9%This article: 0.0%ABC News: 0.1%Appeal to Nature0.0%This article: 1.1%ABC News: 0.2%Composition/Division1.1%This article: 3.1%ABC News: 1.2%Anecdotal3.1%This article: 9.4%ABC News: 0.1%No True Scotsman9.4%This article: 4.3%ABC News: 1.8%Ambiguity (Equivocation)4.3%This article: 0.0%ABC News: 0.0%Gambler’s Fallacy0.0%This article: 1.2%ABC News: 0.0%Middle Ground1.2%This article: 0.0%ABC News: 0.0%Personal Incredulity0.0%This article: 0.0%ABC News: 0.2%Special Pleading0.0%This article: 0.0%ABC News: 0.1%Genetic Fallacy0.0%This article: 4.3%ABC News: 1.9%Unattributed Quote4.3%This article: 0.0%ABC News: 1.0%Quote-first Misdirection0.0%This article: 0.0%ABC News: 3.1%Biased Writer Voice0.0%This article: 0.0%ABC News: 0.6%Indoctrination0.0%This article: 0.0%ABC News: 0.7%Politically Left Leaning Bias0.0%This article: 0.0%ABC News: 0.2%Politically Right Leaning Bias0.0%This article: 0.0%ABC News: 1.0%Attempt to Sell a Product or S…0.0%

909 words analyzed.

Speakers

3speakers8.1%attributed speech835writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 11 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 2 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageOla • 7 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 18 words • 0.0% coverageWriter's voice • 24 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageWriter's voice • 35 words • 0.0% coveragePope • 19 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageOla • 20 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 58 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageOla • 26 words • 0.0% coverageWriter's voice • 85 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageWriter's voice • 26 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 19 words • 0.0% coverageWriter's voice • 19 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 4 words • 0.0% coverageWriter's voice • 25 words • 0.0% coverageWriter's voice • 33 words • 0.0% coverageWriter's voice • 39 words • 100.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 30 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 8 words • 0.0% coverageWriter's voice • 23 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageWriter's voice • 48 words • 0.0% coverageWriter's voice • 8 words • 0.0% coverageWriter's voice • 3 words • 0.0% coverageWriter's voice • 35 words • 0.0% coverageWriter's voice • 59 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageMike Muse • 2 words • 0.0% coverage
Selected voice

Ola

100%flagged-word coverage
53 attributed words72% of attributed speech89% writer coverage
0%2.5%5.0%Unattributed Quote-4.7 ptsWriter: 4.7%Ola: 0.0%0.0%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

Loading…
Loading…
Loading…
Loading…
Loading…
Loading…

Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.