Why Would Google’s Artificial Intelligence Director Leave for Apple? The Race for NLP, 3rd-Party Audio Dark Metadata Privacy Concerns, the May 25th Implementation of GDPR, and Apple’s HAL Zach Edwards Follow May 8, 2018 · 25 min read

Apple, Google and Amazon are currently locked in an epic quest over the following multi-trillion dollar question: which company will be the first to maintain 99% accuracy for speech recognition from Natural Language Processing (NLP) in any and every scenario and context, for every language, dialect and slang?

Google AI vs Apple AI vs Amazon AI

Beyond just accurate intent and entity matching, there is another race in speech recognition — the race to organize and categorize audio dark metadata.

There are rarely discussed consequences of audio dark metadata for the privacy of 3rd parties who haven’t agreed to the Terms of Service of the company providing the audio processing — the un-agreed person standing on the train talking near a person dictating into a Google Assistant-powered app, or the co-worker talking about business as someone nearby asks Siri for directions to an after-work dinner, and many other potential scenarios.

There is a huge value for a business to acquiring and analyze dark audio metadata, and it’s important for the public and governing bodies to understand their value.

The winner of the speech recognition race will be the company that not only perfects their segmented NLP models, but also the one that does it under the legal, ethical and social norms required in the marketplace.

Apple appears to have a dominant position with their rarely-reported-on Hardware Abstraction Layer (“HAL”) architecture which attempts to process and provide some layer of anonymization directly on their devices before the data is stored. In contrast, Google, Amazon Microsoft and other companies appear to currently skip the on-device anonymizing step. Instead, their public statements and developer documents indicate that their audio Natural Language Processing (“NLP”) tools send all recorded audio to their servers, store it, and then don’t take additional steps to remove private 3rd party audio.

Indeed on Google, Amazon and Microsoft’s websites explaining their speech to text software, they make no mention of third party privacy rights or 3rd party audio dark metadata protection at all. Whether these companies have some work around for filtering and protecting third party metadata once on their server, remains to be seen.

What is abundantly clear, however, is that on May 25, 2018, the EU’s General Data Protection Regulation (GDPR) becomes effective, and creates a whole potential universe of additional liability with regard to the collection of third party audio dark metadata. Though most in the tech world have focused on first party data retention policies (terms of use, individual user privacy rights, enforceability of privacy agreements), protecting third party audio dark metadata — that is, data collected and recorded from people and things who are not the first party users of the speech device — marks the new frontier in privacy. With new regulations and privacy concerns growing daily, the ultimate winner of the speech recognition race will not only be the one who makes it to 99% recognition the fastest, but the company who successfully does this while also protecting the metadata of first and third party users.

Time is of the essence, due to GDPR going into effect on May 25th, 2018, and if a company doesn’t comply, the EU’s GDPR clearly states, “those organizations in non-compliance may face heavy fines.” The formula to determine GDPR fines could cost American businesses potentially hundreds of millions or billions of dollars, and as of publishing this article, there will be less than 3 weeks before the law goes into full effect.

If 3rd party audio dark metadata rights are included under GDPR, many companies need to make significant changes to their speech recognition NLP systems in a short period of time.