KQED61%

Can New Cameras Save the Gray Whales in the San Francisco Bay? 34%

By Desmond Meagley0%

5/25/2026, 9:00:46 AM

BS Summary: This article contains 25 faulty reasoning types, including Optimism Bias, Overconfidence Bias, and Negativity Bias, with Attempt to Sell a Product or Service as the most egregious example at 16.2% saturation with 140 hits. Analysis detected 1,047 faulty-reasoning hits from 862 analyzed words, generating a BS Score of 41.8% and a BS Rank of 34% (14,598 of 21,887 articles). This article is better (less manipulative) than 66.70% of the article peer group.

On a sunny, clear Tuesday, marine scientist Douglas McCauley surveyed the cobalt-blue waters of the San Francisco Bay from a public ferry headed to Angel Island. 
He kept watch for gray whales breaking the surface of the water to breathe, traveling and hungry, near the boat’s path. 
 Five or 10 years ago, it would be unfathomable,” to be concerned about whales being struck by ships in the San Francisco Bay, said McCauley, the director of the Benioff Ocean Science Laboratory at the University of California, Santa Barbara. 
But recently, the ferry’s path has become a feeding “hotspot,” the scientist said  putting the 90,000 lb., migratory mammals directly in harm’s way. 
“This is a new thing, to be sharing this [busy] space with whales,“ McCauley continued. 
A new AI-powered camera, however, installed on the island’s Point Blunt, seeks to shine a light on the increased whale activity in the Bay, “with so much greater resolution and accuracy” than before. 
The camera, produced by Whalespotter, a Massachusetts-based company, searches for heat signatures of warm-blooded mammals  “a whale that’s breathing out in a cold bay,” McCauley said. 
To the thermal camera’s artificial intelligence, “that red hot heat from a warm whale is what stands out, kind of like a hot needle in a cold haystack.” 
Gray whales make one of the longest migrations of any animal on Earth, from their feeding grounds in the Arctic to lagoons in Baja California, where they have their offspring. 
Typically, they don’t consume any additional food along the journey, which spans over 12,000 miles. 
But changes to Arctic sea ice and weather patterns have reduced the whales’ usual food supply, McCauley said. 
Starvation, habitat loss from climate change, and boat strikes have contributed to reducing the population of the whales to their lowest totals in decades. 
While this species of gray whale is not considered endangered, their numbers dropped by half in the last ten years alone, from 26,000 to 13,000. 
Nearly one in five gray whales entering the Bay dies there, often due to vessel collisions, according to a new study published by Marin County’s Marine Mammal Center and California Academy of Sciences. 
McCauley said 21 dead whales surfaced in the Bay last year, and that 40% of them showed signs of being struck by a boat or shipping freighter. 
 The process really began last year in the heart of this crisis where everyone said, ‘Okay, we, we need a solution, and we need one fast.’” 
Within two hours from the moment the camera switched on two weeks ago, it had already identified 180 “blows,” or instances of whales coming to the surface of the water to breathe, according to Benioff scientist Rachel Rhodes. 
Though this was likely a small pod lingering in front of the sensor, the researchers took it as a sign they were in the right spot. 
“I think I’m a not-half-bad whale watcher,” said McCauley, but “that does a much better job than I do of actually seeing whales.” 
In order to bring the camera to the Bay Area and share its data with ships that need it, the Benioff lab partnered with over a dozen groups across industry, research and government. 
The Marine Mammal Center, which assists Benioff researchers analyze the condition of the whales that die in the Bay was a key partner, as was the Coast Guard, which offered a spot on one of their communications towers for the camera and reports whale sightings from Vessel Traffic Control. 
This week, the San Francisco Bay Ferry also switched on its own WhaleSpotter camera, which will operate on the Vallejo line and contribute to WhaleSafe, a free public database run by Benioff. 
WhaleSafe updates in real time using both reports from human spotters and WhaleSpotter sensors to give boats advance notice of whale traffic. 
Shawn Henry, WhaleSpotter’s CEO, said the Angel Island camera is the company’s first stationary sensor of its kind in California  the company set up similar cameras on the East Coast to monitor the endangered North Atlantic right whale. 
Time is a major consideration in keeping whales safe from larger ships, Henry said. 
Freighter ships can’t quickly slow down or change direction, and can strike whales without operators even noticing them. 
 We can provide very reliable detection of whales at long range, long enough in order for the largest vessels to take evasive action to avoid whales,” Henry said. 
