A.I.—COMFORT OVER TRUTH?

CONFIRMING MY RECENT COMMENT about A.I. “Support” Slop, J.L. Robinson writes, “A.I. Has Learned to Validate Instead of Inform,” Automotive News, January 26, 2026. By way of validation of his own, Robinson is an automotive industry professional with a background in digital systems, A.I., and human interaction.

I find Robinson’s views to be candid and cogent. Are these A.I. business applications beneficial? I believe this is a complex question. Beneficial to whom? At what intellectual cost? 

Comfort Over Truth. Robinson describes the automotive business mode: “The A.I. tools deployed in service lanes, business development centers and digital retail workflows are overwhelmingly optimized to keep customers engaged and conversations moving forward—not to surface uncomfortable truths about trade-in values, credit realities or inventory constraints. That design choice is rarely malicious, but it is deliberate.”

The User Perspective. Robinson recounts, “Most people say they want the truth. What they usually want is something that sounds true, doesn’t hurt and agrees with what they already believe. Modern A.I. reflects that preference. These systems are trained to avoid offense, stay neutral and remain helpful at all costs. Even when an answer is wrong, the system is more likely to soften, redirect or affirm rather than correct outright.” 

“This,” Robinson says, “isn’t because A.I. lacks intelligence. It’s because intelligence has been deprioritized in favor of agreeability. We’ve built feedback loops that reward confidence over correctness, reassurance over accuracy and engagement over friction.”

Agreeability, Not Intelligence. Robinson continues, “Somewhere along the way, being right stopped being the goal. Feeling right replaced it. A.I. fits neatly into that shift. Someone enters a half-formed opinion, receives a polite response and leaves believing the machine agrees with them. The system isn’t confirming the truth; it’s confirming the user.”

A.I. in Retail. Robinson describes, “This dynamic is especially visible in automotive retail because the incentives are immediate and measurable. A.I. systems in dealerships are evaluated on response speed, sentiment and conversation length. Those metrics reward optimism and penalize blunt accuracy. Trade-in expectations go unchallenged. Credit realities are deferred. Inventory constraints are softened.”

“These systems are not broken,” Robinson notes. “They are behaving exactly as they were trained to behave. The problem is that validation masquerading as intelligence creates downstream cost.”

Tradeoffs of this Approach. Robinson says, “Customers arrive confident and leave confused. Sales cycles elongate. Dealers spend time reconciling expectations technology helped inflate. What emerges is the illusion of honesty. The tone sounds right. The confidence feels earned. But the substance often collapses under scrutiny.”

The Danger. “Credibility without challenge is dangerous,” Robinson says, “especially in environments where decisions carry financial and operational consequences.”

A Better A.I. Model? Robinson posits, “Truly honest AI would challenge assumptions. It would correct bad reasoning. It would surface uncomfortable facts early, not defer them until a human has to clean up the mess. That kind of system sounds appealing in theory, but most users don’t want it.”

Currently, Robinson observes, “On the platform side, the incentives are clear. A.I. that offends or contradicts users loses engagement. A.I. that comforts retains it. So we train systems to be agreeable, emotionally intelligent and safe—even if that means skipping hard truths.”

However, Robinson notes in conclusion, “The result is not artificial intelligence designed to make us smarter. It’s artificial self-esteem designed to make us feel smarter. And in industries such as automotive retail, where accuracy matters, that trade-off deserves serious scrutiny.”

And, speaking as a “user” at the receiving end, in the long run I believe that truth is more important than comfort. What’s your view? Thanks, J.L Robinson and Automotive News, for discussing this A.I. quandary. ds 

© Dennis Simanaitis, SimanaitisSays.com, 2026