#statistics-misrepresentation

#statistics-misrepresentation

Google AI mode has added an 'Ask about this' option above the sources where all URLs are displayed. Clicking on 'Ask about' here automatically pulled a new prompt into the search box.

Organizations are drowning in dashboards, KPIs, performance metrics, behavioral traces, biometric indicators, predictive scores, engagement rates, and AI-generated forecasts. We have more data than we know what to do with. We pretend that the mere presence of data guarantees clarity. It does not. That's data hubris—the arrogant belief that because something can be measured, it can be mastered.

Google disabled specific queries, such as "what is the normal range for liver blood tests," after experts contacted by The Guardian flagged the results as dangerous. The report also highlighted a critical error regarding pancreatic cancer: The AI suggested patients avoid high-fat foods, a recommendation that contradicts standard medical guidance to maintain weight and could jeopardize patient health. Despite these findings, Google only deactivated the summaries for the liver test queries, leaving other potentially harmful answers accessible.

Some clinicians have an uncanny quality. A colleague describes herself and others with this instinct as "witchy"-a capacity to know things about patients they haven't said yet, to follow a stray association to a song lyric or a half-remembered cultural reference and arrive, reliably, at something the patient urgently needed to say but couldn't reach on their own. We see with artificial intelligence these intriguing possibilities for discovery, especially as connections that human beings never would see pop out of apparently unrelated data.

Large language models (LLMs) base their predictions on training data and cannot respond effectively to queries about other data. The AI industry has dealt with that limitation through a process called retrieval-augmented generation (RAG), which gives LLMs access to external datasets. Google's AI Overviews in Search, for example, use RAG to provide the underlying Gemini model with current, though not necessarily accurate, web data.

Before enterprises can deploy AI agents that actually work, they need something most organizations don't have: a single, authoritative source of truth.

Three scientists have coined a rather scatological, yet revealing, term: PISS, short for Published In Support of Self. The acronym defines a disconcerting phenomenon. Specialized scientific journals that were once published every two weeks or weekly now churn out special issues every few hours. Previously, these monographs were selective and entrusted to a leading figure in a scientific discipline. Now, even the most mediocre researchers receive a flood of invitations to edit one of these countless special issues, which have become a multi-million dollar business.

On October 1, 2022, something strange happened in the Philippines: 433 people won the jackpot in the local lottery. For this particular lotto, six numbers ranging in value from 1 to 55 were randomly selected, and the 433 winners all matched. Even more bizarre, when arranged in ascending order, the winning numbers were: 9, 18, 27, 36, 45 and 54. In other words, the winning numbers were multiples of 9 (9 1, 9 2, 9 3, etcetera).

Most days, an email lands in my inbox with the promise to amplify my growth-my newsletter subscribers, the reach of my podcasts, the number of client leads, etc. I've gotten used to random people pitching me on their services, and some of the messages expertly prey on my insecurities as a business owner ("you're leaving so much on the table," et al.). I never answer any of them, but I sometimes wonder which ones might actually be legit.