FedScoop40%

Tom Cotton prods Treasury for tax code tweaks to modernize OT 57%

By mbracken56%

8/5/2026, 12:18:42 PM

BS Summary: This article contains 16 faulty reasoning types, including Ambiguity (Equivocation), Biased Writer Voice, and Status Quo Bias, with Negativity Bias as the most egregious example at 25.5% saturation with 109 hits. Analysis detected 786 faulty-reasoning hits from 428 analyzed words, generating a BS Score of 45.5% and a BS Rank of 57% (13,773 of 31,653 articles). This article is worse (more manipulative) than 56.50% of the article peer group.

With the country’s operational technology underfunded, outdated and increasingly vulnerable to cyberattacks, the Senate Intelligence Committee chairman is pushing the Treasury Department to do what it can to spur investment in it. 
Sen. 
Tom Cotton, R-Ark., said in a letter Wednesday to Treasury Secretary Scott Bessent that the department “can make better use of existing incentives in the tax code” to bolster OT, the hardware and software that underpins U.S. critical infrastructure. 
“The United States is already under attack,” Cotton wrote, pointing to recent cyberattacks on community water systems in Minnesota and an Iran-backed campaign to exploit programmable logic controllers across American critical infrastructure. 
“Those who carry the greatest risk are least able to manage it.” 
Cotton, who has led the Senate Intel panel since the beginning of the second Trump administration, made the case that federal tax guidance “discourages” investment needed to defend OT at a time when attacks on civilian infrastructure “have become a routine instrument of modern warfare.” 
Some of the technology is profoundly antiquated; Cotton noted that controllers responsible for running turbines or processing lines were invented in the 1960s “and still rely on protocols designed for isolated plants, not for today’s interconnected environment.” 
The problem calls for action from Treasury to spur modernization and investment in OT, Cotton said in the letter, starting with confirmation from the agency that developing security software for industrial control systems is counted as research under Section 41 of the U.S. tax code. 
“A company writing code to detect an intruder inside a water plant’s controls is doing research in the ordinary sense of the word,” Cotton said. 
“The tax code rewards research, but it is unclear whether this research qualifies, which discourages the necessary investments in operational technology security.” 
The Arkansas Republican also implored Bessent to use section 7701(e) to create a “safe harbor” for cybersecurity agreements with public utilities, clarifying that monitoring contracts would be treated as services as opposed to long-term equipment leases. 
Finally, Cotton asked Bessent to extend a current exception for companies that lease security equipment to utilities to the service providers as well. 
Under current tax code, lessors are protected, “but a company that retains ownership and sells monitoring services receives no such protection, even though the work is essentially identical,” the letter noted. 
“The distinction steers small systems away from these arrangements.” 
Cotton didn’t set a deadline for responses in his letter to Bessent, writing that he looked forward to working on the matter and stands “ready to discuss further.” 
