She had four kids with Elon Musk. Now she’s central to his courtroom fight. ⁠98%

By Elizabeth Dwoskin⁠0% Gerrit De Vynck⁠0% Faiz Siddiqui⁠0%

5/8/2026, 9:00:00 AM

BS Summary: This article contains 13 faulty reasoning types, including Biased Writer Voice, Framing Effect, and Availability Heuristic, with Appeal to Authority as the most egregious example at 73.7% saturation with 70 hits. Analysis detected 449 faulty-reasoning hits from 95 analyzed words, generating a BS Score of 96.3% and a BS Rank of ⁠98% (592 of 21,886 articles). This article is worse (more manipulative) than 97.30% of the article peer group.

OAKLAND, Calif. — Shivon Zilis had her back against the wall. 
For more than six years, the tech executive had worked largely outside the public eye as a trusted confidante to Tesla CEO Elon Musk and his three co-founders at the artificial intelligence start-up OpenAI. 
But now, as the company’s recently launched ChatGPT soared, OpenAI CEO Sam Altman had discovered that Musk was planning a rival AI venture and poaching talent from the start-up, according to federal court testimony this week. 
Article reasoning-pattern comparisonThis article: 35.8%Elizabeth Dwoskin: 11.9%The Washington Post: 3.8%Confirmation Bias35.8%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 1.3%Anchoring Bias0.0%This article: 37.9%Elizabeth Dwoskin: 12.6%The Washington Post: 4.9%Availability Heuristic37.9%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 1.0%Representativeness Heuristic0.0%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 0.5%Hindsight Bias0.0%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 1.2%Overconfidence Bias0.0%This article: 45.3%Elizabeth Dwoskin: 38.9%The Washington Post: 21.5%Framing Effect45.3%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 0.8%Loss Aversion0.0%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 0.9%Status Quo Bias0.0%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 0.1%Sunk Cost Effect0.0%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 3.6%Optimism Bias0.0%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 3.6%Pessimism Bias0.0%This article: 18.9%Elizabeth Dwoskin: 10.2%The Washington Post: 18.5%Negativity Bias18.9%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 1.5%Self-Serving Bias0.0%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 0.9%Fundamental Attribution Error0.0%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 0.1%Actor-Observer Bias0.0%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 2.2%In-Group Bias0.0%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 0.8%Out-Group Homogeneity Bias0.0%This article: 35.8%Elizabeth Dwoskin: 35.8%The Washington Post: 2.1%Halo Effect35.8%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 0.4%Horn Effect0.0%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 0.0%Dunning-Kruger Effect0.0%This article: 37.9%Elizabeth Dwoskin: 12.6%The Washington Post: 2.4%Recency Bias37.9%This article: 0.0%Elizabeth Dwoskin: 4.9%The Washington Post: 1.0%Primacy Effect0.0%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 0.0%Blind-Spot Bias0.0%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 0.9%Ad Hominem0.0%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 0.1%Straw Man0.0%This article: 73.7%Elizabeth Dwoskin: 49.1%The Washington Post: 5.2%Appeal to Authority73.7%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 1.5%False Dilemma0.0%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 1.0%Slippery Slope0.0%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 0.1%Circular Reasoning0.0%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 5.9%Hasty Generalization0.0%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 0.1%Red Herring0.0%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 0.5%Bandwagon0.0%This article: 11.6%Elizabeth Dwoskin: 7.7%The Washington Post: 6.3%Appeal to Emotion11.6%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 1.0%Begging the Question0.0%This article: 37.9%Elizabeth Dwoskin: 25.3%The Washington Post: 4.5%Post Hoc (False Cause)37.9%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 0.2%Tu Quoque0.0%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 0.6%Burden of Proof0.0%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 0.1%Appeal to Nature0.0%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 0.1%Composition/Division0.0%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 1.9%Anecdotal0.0%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 0.2%No True Scotsman0.0%This article: 7.4%Elizabeth Dwoskin: 2.5%The Washington Post: 2.7%Ambiguity (Equivocation)7.4%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 0.1%Middle Ground0.0%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 0.0%Personal Incredulity0.0%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 0.1%Special Pleading0.0%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 0.2%Genetic Fallacy0.0%This article: 37.9%Elizabeth Dwoskin: 12.6%The Washington Post: 4.8%Unattributed Quote37.9%This article: 37.9%Elizabeth Dwoskin: 12.6%The Washington Post: 2.5%Quote-first Misdirection37.9%This article: 54.7%Elizabeth Dwoskin: 41.4%The Washington Post: 15.2%Biased Writer Voice54.7%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 2.0%Indoctrination0.0%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 3.6%Politically Left Leaning Bias0.0%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 1.4%Politically Right Leaning Bias0.0%This article: 0.0%Elizabeth Dwoskin: 0.0%The Washington Post: 1.5%Attempt to Sell a Product or S…0.0%

95 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.