INSIGHTS, FLOWS & INVESTMENT TRENDS
AI Is Not Human. Stop Describing It That Way.
We don’t say a dog “lied” or a cat “hates” the mouse it catches. We reserve those words for human intent.
With AI, that discipline has disappeared.
Executives, media, and users now describe models as if they understand, decide, and learn. They don’t. These systems generate outputs from statistical patterns in data—without context, perspective, or awareness. The language is convenient. It’s also wrong. AI only operates based upon historical data.
The vocabulary isn’t semantics; it shapes how these systems are trusted and where they’re applied.
| Human Terms used for AI: | AI Is: |
| Understands | Matching patterns — no comprehension |
| Decides | Selecting probabilities — no judgment |
| Knows | Reflecting training data — no verification |
| Learns | Running on fixed weights — no update from interactions |
| Lied | Producing a mistake — no intent |
In investment workflows, it’s important to not be misled by the humanizing vocabulary and use AI for what it can do. AI is highly effective when the task is bound, pattern-based and a calculation is the answer:
- Screening large datasets
- Identifying statistical anomalies
- Structuring and extracting information
Humans are best and need to be relied upon where outcomes depend on judgment, context, experience, or what isn’t in the data.
The decision—and the accountability—are still the responsibility of the human.
Listen to the Podcast to learn more
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