A Little Law Gives Hope That Government Can Suck Less and Make People’s Lives Better 12%

By Sophie Hurwitz63%

7/12/2026, 7:50:29 PM

BS Summary: This article contains 27 faulty reasoning types, including Hasty Generalization, Anecdotal, and Loss Aversion, with Negativity Bias as the most egregious example at 32.3% saturation with 272 hits. Analysis detected 1,904 faulty-reasoning hits from 843 analyzed words, generating a BS Score of 28.7% and a BS Rank of 12% (19,340 of 21,887 articles). This article is better (less manipulative) than 88.40% of the article peer group.

When Sam Levine, Commissioner of New York City’s Department of Consumer and Worker Protection (DCWP), was eleven, he signed up for a service that would send him ten free CDs in the mail. 
“I didn’t know it then, but I had just signed up for my first subscription,” Levine said. 
A few months and a pile of bills later, he was begging his parents to help him cancel the membership he’d unknowingly purchased. 
It’s been 28 years since Levine was lured in with the promise of a Cher CD, but the problem of “subscription traps”—subscriptions which are easy to get, but a minefield to cancel  has only gotten worse . 
At a press conference Friday, Levine joined New York City Mayor Zohran Mamdani and former FTC Commissioner Lina Khan to present a municipal-level solution: New York City’s Click To Cancel Rule. 
“These are now part of the business model for some of the largest companies in our economy.” 
The idea behind the regulation is simple. 
A subscription should be as easy to cancel as it is to sign up for. 
A person should not be required to cancel a gym membership in-person if they got that membership online, or mail in a letter, or spend hours on hold with customer service in order to stop being charged for a service they aren’t using. 
Click to cancel is not a new idea: Under Joe Biden and Commissioner Khan, the Federal Trade Commission approved a federal click to cancel rule in 2024—only for that rule to be struck down on procedural grounds by the Eighth Circuit Court a year later, after a trade group representing major cable and internet providers sued to block it from going into effect. 
(Trump’s FTC may revive the rule , which was widely popular with consumers, later this year.) 
“At the Federal Trade Commission, we would receive tens of thousands of complaints each year from people who had lost hard-earned money to these predatory schemes,” Khan, a member of Mamdani’s transition team, said at Friday’s press conference. 
“People wrote to us about spending days trying to cancel a gym membership, about charges that kept appearing months after they’d been canceled…These are not just the tactics of fly-by-night scammers. 
These are now part of the business model for some of the largest companies in our economy.” 
Uber, for instance, is currently being sued by the FTC and a coalition of state Attorneys General for allegedly “misleading customers by trapping them in recurring subscriptions to its Uber One service that were exceedingly difficult to cancel.” 
Adobe, too, has been accused of using these practices: An Adobe executive, according to court documents unearthed in 2024, called hidden early-termination fees  a bit like heroin  for the company. 
Now, under Andrew Ferguson, the FTC is less aggressive about consumer-protection enforcement than it was under Khan. 
But on the state and city levels, consumers still have advocates. 
In California, Maryland and Colorado , statewide Click To Cancel rules are in effect. 
In New York, too, statewide consumer protections are already among the strongest in the country . 
But when New York City’s rule goes into effect this October, it will be the first municipal law of its kind, Mamdani said. 
It will add a local enforcement mechanism, DCWP Commissioner Levine said, giving New Yorkers the opportunity to complain directly about subscription traps by calling 311. 
And it’s expected to collectively save New Yorkers somewhere between $ 21.5 and $162.5 million per year, according to the Roosevelt Institute. 
Friday’s announcement—held, notably, in a gym, in front of a cluster of elliptical machines—is part of a broader crackdown on predatory pricing. 
New York City is also targeting so-called “junk fees” that raise the final price of everything from apartments to sporting events, requiring companies to advertise final prices including additional charges or fees up-front. 
“It is estimated that the average family of four loses more than $3,200 per year on junk fees and hidden costs,” Mamdani said at the press conference. 
Enforcement will begin October 1, with businesses that don’t provide easy cancellation processes facing civil penalties starting at $525 per violation. 
For 187 New York City gyms, warning letters were already sent out this past February. 
New Yorkers will be able to file complaints through the Department of Consumer and Worker Protections, which may then take subscription-trapping companies to court. 
