AI ETHICS AND REGULATION
creates targets that attackers can’ t resist:“ This ends up with a big bullseye that somebody’ s going to try to hit,” he says.
IBM research highlights that AI systems hoover up vast amounts of data to function properly.
Terabytes or petabytes of text, images or video routinely get swept into training datasets, and inevitably some carry real sensitivity – healthcare information, social media data, financial records and biometric data for facial recognition.
The mathematics works against security teams. More data means more surface area for attacks – and the odds keep tilting towards eventual exposure.
Jennifer King, a fellow at the Stanford University Institute for Human-Centered Artificial Intelligence, points out how public attitudes have shifted:“ Ten years ago, most people thought about data privacy in terms of online shopping,” she explains.
“ But now we’ ve seen companies shift to this ubiquitous data collection that trains AI systems, which can have a major impact across society, especially our civil rights.”
George Zhao, former CEO of Honor, adds:“ Without data security and user privacy protection, AI becomes useless.
“ This has always been one of our valuable propositions. We say that user data does not leave the device. This is a principle we adhere to.”
144 December 2025