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How AI is upending the fashion industry... and how students are adapting 89%

6/3/2026, 5:03:13 PM

Topics: Video
Keywords: Youtube

BS Summary: This video contains 27 faulty reasoning types, including Negativity Bias, Status Quo Bias, and Post Hoc (False Cause), with Anecdotal as the most egregious example at 34.9% saturation with 116 hits. Analysis detected 1,314 faulty-reasoning hits from 332 analyzed words, generating a BS Score of 82.4% and a BS Rank of 89% (2,401 of 21,887 videos). This video is worse (more manipulative) than 89.00% of the video peer group.

From runway to rack, every piece tells a 
story we often don't see. Fashion is a 
$500 billion industry today, but FIT 
President Jason Shoe Box says despite the revenue, the industry is facing challenges. 
>> Some of those jobs in New York City are going down. Fashion, we've lost about 23% of the fashion designers in the city in the last 10 years. That's that's an alarm bell. 
>> Uncertainty over AI is fueling the decline, and Shoe Box's goal is to teach the next generation to harness their creativity while working alongside the technology. 
>> AI 
AI massively disruptive, right? We are incorporating it across our classrooms. 
We're doing all kinds of different partnerships with major industry corporations helping them experiment with their AI. 
>> Fashion companies are using AI for trend forecasting, inventory planning, and digital design. While in stores and fitting rooms, it's assisting customers. 
Tia Cost is an FIT junior studying the business side of fashion. 
>> We need to learn how to adapt to AI and learn how to use it to better our jobs and our positions in the industry because it is here to stay. 
>> AI is also finding ways to improve sustainability. 
We saw how FIT is now experimenting with gardens, creating natural dyes from plants to color fabrics. 
>> Extract colors from something like a Hopi black dye sunflower. We take the seeds out of that and it turns purple. 
>> Regardless, Shoe Box says some things just never go out of style. 
>> People will always wear clothes. You still need someone to make those clothes. You still need someone to design those clothes. 
A robot does not have an imagination that will design the next hot thing that someone wants to wear. 
>> By stitching, tech, and human touch together, he hopes to bring jobs back to the global fashion hub. Evan Moon, CBS News, New York. 
Confirmation Bias
3.3%
Anchoring Bias
1.8%
Availability Heuristic
17.8%
Representativeness Heuristic
16%
Hindsight Bias
0%
Overconfidence Bias
13.6%
Framing Effect
4.2%
Loss Aversion
0%
Status Quo Bias
27.1%
Sunk Cost Effect
0%
Optimism Bias
25%
Pessimism Bias
3.9%
Negativity Bias
32.5%
Self-Serving Bias
0%
Fundamental Attribution Error
13.9%
Actor-Observer Bias
3.9%
In-Group Bias
0%
Out-Group Homogeneity Bias
0%
Halo Effect
21.4%
Horn Effect
0%
Dunning-Kruger Effect
0%
Recency Bias
0%
Primacy Effect
3.6%
Blind-Spot Bias
0%
Ad Hominem
0%
Straw Man
0%
Appeal to Authority
14.5%
False Dilemma
25.6%
Slippery Slope
0%
Circular Reasoning
0%
Hasty Generalization
23.8%
Red Herring
0%
Bandwagon
0%
Appeal to Emotion
21.1%
Begging the Question
11.4%
Post Hoc (False Cause)
25.9%
Tu Quoque
0%
Burden of Proof
13.6%
Appeal to Nature
12.3%
Composition/Division
2.4%
Anecdotal
34.9%
No True Scotsman
3.9%
Ambiguity (Equivocation)
15.7%
Gambler’s Fallacy
0%
Middle Ground
0%
Personal Incredulity
0%
Special Pleading
0%
Genetic Fallacy
2.7%
Unattributed Quote
0%
Quote-first Misdirection
0%
Biased Writer Voice
0%
Indoctrination
0%
Politically Left Leaning Bias
0%
Politically Right Leaning Bias
0%
Attempt to Sell a Product or Service
0%

332 words analyzed.

Analysis

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