Article reasoning-pattern comparisonThis article: 14.3%mbracken: 2.0%FedScoop: 1.4%Confirmation Bias14.3%This article: 10.5%mbracken: 1.5%FedScoop: 0.5%Anchoring Bias10.5%This article: 7.5%mbracken: 3.6%FedScoop: 1.9%Availability Heuristic7.5%This article: 0.0%mbracken: 0.3%FedScoop: 0.3%Representativeness Heuristic0.0%This article: 0.0%mbracken: 0.5%FedScoop: 0.1%Hindsight Bias0.0%This article: 0.0%mbracken: 3.8%FedScoop: 1.3%Overconfidence Bias0.0%This article: 10.5%mbracken: 5.1%FedScoop: 3.7%Framing Effect10.5%This article: 8.4%mbracken: 0.7%FedScoop: 0.3%Loss Aversion8.4%This article: 15.9%mbracken: 1.2%FedScoop: 0.4%Status Quo Bias15.9%This article: 0.0%mbracken: 0.0%FedScoop: 0.1%Sunk Cost Effect0.0%This article: 6.5%mbracken: 2.1%FedScoop: 2.2%Optimism Bias6.5%This article: 5.1%mbracken: 0.6%FedScoop: 0.8%Pessimism Bias5.1%This article: 25.5%mbracken: 4.5%FedScoop: 7.2%Negativity Bias25.5%This article: 0.0%mbracken: 0.0%FedScoop: 0.7%Self-Serving Bias0.0%This article: 0.0%mbracken: 0.0%FedScoop: 0.0%Fundamental Attribution Error0.0%This article: 0.0%mbracken: 0.0%FedScoop: 0.0%Actor-Observer Bias0.0%This article: 0.0%mbracken: 0.0%FedScoop: 0.1%In-Group Bias0.0%This article: 0.0%mbracken: 0.0%FedScoop: 0.0%Out-Group Homogeneity Bias0.0%This article: 0.0%mbracken: 0.3%FedScoop: 0.4%Halo Effect0.0%This article: 0.0%mbracken: 0.0%FedScoop: 0.0%Horn Effect0.0%This article: 0.0%mbracken: 0.0%FedScoop: 0.0%Dunning-Kruger Effect0.0%This article: 0.0%mbracken: 0.9%FedScoop: 0.5%Recency Bias0.0%This article: 0.0%mbracken: 0.0%FedScoop: 0.0%Primacy Effect0.0%This article: 0.0%mbracken: 0.0%FedScoop: 0.0%Blind-Spot Bias0.0%This article: 0.0%mbracken: 0.0%FedScoop: 0.4%Ad Hominem0.0%This article: 0.0%mbracken: 0.2%FedScoop: 0.0%Straw Man0.0%This article: 0.0%mbracken: 2.3%FedScoop: 1.4%Appeal to Authority0.0%This article: 0.0%mbracken: 3.1%FedScoop: 1.0%False Dilemma0.0%This article: 0.0%mbracken: 0.0%FedScoop: 0.5%Slippery Slope0.0%This article: 0.0%mbracken: 0.5%FedScoop: 0.1%Circular Reasoning0.0%This article: 2.1%mbracken: 4.3%FedScoop: 2.4%Hasty Generalization2.1%This article: 0.0%mbracken: 0.0%FedScoop: 0.0%Red Herring0.0%This article: 0.0%mbracken: 1.3%FedScoop: 0.8%Bandwagon0.0%This article: 0.0%mbracken: 1.8%FedScoop: 3.5%Appeal to Emotion0.0%This article: 0.0%mbracken: 1.5%FedScoop: 0.8%Begging the Question0.0%This article: 15.7%mbracken: 1.6%FedScoop: 0.9%Post Hoc (False Cause)15.7%This article: 0.0%mbracken: 0.0%FedScoop: 0.0%Tu Quoque0.0%This article: 0.0%mbracken: 0.0%FedScoop: 0.0%Burden of Proof0.0%This article: 0.0%mbracken: 0.0%FedScoop: 0.0%Appeal to Nature0.0%This article: 0.0%mbracken: 0.0%FedScoop: 0.0%Composition/Division0.0%This article: 7.5%mbracken: 1.8%FedScoop: 0.9%Anecdotal7.5%This article: 0.0%mbracken: 0.0%FedScoop: 0.0%No True Scotsman0.0%This article: 18.5%mbracken: 1.6%FedScoop: 0.7%Ambiguity (Equivocation)18.5%This article: 0.0%mbracken: 0.0%FedScoop: 0.0%Gambler’s Fallacy0.0%This article: 0.0%mbracken: 0.3%FedScoop: 0.1%Middle Ground0.0%This article: 0.0%mbracken: 0.0%FedScoop: 0.2%Personal Incredulity0.0%This article: 10.5%mbracken: 0.8%FedScoop: 0.2%Special Pleading10.5%This article: 0.0%mbracken: 0.0%FedScoop: 0.0%Genetic Fallacy0.0%This article: 0.0%mbracken: 0.0%FedScoop: 0.3%Unattributed Quote0.0%This article: 0.0%mbracken: 1.2%FedScoop: 1.4%Quote-first Misdirection0.0%This article: 16.1%mbracken: 1.4%FedScoop: 1.4%Biased Writer Voice16.1%This article: 0.0%mbracken: 4.3%FedScoop: 1.9%Indoctrination0.0%This article: 0.0%mbracken: 0.0%FedScoop: 0.1%Politically Left Leaning Bias0.0%This article: 0.0%mbracken: 0.0%FedScoop: 0.0%Politically Right Leaning Bias0.0%This article: 9.1%mbracken: 1.0%FedScoop: 0.3%Attempt to Sell a Product or S…9.1%

428 words analyzed.

Speakers

1speaker90%attributed speech44writer words
Selected voice

Tom Cotton

88%flagged-word coverage
384 attributed words100% of attributed speech73% writer coverage
0%37.5%75.0%Biased Writer Voice-63.1 ptsWriter: 72.7%Tom Cotton: 9.6%9.6%Attempt to Sell a Product +10.2 ptsWriter: 0.0%Tom Cotton: 10.2%10.2%

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

Loading…
Loading…
Loading…
Loading…

Analysis

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