“Ambient contextuality hinges on the idea that there is information hidden all around us that helps clarify our intent in any given conversation. Answering the simple questions of who, what, where and when is now easier than ever as IoT continues to mine and mind the data of our lives. I once sketched out a derivative needs pyramid for IoT devices using the example of Maslow’s hierarchy of needs pyramid to chart a course for “thing-actualization”, whereby our technology could use analytics, learned logic and predictive behavior to establish groups and networks of things and enable other more “complex” things. The voice interfaces and natural-language processing technology on display in interactive speakers such as Amazon’s Alexa or Apple’s Homepod are examples of this actualization in action – predictive analytics and machine learning imbued into objects and interfaces to technology that collect data and collectively power progressively complex functions, often in real time.
But it is still not conversation. There is a new, nascent communications triangle between people, processes and things that fuels usability, and it still has a bit of its own growing up to do.
Deeper questions like how and why are also key to conversation for humans.”
Hunter points out privacy issues with devices that constantly collect information about us, but concludes that “the challenge now is to make our machines ‘speak’ human – to imbue them with context and inference and informality so that conversation flows naturally.”