Under Trump’s regulation-averse federal government—one that in fact brands itself as having the  most ambitious deregulation agenda in history” —big companies tend to be able to extract value from people and come out on top without repercussions. 
Unwanted subscription fees, Khan said, “represent an upwards transfer of wealth; often from people who are already living on the financial margins of this city, to people who ultimately looking to buy a private jet or a second yacht.” 
So it’s nice to see that, at least on the local level, protecting people from predatory corporate tactics might still be possible. 
Article reasoning-pattern comparisonThis article: 11.0%Sophie Hurwitz: 6.2%Mother Jones: 4.0%Confirmation Bias11.0%This article: 0.0%Sophie Hurwitz: 1.1%Mother Jones: 0.7%Anchoring Bias0.0%This article: 3.7%Sophie Hurwitz: 4.7%Mother Jones: 3.3%Availability Heuristic3.7%This article: 4.5%Sophie Hurwitz: 1.0%Mother Jones: 0.8%Representativeness Heuristic4.5%This article: 0.0%Sophie Hurwitz: 0.8%Mother Jones: 0.8%Hindsight Bias0.0%This article: 0.0%Sophie Hurwitz: 0.9%Mother Jones: 1.2%Overconfidence Bias0.0%This article: 14.7%Sophie Hurwitz: 9.4%Mother Jones: 7.2%Framing Effect14.7%This article: 15.7%Sophie Hurwitz: 0.8%Mother Jones: 0.6%Loss Aversion15.7%This article: 0.0%Sophie Hurwitz: 0.4%Mother Jones: 0.6%Status Quo Bias0.0%This article: 0.0%Sophie Hurwitz: 0.0%Mother Jones: 0.1%Sunk Cost Effect0.0%This article: 8.7%Sophie Hurwitz: 1.4%Mother Jones: 1.6%Optimism Bias8.7%This article: 9.0%Sophie Hurwitz: 1.5%Mother Jones: 1.9%Pessimism Bias9.0%This article: 32.3%Sophie Hurwitz: 13.0%Mother Jones: 9.6%Negativity Bias32.3%This article: 0.0%Sophie Hurwitz: 1.4%Mother Jones: 0.8%Self-Serving Bias0.0%This article: 0.0%Sophie Hurwitz: 1.7%Mother Jones: 1.0%Fundamental Attribution Error0.0%This article: 2.0%Sophie Hurwitz: 0.1%Mother Jones: 0.2%Actor-Observer Bias2.0%This article: 0.0%Sophie Hurwitz: 2.5%Mother Jones: 1.0%In-Group Bias0.0%This article: 0.0%Sophie Hurwitz: 1.4%Mother Jones: 0.5%Out-Group Homogeneity Bias0.0%This article: 1.9%Sophie Hurwitz: 1.0%Mother Jones: 1.5%Halo Effect1.9%This article: 0.0%Sophie Hurwitz: 0.8%Mother Jones: 0.3%Horn Effect0.0%This article: 0.0%Sophie Hurwitz: 0.1%Mother Jones: 0.0%Dunning-Kruger Effect0.0%This article: 3.9%Sophie Hurwitz: 2.0%Mother Jones: 1.1%Recency Bias3.9%This article: 2.7%Sophie Hurwitz: 0.7%Mother Jones: 0.3%Primacy Effect2.7%This article: 0.0%Sophie Hurwitz: 0.0%Mother Jones: 0.0%Blind-Spot Bias0.0%This article: 0.0%Sophie Hurwitz: 2.6%Mother Jones: 1.9%Ad Hominem0.0%This article: 0.0%Sophie Hurwitz: 1.6%Mother Jones: 0.6%Straw Man0.0%This article: 14.2%Sophie Hurwitz: 3.1%Mother Jones: 3.6%Appeal to Authority14.2%This article: 1.3%Sophie Hurwitz: 1.2%Mother Jones: 1.4%False Dilemma1.3%This article: 0.0%Sophie Hurwitz: 0.6%Mother Jones: 1.7%Slippery Slope0.0%This article: 0.0%Sophie Hurwitz: 0.0%Mother Jones: 0.1%Circular Reasoning0.0%This article: 21.7%Sophie Hurwitz: 7.9%Mother Jones: 4.7%Hasty Generalization21.7%This article: 2.6%Sophie Hurwitz: 0.8%Mother Jones: 0.2%Red Herring2.6%This article: 1.9%Sophie Hurwitz: 0.6%Mother Jones: 0.5%Bandwagon1.9%This article: 12.5%Sophie Hurwitz: 9.9%Mother Jones: 6.4%Appeal to Emotion12.5%This article: 0.0%Sophie Hurwitz: 1.6%Mother Jones: 1.1%Begging the Question0.0%This article: 12.0%Sophie Hurwitz: 1.4%Mother Jones: 2.1%Post Hoc (False Cause)12.0%This article: 0.0%Sophie Hurwitz: 0.3%Mother Jones: 0.1%Tu Quoque0.0%This article: 0.0%Sophie Hurwitz: 1.0%Mother Jones: 0.5%Burden of Proof0.0%This article: 0.0%Sophie Hurwitz: 0.0%Mother Jones: 0.3%Appeal to Nature0.0%This article: 0.0%Sophie Hurwitz: 0.4%Mother Jones: 0.3%Composition/Division0.0%This article: 16.8%Sophie Hurwitz: 5.4%Mother Jones: 2.3%Anecdotal16.8%This article: 0.0%Sophie Hurwitz: 0.1%Mother Jones: 0.1%No True Scotsman0.0%This article: 0.8%Sophie Hurwitz: 1.7%Mother Jones: 1.4%Ambiguity (Equivocation)0.8%This article: 0.0%Sophie Hurwitz: 0.0%Mother Jones: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Sophie Hurwitz: 0.1%Mother Jones: 0.1%Middle Ground0.0%This article: 0.0%Sophie Hurwitz: 0.0%Mother Jones: 0.1%Personal Incredulity0.0%This article: 0.0%Sophie Hurwitz: 0.1%Mother Jones: 0.1%Special Pleading0.0%This article: 0.0%Sophie Hurwitz: 0.4%Mother Jones: 0.3%Genetic Fallacy0.0%This article: 2.0%Sophie Hurwitz: 2.7%Mother Jones: 1.8%Unattributed Quote2.0%This article: 2.0%Sophie Hurwitz: 2.8%Mother Jones: 1.5%Quote-first Misdirection2.0%This article: 12.7%Sophie Hurwitz: 9.6%Mother Jones: 9.2%Biased Writer Voice12.7%This article: 6.9%Sophie Hurwitz: 2.0%Mother Jones: 1.8%Indoctrination6.9%This article: 4.5%Sophie Hurwitz: 4.9%Mother Jones: 4.5%Politically Left Leaning Bias4.5%This article: 0.0%Sophie Hurwitz: 1.0%Mother Jones: 0.3%Politically Right Leaning Bias0.0%This article: 3.8%Sophie Hurwitz: 0.2%Mother Jones: 0.7%Attempt to Sell a Product or S…3.8%

