CBC50%

What the cluck was that? Scientists turn to AI to decode what chickens are saying 27%

By Vanessa Caldwell0%

1/29/2026, 3:01:01 PM

BS Summary: This article contains 21 faulty reasoning types, including Optimism Bias, Appeal to Authority, and Hasty Generalization, with Ambiguity (Equivocation) as the most egregious example at 29.6% saturation with 68 hits. Analysis detected 482 faulty-reasoning hits from 230 analyzed words, generating a BS Score of 38.3% and a BS Rank of 27% (12,344 of 16,813 articles). This article is better (less manipulative) than 73.40% of the article peer group.

In Nova Scotia, livestock scientist Suresh Neethirajan is using technology to decode chickens’ complex mode of communication. 
Neethirajan and his students at Dalhousie University record every squawk, cluck and chirp made by a flock of chickens, while cameras simultaneously capture the birds’ movements. 
The researchers also use thermal imaging to track the animals’ body temperature, which can indicate stress. 
In this clip from Cluck! 
Chickens Exposed, a documentary from The Nature of Things, Neethirajan explains how he and his team used AI to sift through four months of recordings. 
Together, the information can show the context of the sounds being made and give meaning to what the chickens are communicating. 
“So we can listen to the variety of calls made [in] different contexts and understand the buried emotions behind these calls,” he says in the film. 
In the documentary Cluck! 
Chickens Exposed, Suresh Neethirajan shows examples of some of the birds’ sounds and the meaning behind them. 
He believes a tool could help translate exchanges between chickens and humans. 
In the future, farmers could use their chickens’ calls to monitor them and adjust conditions to improve their well-being. 
“The happy bird is a productive bird,” Neethirajan says. 
Learn more in Cluck! 
Chickens Exposed, now streaming on CBC Gem and The Nature of Things YouTube channel. 
Confirmation Bias
3.9%
Anchoring Bias
0%
Availability Heuristic
0%
Representativeness Heuristic
3.9%
Hindsight Bias
0%
Overconfidence Bias
11.3%
Framing Effect
0%
Loss Aversion
0%
Status Quo Bias
4.3%
Sunk Cost Effect
10.9%
Optimism Bias
22.6%
Pessimism Bias
8.3%
Negativity Bias
2.2%
Self-Serving Bias
0%
Fundamental Attribution Error
0%
Actor-Observer Bias
0%
In-Group Bias
0%
Out-Group Homogeneity Bias
0%
Halo Effect
7.4%
Horn Effect
0%
Dunning-Kruger Effect
0%
Recency Bias
8.3%
Primacy Effect
0%
Blind-Spot Bias
0%
Ad Hominem
0%
Straw Man
0%
Appeal to Authority
15.2%
False Dilemma
5.2%
Slippery Slope
0%
Circular Reasoning
0%
Hasty Generalization
15.2%
Red Herring
0%
Bandwagon
0%
Appeal to Emotion
11.3%
Begging the Question
9.1%
Post Hoc (False Cause)
8.3%
Tu Quoque
0%
Burden of Proof
0%
Appeal to Nature
0%
Composition/Division
0%
Anecdotal
11.3%
No True Scotsman
0%
Ambiguity (Equivocation)
29.6%
Gambler’s Fallacy
0%
Middle Ground
0%
Personal Incredulity
0%
Special Pleading
0%
Genetic Fallacy
0%
Unattributed Quote
11.3%
Quote-first Misdirection
2.2%
Biased Writer Voice
0%
Indoctrination
0%
Politically Left Leaning Bias
0%
Politically Right Leaning Bias
0%
Attempt to Sell a Product or Service
7.8%

230 words analyzed.

Analysis

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