AI Use Disclosure

AI tools assist with parts of the editorial workflow at Expected Value. Given the subject matter of this site, it would be a strange editorial stance to use AI tools and not say so. This disclosure explains what AI is and is not used for, so readers can decide how to weigh the content.

What AI is used for

• Research synthesis. Reading and summarising peer-reviewed papers, working papers from named academics, regulatory filings, and other primary sources. AI summaries are verified against the underlying source before any factual claim is made on the site.
• Drafting. Producing first drafts of explanatory passages, worked examples, FAQ entries, and historical context sections — always against a research brief and an evaluation framework set by the editor.
• Editing. Tightening prose, checking consistency, suggesting clearer structure.

What AI is not used for

• Doing the maths on its own. This is the most important rule on a probability-and-decision-making site. AI models routinely make arithmetic and probability errors that read as fluent prose. Every numerical claim, worked example, and probabilistic statement on this site is checked against a primary source or recomputed by the editor before publication. The AI is treated as a research assistant, not a calculator.
• Fabricating first-person experience. AI is not asked to write "I ran a Monte Carlo simulation of 10,000 trials" or "I tested this in my own portfolio" passages where no such activity occurred.
• Inventing data. AI is not asked to invent study sample sizes, p-values, effect sizes, or other quantitative claims. Every number on the site has a citable source.
• Generating fake testimonials or quotes. AI is never used to fabricate quotes from researchers, named academics, or readers. Where a quote appears, it is from a published source we can cite.
• Replacing the editor. Every published article is reviewed by a human editor for factual accuracy, numerical correctness, and policy compliance before publication. The site is not 100% AI-run — the human in the loop is real and is the one accountable for what appears here.

Verification

Where accuracy matters most — probabilities, p-values, sample sizes, effect sizes, attributed quotes, study findings, regulatory facts — claims are checked against primary sources and dated. If you spot a factual error, particularly a maths error, please flag it via the editorial policy page and we will correct it promptly.