Gothamist76%

Is that WNYC interview invite real, or part of ‘an emerging scam model?’ 16%

By Catalina Gonella27%

5/10/2026, 3:01:08 PM

BS Summary: This article contains 8 faulty reasoning types, including Availability Heuristic, Hasty Generalization, and False Dilemma, with Appeal to Authority as the most egregious example at 10.8% saturation with 64 hits. Analysis detected 354 faulty-reasoning hits from 590 analyzed words, generating a BS Score of 31.7% and a BS Rank of 16% (17,935 of 21,172 articles). This article is better (less manipulative) than 84.70% of the article peer group.

Maine-based artist and writer Ann Tracy was initially thrilled when she got an email inviting her to be a guest on "The New Yorker Radio Hour," a show and podcast hosted by New Yorker editor David Remnick and co-produced by the magazine and WNYC Studios. 
But then she realized the email address didn’t look like it belonged to the organization. 
 I'm thinking, 'Oh my God, how did they figure out little old Ann Tracy,'" she said. 
“Then my intuition kicked in, and I started looking at the email itself a little more closely, and noticed number one, it was from a Gmail account, not from 'The New Yorker Radio Hour' account, and I thought, ‘hmm.’” 
According to WNYC’s in-house data security expert, Kenneth Atkins, Tracy was one of dozens of people, many of them authors, who got similar “phishing” emails  fraudulent messages that aim to steal personal information  from accounts impersonating producers or hosts of different WNYC shows, inviting them to be on-air guests. 
WNYC is part of New York Public Radio, an organization that includes Gothamist. 
“The important thing here is that ultimately they ask the authors to provide either some sort of voluntary contribution or a fixed fee to be on the show to cover the cost of promotion and to cover the cost of production,” Atkins said on WNYC’s "Brian Lehrer Show" last week. 
But, as host Brian Lehrer emphasized: “Our interviews and our airtime are never for sale, nor do we collect fees from our guests for logistics, production, or anything else that goes into making the show. 
We will never ask you to pay to come on.” 
New York state’s Division of Consumer Protection has tracked more than 6,000 similar impersonation scam reports in the past 12 months across the five boroughs. 
The agency didn’t find any complaints specifically mentioning WNYC, but instead found three other similar complaints across the country impersonating other public radio stations. 
“They were all filed within the past month, so this may be an emerging scam model,” said Mercedes Padilla, a spokesperson for the division. 
Tracy told Gothamist the email she received from the phony account was well written, parroting career highlights such as her “continued engagement with theatre through the SnowLion Repertory Theatre Company’s Play Lab” and “your multidisciplinary creative life, spanning performance, writing, and media” as reasons why she would be a good fit for the show. 
 It was almost too well-written to be a scam. 
And I thought to myself, ‘Well, it could be real or it could be someone using AI crawling my website, getting the information from that, and then working that with AI into an email,” she said. 
Tracy’s hunch could be correct, said Rachel Tobac, CEO of San-Francisco-based SocialProof Security. 
More scammers are using a tactic called “spear phishing,” a targeted form of cyberattack that uses information about their targets available online to craft personalized, deceptive emails with the goal of extracting personal information or money. 
 They're definitely increasing in believability and scalability because of AI,” Tobac said. 
“Previously, attackers will have to go and draft a phishing message for each and every individual person. 
It takes a really long time for the attacker to do that. 
But now? 
"AI can do all of the research, choose the targets, develop the text message or the email or the phone call, even do a voice clone or a deepfake to sound like somebody that they're not.” 
Article reasoning-pattern comparisonThis article: 2.2%Catalina Gonella: 1.9%Gothamist: 2.7%Confirmation Bias2.2%This article: 0.0%Catalina Gonella: 0.5%Gothamist: 1.5%Anchoring Bias0.0%This article: 10.3%Catalina Gonella: 4.0%Gothamist: 3.6%Availability Heuristic10.3%This article: 0.0%Catalina Gonella: 1.0%Gothamist: 1.1%Representativeness Heuristic0.0%This article: 0.0%Catalina Gonella: 0.5%Gothamist: 0.7%Hindsight Bias0.0%This article: 0.0%Catalina Gonella: 1.1%Gothamist: 1.2%Overconfidence Bias0.0%This article: 0.0%Catalina Gonella: 3.6%Gothamist: 8.4%Framing Effect0.0%This article: 0.0%Catalina Gonella: 1.0%Gothamist: 1.2%Loss Aversion0.0%This article: 0.0%Catalina Gonella: 0.7%Gothamist: 1.1%Status Quo Bias0.0%This article: 0.0%Catalina Gonella: 0.1%Gothamist: 0.2%Sunk Cost Effect0.0%This article: 0.0%Catalina Gonella: 3.3%Gothamist: 3.6%Optimism Bias0.0%This article: 6.1%Catalina Gonella: 1.1%Gothamist: 1.7%Pessimism Bias6.1%This article: 0.0%Catalina Gonella: 5.3%Gothamist: 8.5%Negativity Bias0.0%This article: 0.0%Catalina Gonella: 1.1%Gothamist: 2.6%Self-Serving Bias0.0%This article: 0.0%Catalina Gonella: 0.5%Gothamist: 1.0%Fundamental Attribution Error0.0%This article: 0.0%Catalina Gonella: 0.3%Gothamist: 0.3%Actor-Observer Bias0.0%This article: 0.0%Catalina Gonella: 1.4%Gothamist: 2.1%In-Group Bias0.0%This article: 0.0%Catalina Gonella: 0.1%Gothamist: 0.6%Out-Group Homogeneity Bias0.0%This article: 0.0%Catalina Gonella: 1.6%Gothamist: 2.1%Halo Effect0.0%This article: 0.0%Catalina Gonella: 0.0%Gothamist: 0.2%Horn Effect0.0%This article: 0.0%Catalina Gonella: 0.0%Gothamist: 0.0%Dunning-Kruger Effect0.0%This article: 0.0%Catalina Gonella: 1.2%Gothamist: 1.3%Recency Bias0.0%This article: 0.0%Catalina Gonella: 0.4%Gothamist: 0.4%Primacy Effect0.0%This article: 0.0%Catalina Gonella: 0.1%Gothamist: 0.1%Blind-Spot Bias0.0%This article: 0.0%Catalina Gonella: 0.1%Gothamist: 1.0%Ad Hominem0.0%This article: 0.0%Catalina Gonella: 0.1%Gothamist: 0.2%Straw Man0.0%This article: 10.8%Catalina Gonella: 2.8%Gothamist: 4.4%Appeal to Authority10.8%This article: 8.3%Catalina Gonella: 0.7%Gothamist: 1.2%False Dilemma8.3%This article: 6.1%Catalina Gonella: 0.1%Gothamist: 0.8%Slippery Slope6.1%This article: 0.0%Catalina Gonella: 0.0%Gothamist: 0.1%Circular Reasoning0.0%This article: 10.2%Catalina Gonella: 3.8%Gothamist: 3.8%Hasty Generalization10.2%This article: 0.0%Catalina Gonella: 0.0%Gothamist: 0.3%Red Herring0.0%This article: 0.0%Catalina Gonella: 0.6%Gothamist: 0.8%Bandwagon0.0%This article: 0.0%Catalina Gonella: 4.2%Gothamist: 6.4%Appeal to Emotion0.0%This article: 0.0%Catalina Gonella: 0.4%Gothamist: 0.7%Begging the Question0.0%This article: 0.0%Catalina Gonella: 2.0%Gothamist: 2.4%Post Hoc (False Cause)0.0%This article: 0.0%Catalina Gonella: 0.1%Gothamist: 0.1%Tu Quoque0.0%This article: 0.0%Catalina Gonella: 0.4%Gothamist: 0.4%Burden of Proof0.0%This article: 0.0%Catalina Gonella: 0.0%Gothamist: 0.2%Appeal to Nature0.0%This article: 0.0%Catalina Gonella: 0.0%Gothamist: 0.2%Composition/Division0.0%This article: 0.0%Catalina Gonella: 3.0%Gothamist: 2.8%Anecdotal0.0%This article: 0.0%Catalina Gonella: 0.0%Gothamist: 0.1%No True Scotsman0.0%This article: 0.0%Catalina Gonella: 0.9%Gothamist: 1.2%Ambiguity (Equivocation)0.0%This article: 0.0%Catalina Gonella: 0.0%Gothamist: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Catalina Gonella: 0.1%Gothamist: 0.1%Middle Ground0.0%This article: 0.0%Catalina Gonella: 0.1%Gothamist: 0.1%Personal Incredulity0.0%This article: 0.0%Catalina Gonella: 0.0%Gothamist: 0.2%Special Pleading0.0%This article: 0.0%Catalina Gonella: 0.0%Gothamist: 0.2%Genetic Fallacy0.0%This article: 0.0%Catalina Gonella: 1.0%Gothamist: 1.2%Unattributed Quote0.0%This article: 5.9%Catalina Gonella: 1.8%Gothamist: 1.0%Quote-first Misdirection5.9%This article: 0.0%Catalina Gonella: 3.9%Gothamist: 3.2%Biased Writer Voice0.0%This article: 0.0%Catalina Gonella: 3.7%Gothamist: 1.5%Indoctrination0.0%This article: 0.0%Catalina Gonella: 0.2%Gothamist: 1.0%Politically Left Leaning Bias0.0%This article: 0.0%Catalina Gonella: 0.1%Gothamist: 0.2%Politically Right Leaning Bias0.0%This article: 0.0%Catalina Gonella: 0.9%Gothamist: 1.0%Attempt to Sell a Product or S…0.0%

