AI-washing is everywhere. Here’s a dev’s quick guide to spotting it and avoiding hype over real impact.
Red Flags to Demand Proof
Red Flag #1: They Can't Explain the "How" — If a vendor uses vague terms like "intelligent algorithms" and won’t name whether they use NLP topic modeling, a forecasting model, or a simple heuristic, it’s a red flag. Real AI uses concrete methods. [1]
Red Flag #2: They Pitch Features, Not Outcomes — A demo full of flashy AI features but no measurable impact (latency, error rate, conversion) signals tech-for-tech’s-sake. [1]
Red Flag #3: The "Magic Black Box" Defense — Answers like "it’s proprietary" or "it just works" undermine governance. A solid vendor can discuss training and explainability. [1]
Red Flag #4: The "AI Island" Architecture — No robust integration strategy leads to data silos. AI should feed core workflows via documented APIs. [1]
Red Flag #5: They Have No Real-World Proof — Grand marketing claims require detailed case studies with measurable results from similar-scale companies. [1]
Beyond buzz, look for real capability signals:
Token prediction ≠ reasoning — LLMs excel at fluency, not guaranteed truth; demand checks on logic and arithmetic. [2]
Symbol-grounding and measurement — Numbers are symbols; look for grounding or external calculators, or retrieval augmentation. [2]
Closing thought: Demand proof, transparency, and tangible outcomes, not slogans.
References
"AI-Powered" Is a Red Flag. Here's a Dev's Guide to Calling Bullshit
Dev guide to spotting AI-washing; flags include opaque how, outcomes, black box, architecture, real proofs vendor claims and measurable results
View sourceThe Illusion of Intelligence: Structural Flaws in Large Language Models
Post argues LLMs lack true reasoning, grounding, and measurement integrity; contrasts with expert systems; discusses market motives and hybrid approaches
View source