Filtering News Noise: Michael Hiltzik on Investor Trust and Source Credibility

Navigating Information Overload

• 💡 Investors are drowning in a flood of noisy news, including outrageous, algorithm-driven clickbait from social media, TV, and radio.
• 🧠 The traditional skill of assessing information based on worldview and reality is now more important than ever.

Evaluating News Sources

• 🔍 Always assess the source of information; trade organizations are essentially PR arms and will spin data.
• ⚠️ Be skeptical of studies cited by trade organizations; inquire about who commissioned the study.
• 📚 Reporters are often overworked and may simply parroting press releases; intelligent investors should go to the raw material to make their own judgments.

Identifying Trustworthy Sources

• ✅ Trustworthy economic sources have demonstrated integrity in data interpretation over time.
• 📊 Factor in a source's ideology, funders, and history to assess its information.
• 📈 Some reports are quickly refuted, and sources compile a record of inaccuracy or reliability; paying attention takes time and effort.

Anecdotes vs. Data

• 📌 Be wary of anecdotes and one-off stories (N=1); they are not data series and can be misleading.
• 🗣️ "Man on the street" interviews can be unreliable unless the subject is in a position to know the answers and the questions are narrow.
• 🧐 Compare what you read to your own experience; if it's at odds, that's an important signal.

Social Media and AI Risks

• 🚫 Mainstream media stories relying on social media sourcing are very suspect.
• 🐦 While X (formerly Twitter) can be curated, it's increasingly difficult to filter out noise.
• 🤖 The speaker is an AI skeptic, viewing many AI claims as marketing; current AI creations often have giveaways like unusual language or images.
• ⚠️ Relying on AI for news is a risk, and the industry's AI craze is likely to lead to problems.