843 words analyzed.

Speakers

3speakers26%attributed speech626writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 15 words • 100.0% coverageWriter's voice • 33 words • 0.0% coverageSam Levine • 17 words • 100.0% coverageWriter's voice • 23 words • 0.0% coverageWriter's voice • 38 words • 100.0% coverageWriter's voice • 31 words • 0.0% coverageLina Khan • 17 words • 100.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 15 words • 100.0% coverageWriter's voice • 43 words • 100.0% coverageWriter's voice • 63 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageLina Khan • 38 words • 0.0% coverageLina Khan • 31 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 38 words • 0.0% coverageWriter's voice • 32 words • 100.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageZohran Mamdani • 23 words • 0.0% coverageSam Levine • 25 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageWriter's voice • 33 words • 0.0% coverageZohran Mamdani • 27 words • 0.0% coverageWriter's voice • 21 words • 0.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 24 words • 0.0% coverageWriter's voice • 38 words • 100.0% coverageLina Khan • 39 words • 0.0% coverageWriter's voice • 22 words • 100.0% coverage
Selected voice

Lina Khan

100%flagged-word coverage
125 attributed words58% of attributed speech73% writer coverage
0%10.0%20.0%Biased Writer Voice-17.1 ptsWriter: 17.1%Lina Khan: 0.0%0.0%Quote-first Misdirection+13.6 ptsWriter: 0.0%Lina Khan: 13.6%13.6%Indoctrination-9.3 ptsWriter: 9.3%Lina Khan: 0.0%0.0%Politically Left Leaning B-6.1 ptsWriter: 6.1%Lina Khan: 0.0%0.0%Attempt to Sell a Product -5.1 ptsWriter: 5.1%Lina Khan: 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.