590 words analyzed.

Speakers

5speakers51%attributed speech289writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 13 words • 0.0% coverageWriter's voice • 45 words • 0.0% coverageWriter's voice • 15 words • 0.0% coverageAnn Tracy • 17 words • 0.0% coverageAnn Tracy • 39 words • 0.0% coverageWriter's voice • 51 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageKenneth Atkins • 50 words • 0.0% coverageBrian Lehrer • 35 words • 100.0% coverageBrian Lehrer • 10 words • 0.0% coverageWriter's voice • 25 words • 0.0% coverageWriter's voice • 24 words • 0.0% coverageMercedes Padilla • 24 words • 0.0% coverageWriter's voice • 54 words • 0.0% coverageAnn Tracy • 10 words • 0.0% coverageAnn Tracy • 36 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 36 words • 0.0% coverageRachel Tobac • 13 words • 0.0% coverageRachel Tobac • 17 words • 0.0% coverageRachel Tobac • 12 words • 0.0% coverageRachel Tobac • 2 words • 0.0% coverageRachel Tobac • 36 words • 0.0% coverage
Selected voice

Rachel Tobac

61%flagged-word coverage
80 attributed words27% of attributed speech48% writer coverage

No manipulation-pattern hits were found in this speaker's attributed words or the writer's voice.

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.