Why AI hardware needs privacy built in from the start

As artificial intelligence moves into devices that can see, hear and interpret the world, privacy is becoming a product-design question. TechRadar’s Will Wang argues that teams should consider it from the start, rather than trying to address concerns after launch.

Wang points to smart glasses as a clear example. Cameras can give an AI system visual context, but glasses are used around people who may not know whether recording or data processing is taking place. Those nearby have less information about a device’s activity than the person wearing it.

Design decisions made early can shape what information a device collects, how it processes that information and whether it retains or sends data to the cloud. Wang says product teams should ask what information a device needs for its core function, whether processing can happen locally, whether data can be deleted after a task and whether sensors need to stay active continuously.

Those choices can limit some capabilities, but Wang argues that the most capable product is not always the one people feel comfortable using in daily life. Privacy, he writes, belongs in the same discussions as sensors, computing, storage and essential features. Waiting until launch can leave important decisions already locked into the product.

The source article ends mid-sentence while discussing wearable technology, so it does not provide the rest of Wang’s conclusion.