KQED⁠61%

How AI and Tech Are Changing The Campaign Finance Game ⁠0%

By Marisa Lagos⁠87% Scott Shafer⁠0%

3/25/2026, 12:00:44 AM

BS Summary: This article contains 7 faulty reasoning types, including Biased Writer Voice, Negativity Bias, and Appeal to Emotion, with Framing Effect as the most egregious example at 70.2% saturation with 73 hits. Analysis detected 366 faulty-reasoning hits from 104 analyzed words, generating a BS Score of 0% and a BS Rank of ⁠0% (0 of 21,886 articles). This article is better (less manipulative) than 100.00% of the article peer group.

With the 2026 midterms ahead, a flood of campaign donations is expected in California and beyond — with a growing amount coming from the tech industry, including a $500 million push by California tech billionaires. 
Scott and Marisa sit down with Hilary Braseth, Executive Director of the nonpartisan organization Open Secrets, to discuss what these donations could mean as the primary season gets into full swing. 
They also dig into the rise of hard-to-trace “dark money,” and how emerging industries like AI and crypto are using a new playbook to influence elections and policy. 
Article reasoning-pattern comparisonThis article: 0.0%Marisa Lagos: 5.0%CalMatters: 1.9%Confirmation Bias0.0%This article: 0.0%Marisa Lagos: 0.9%CalMatters: 0.9%Anchoring Bias0.0%This article: 33.7%Marisa Lagos: 4.2%CalMatters: 3.0%Availability Heuristic33.7%This article: 0.0%Marisa Lagos: 1.8%CalMatters: 1.0%Representativeness Heuristic0.0%This article: 0.0%Marisa Lagos: 1.0%CalMatters: 0.5%Hindsight Bias0.0%This article: 0.0%Marisa Lagos: 1.9%CalMatters: 1.2%Overconfidence Bias0.0%This article: 70.2%Marisa Lagos: 14.7%CalMatters: 6.3%Framing Effect70.2%This article: 0.0%Marisa Lagos: 0.4%CalMatters: 1.0%Loss Aversion0.0%This article: 0.0%Marisa Lagos: 1.5%CalMatters: 0.7%Status Quo Bias0.0%This article: 0.0%Marisa Lagos: 0.0%CalMatters: 0.2%Sunk Cost Effect0.0%This article: 0.0%Marisa Lagos: 3.5%CalMatters: 3.5%Optimism Bias0.0%This article: 0.0%Marisa Lagos: 0.7%CalMatters: 1.4%Pessimism Bias0.0%This article: 60.6%Marisa Lagos: 11.6%CalMatters: 6.4%Negativity Bias60.6%This article: 0.0%Marisa Lagos: 2.8%CalMatters: 1.7%Self-Serving Bias0.0%This article: 0.0%Marisa Lagos: 2.1%CalMatters: 0.7%Fundamental Attribution Error0.0%This article: 0.0%Marisa Lagos: 0.5%CalMatters: 0.2%Actor-Observer Bias0.0%This article: 0.0%Marisa Lagos: 2.9%CalMatters: 1.7%In-Group Bias0.0%This article: 0.0%Marisa Lagos: 1.1%CalMatters: 0.4%Out-Group Homogeneity Bias0.0%This article: 0.0%Marisa Lagos: 2.7%CalMatters: 2.7%Halo Effect0.0%This article: 0.0%Marisa Lagos: 0.3%CalMatters: 0.1%Horn Effect0.0%This article: 0.0%Marisa Lagos: 0.0%CalMatters: 0.0%Dunning-Kruger Effect0.0%This article: 0.0%Marisa Lagos: 2.5%CalMatters: 0.9%Recency Bias0.0%This article: 0.0%Marisa Lagos: 1.0%CalMatters: 0.3%Primacy Effect0.0%This article: 0.0%Marisa Lagos: 0.1%CalMatters: 0.0%Blind-Spot Bias0.0%This article: 0.0%Marisa Lagos: 1.9%CalMatters: 0.6%Ad Hominem0.0%This article: 0.0%Marisa Lagos: 0.2%CalMatters: 0.2%Straw Man0.0%This article: 29.8%Marisa Lagos: 4.5%CalMatters: 3.1%Appeal to Authority29.8%This article: 0.0%Marisa Lagos: 2.5%CalMatters: 1.1%False Dilemma0.0%This article: 0.0%Marisa Lagos: 1.1%CalMatters: 0.8%Slippery Slope0.0%This article: 0.0%Marisa Lagos: 0.1%CalMatters: 0.1%Circular Reasoning0.0%This article: 26.9%Marisa Lagos: 4.6%CalMatters: 3.6%Hasty Generalization26.9%This article: 0.0%Marisa Lagos: 1.1%CalMatters: 0.2%Red Herring0.0%This article: 0.0%Marisa Lagos: 1.5%CalMatters: 0.7%Bandwagon0.0%This article: 60.6%Marisa Lagos: 6.5%CalMatters: 5.3%Appeal to Emotion60.6%This article: 0.0%Marisa Lagos: 1.6%CalMatters: 0.6%Begging the Question0.0%This article: 0.0%Marisa Lagos: 3.6%CalMatters: 2.0%Post Hoc (False Cause)0.0%This article: 0.0%Marisa Lagos: 0.2%CalMatters: 0.1%Tu Quoque0.0%This article: 0.0%Marisa Lagos: 1.1%CalMatters: 0.3%Burden of Proof0.0%This article: 0.0%Marisa Lagos: 0.1%CalMatters: 0.2%Appeal to Nature0.0%This article: 0.0%Marisa Lagos: 0.3%CalMatters: 0.2%Composition/Division0.0%This article: 0.0%Marisa Lagos: 1.2%CalMatters: 3.1%Anecdotal0.0%This article: 0.0%Marisa Lagos: 0.0%CalMatters: 0.0%No True Scotsman0.0%This article: 0.0%Marisa Lagos: 1.5%CalMatters: 1.2%Ambiguity (Equivocation)0.0%This article: 0.0%Marisa Lagos: 0.0%CalMatters: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Marisa Lagos: 0.3%CalMatters: 0.1%Middle Ground0.0%This article: 0.0%Marisa Lagos: 0.2%CalMatters: 0.1%Personal Incredulity0.0%This article: 0.0%Marisa Lagos: 0.8%CalMatters: 0.1%Special Pleading0.0%This article: 0.0%Marisa Lagos: 0.7%CalMatters: 0.1%Genetic Fallacy0.0%This article: 0.0%Marisa Lagos: 0.9%CalMatters: 0.8%Unattributed Quote0.0%This article: 0.0%Marisa Lagos: 0.8%CalMatters: 0.7%Quote-first Misdirection0.0%This article: 70.2%Marisa Lagos: 7.1%CalMatters: 3.1%Biased Writer Voice70.2%This article: 0.0%Marisa Lagos: 1.0%CalMatters: 1.9%Indoctrination0.0%This article: 0.0%Marisa Lagos: 6.1%CalMatters: 1.1%Politically Left Leaning Bias0.0%This article: 0.0%Marisa Lagos: 1.1%CalMatters: 0.1%Politically Right Leaning Bias0.0%This article: 0.0%Marisa Lagos: 3.5%CalMatters: 1.2%Attempt to Sell a Product or S…0.0%

104 words analyzed.

Speakers

No attributed speakers were identified in this analysis.

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Analysis

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