Deceivers hijack our trust in precision by attaching specific numbers (e.g., "13.5% of customers") to their claims. This gives a "patina of rigor and understanding," making us less likely to question the source or validity of the information itself, even if the number is arbitrary.

OpenAI has publicly acknowledged that the em-dash has become a "neon sign" for AI-generated text. They are updating their model to use it more sparingly, highlighting the subtle cues that distinguish human from machine writing and the ongoing effort to make AI outputs more natural and less detectable.

The absurd plots and bad grammar in phishing emails are a feature, not a bug. They efficiently screen out discerning individuals, ensuring that scammers only waste their time interacting with the recipients most likely to fall for the con from the outset.

When using LLMs to analyze unstructured data like interview transcripts, they often hallucinate compelling but non-existent quotes. To maintain integrity, always include a specific prompt instruction like "use quotes and cite your sources from the transcript for each quote." This forces the AI to ground its analysis in actual data.

In high-visibility roles, striving for perfect communication is counterproductive. Mistakes are inevitable. The key to credibility is not avoiding errors, but handling them with authenticity. This display of humanity makes a communicator more relatable and trustworthy than a polished but sterile delivery.

The human brain resists ambiguity and seeks closure. When a significant, factual event occurs but is followed by a lack of official information (often for legitimate investigative reasons), this creates an "open loop." People will naturally invent narratives to fill that void, giving rise to conspiracy theories.

The authenticity of digital evidence can be questioned by analyzing its language. When an alleged perpetrator, described as a 'terminally online zoomer,' uses dated, crime-drama jargon like 'squad car' and 'drop points,' it creates a linguistic mismatch that suggests the messages may be inauthentic or constructed to fit a specific narrative.

Biographer Ron Chernow learned more from John D. Rockefeller's intentionally vague letters than from direct revelations. The methods people use to conceal themselves—like writing as if every letter might be read by a prosecutor—are profoundly revealing of their personality, fears, and mindset.

A two-step analytical method to vet information: First, distinguish objective (multi-source, verifiable) facts from subjective (opinion-based) claims. Second, assess claims on a matrix of probability and source reliability. A low-reliability source making an improbable claim, like many conspiracy theories, should be considered highly unlikely.