Once the AI’s sightings are confirmed, the information is immediately shared with WhaleSafe users. 
Henry said the cost of these cameras is comparable to that of a traditional ship radar. 
Speaking at the camera’s ribbon-cutting on Tuesday, McCauley said he hopes to see a “network of sensors” across the Bay to account for “blind spots” in their search to save the whales. 
In California, he said, residents are well-versed in climate disruption and crisis, and in helping one another through it. 
“We have a whale that is adapting,” he told the crowd. 
“We’ve extended our definition of neighbor to include this backyard and those whales, and we’re here, in many ways, to help.” 
Article reasoning-pattern comparisonThis article: 3.0%Desmond Meagley: 1.7%CalMatters: 1.9%Confirmation Bias3.0%This article: 0.0%Desmond Meagley: 0.1%CalMatters: 0.9%Anchoring Bias0.0%This article: 3.1%Desmond Meagley: 2.0%CalMatters: 3.0%Availability Heuristic3.1%This article: 2.2%Desmond Meagley: 0.5%CalMatters: 1.0%Representativeness Heuristic2.2%This article: 4.8%Desmond Meagley: 1.5%CalMatters: 0.5%Hindsight Bias4.8%This article: 7.8%Desmond Meagley: 1.7%CalMatters: 1.2%Overconfidence Bias7.8%This article: 1.9%Desmond Meagley: 1.8%CalMatters: 6.3%Framing Effect1.9%This article: 0.0%Desmond Meagley: 0.5%CalMatters: 1.0%Loss Aversion0.0%This article: 0.0%Desmond Meagley: 1.2%CalMatters: 0.7%Status Quo Bias0.0%This article: 0.0%Desmond Meagley: 0.0%CalMatters: 0.2%Sunk Cost Effect0.0%This article: 16.0%Desmond Meagley: 3.9%CalMatters: 3.5%Optimism Bias16.0%This article: 2.1%Desmond Meagley: 1.3%CalMatters: 1.4%Pessimism Bias2.1%This article: 7.8%Desmond Meagley: 1.8%CalMatters: 6.4%Negativity Bias7.8%This article: 2.7%Desmond Meagley: 2.6%CalMatters: 1.7%Self-Serving Bias2.7%This article: 0.0%Desmond Meagley: 0.7%CalMatters: 0.7%Fundamental Attribution Error0.0%This article: 0.0%Desmond Meagley: 0.0%CalMatters: 0.2%Actor-Observer Bias0.0%This article: 4.6%Desmond Meagley: 1.9%CalMatters: 1.7%In-Group Bias4.6%This article: 0.0%Desmond Meagley: 0.0%CalMatters: 0.4%Out-Group Homogeneity Bias0.0%This article: 0.0%Desmond Meagley: 3.8%CalMatters: 2.7%Halo Effect0.0%This article: 0.0%Desmond Meagley: 0.0%CalMatters: 0.1%Horn Effect0.0%This article: 0.0%Desmond Meagley: 0.0%CalMatters: 0.0%Dunning-Kruger Effect0.0%This article: 4.6%Desmond Meagley: 0.3%CalMatters: 0.9%Recency Bias4.6%This article: 0.0%Desmond Meagley: 0.1%CalMatters: 0.3%Primacy Effect0.0%This article: 0.0%Desmond Meagley: 0.0%CalMatters: 0.0%Blind-Spot Bias0.0%This article: 0.0%Desmond Meagley: 0.4%CalMatters: 0.6%Ad Hominem0.0%This article: 0.0%Desmond Meagley: 0.1%CalMatters: 0.2%Straw Man0.0%This article: 4.5%Desmond Meagley: 3.6%CalMatters: 3.1%Appeal to Authority4.5%This article: 1.6%Desmond Meagley: 0.1%CalMatters: 1.1%False Dilemma1.6%This article: 0.0%Desmond Meagley: 0.4%CalMatters: 0.8%Slippery Slope0.0%This article: 0.0%Desmond Meagley: 0.4%CalMatters: 0.1%Circular Reasoning0.0%This article: 3.0%Desmond Meagley: 2.9%CalMatters: 3.6%Hasty Generalization3.0%This article: 0.0%Desmond Meagley: 0.0%CalMatters: 0.2%Red Herring0.0%This article: 3.1%Desmond Meagley: 2.6%CalMatters: 0.7%Bandwagon3.1%This article: 3.7%Desmond Meagley: 3.8%CalMatters: 5.3%Appeal to Emotion3.7%This article: 3.4%Desmond Meagley: 0.4%CalMatters: 0.6%Begging the Question3.4%This article: 5.9%Desmond Meagley: 1.5%CalMatters: 2.0%Post Hoc (False Cause)5.9%This article: 0.0%Desmond Meagley: 0.9%CalMatters: 0.1%Tu Quoque0.0%This article: 0.0%Desmond Meagley: 0.3%CalMatters: 0.3%Burden of Proof0.0%This article: 0.0%Desmond Meagley: 0.0%CalMatters: 0.2%Appeal to Nature0.0%This article: 2.2%Desmond Meagley: 0.4%CalMatters: 0.2%Composition/Division2.2%This article: 0.0%Desmond Meagley: 1.6%CalMatters: 3.1%Anecdotal0.0%This article: 0.0%Desmond Meagley: 0.0%CalMatters: 0.0%No True Scotsman0.0%This article: 1.3%Desmond Meagley: 0.1%CalMatters: 1.2%Ambiguity (Equivocation)1.3%This article: 0.0%Desmond Meagley: 0.0%CalMatters: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Desmond Meagley: 0.2%CalMatters: 0.1%Middle Ground0.0%This article: 0.0%Desmond Meagley: 0.3%CalMatters: 0.1%Personal Incredulity0.0%This article: 3.7%Desmond Meagley: 0.6%CalMatters: 0.1%Special Pleading3.7%This article: 0.0%Desmond Meagley: 0.3%CalMatters: 0.1%Genetic Fallacy0.0%This article: 0.0%Desmond Meagley: 0.3%CalMatters: 0.8%Unattributed Quote0.0%This article: 0.0%Desmond Meagley: 0.8%CalMatters: 0.7%Quote-first Misdirection0.0%This article: 6.0%Desmond Meagley: 1.3%CalMatters: 3.1%Biased Writer Voice6.0%This article: 6.1%Desmond Meagley: 1.3%CalMatters: 1.9%Indoctrination6.1%This article: 0.0%Desmond Meagley: 1.0%CalMatters: 1.1%Politically Left Leaning Bias0.0%This article: 0.0%Desmond Meagley: 0.0%CalMatters: 0.1%Politically Right Leaning Bias0.0%This article: 16.2%Desmond Meagley: 2.4%CalMatters: 1.2%Attempt to Sell a Product or S…16.2%

