Доверя́й, но проверя́й (Trust, but verify) Despite your well considered objections, we need to know that our computers are providing useful output at every le

Доверя́й, но проверя́й (Trust, but verify) Despite your well considered objections, we need to know that our computers are providing useful output at every level, especially at the highest levels which are once again being labeled AI. The concept applies all up and down the stack of systems and organizations: When we don't trust our memory devices, we add error correction. When we don't trust our conventional software, we add QA testing. When we don't trust future governing officials, we add checks and balances. When we don't trust other countries we add verification protocols. "Trusting AI" is not the ultimate oxymoron. It's just one more place we have to design systems to require as little verification as possible, and then provide the means to close the loop and allow verification of what remains. Trust in AI is big now because of the successes of non-symbolic processing. There's a real problem of understanding and explaining answers given by such systems. That the trust problem exists elsewhere is no reason to dismiss its importance here.