An Artificial Intelligence Browser Architecture (AIBA) For Our Kind and Others: A Voice Name System Speech implementation with two warrants, Wake Neutrality and Value Preservation of Personally Identifiable Information
Brian Subirana

TL;DR
This paper introduces a novel AI browser architecture called AIBA that enables privacy-preserving, wake-neutral collection of speech and other data types for health and environmental applications, addressing limitations of current closed systems.
Contribution
We propose a new voice browser-server architecture that ensures wake neutrality and PII value preservation, with successful implementation collecting COVID-19 cough samples.
Findings
Captured over 200,000 COVID-19 cough samples
Demonstrated wake neutrality in speech data collection
Architecture adaptable to multiple data modalities and domains
Abstract
Conversational commerce, first pioneered by Apple's Siri, is the first of may applications based on always-on artificial intelligence systems that decide on its own when to interact with the environment, potentially collecting 24x7 longitudinal training data that is often Personally Identifiable Information (PII). A large body of scholarly papers, on the order of a million according to a simple Google Scholar search, suggests that the treatment of many health conditions, including COVID-19 and dementia, can be vastly improved by this data if the dataset is large enough as it has happened in other domains (e.g. GPT3). In contrast, current dominant systems are closed garden solutions without wake neutrality and that can't fully exploit the PII data they have because of IRB and Cohues-type constraints. We present a voice browser-and-server architecture that aims to address these two…
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Taxonomy
TopicsCOVID-19 diagnosis using AI