862 words analyzed.

Speakers

3speakers46%attributed speech468writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 12 words • 0.0% coverageWriter's voice • 26 words • 0.0% coverageWriter's voice • 21 words • 0.0% coverageDouglas McCauley • 41 words • 0.0% coverageDouglas McCauley • 24 words • 100.0% coverageDouglas McCauley • 15 words • 0.0% coverageWriter's voice • 33 words • 100.0% coverageDouglas McCauley • 27 words • 0.0% coverageWriter's voice • 28 words • 100.0% coverageWriter's voice • 30 words • 0.0% coverageWriter's voice • 15 words • 0.0% coverageDouglas McCauley • 18 words • 0.0% coverageWriter's voice • 24 words • 0.0% coverageWriter's voice • 25 words • 0.0% coverageWriter's voice • 33 words • 0.0% coverageDouglas McCauley • 27 words • 0.0% coverageWriter's voice • 27 words • 0.0% coverageRachel Rhodes • 38 words • 0.0% coverageWriter's voice • 26 words • 0.0% coverageDouglas McCauley • 23 words • 100.0% coverageWriter's voice • 33 words • 0.0% coverageWriter's voice • 49 words • 0.0% coverageWriter's voice • 32 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageShawn Henry • 39 words • 100.0% coverageShawn Henry • 14 words • 0.0% coverageWriter's voice • 18 words • 0.0% coverageShawn Henry • 29 words • 100.0% coverageWriter's voice • 14 words • 0.0% coverageShawn Henry • 16 words • 100.0% coverageDouglas McCauley • 32 words • 100.0% coverageDouglas McCauley • 19 words • 0.0% coverageDouglas McCauley • 11 words • 0.0% coverageDouglas McCauley • 21 words • 100.0% coverage
Selected voice

Shawn Henry

86%flagged-word coverage
98 attributed words25% of attributed speech41% writer coverage
0%45.0%90.0%Attempt to Sell a Product +78.7 ptsWriter: 7.1%Shawn Henry: 85.7%85.7%Biased Writer Voice-6.0 ptsWriter: 6.0%Shawn Henry: 0.0%0.0%

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

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Analysis

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