How the digital giants are colonizing our homes

This is the new battle for the human interface.

[Originally written for IEEE, modified here.]

There’s something about human nature that often fails to see the future when it arrives. The big, exciting, and scary scenarios lumbering on the horizon become practical and even banal once they’re wrapped around us. Right now we’re talking to objects in our homes that recognize our voices, understand our questions, model our behaviors, and even predict our needs while communicating across vast networks of machines, computers, and distant humans. This is made possible by global supply chains optimized to produce the supercomputers we keep in our pockets, and by the most valuable companies on the planet advancing software into the new wave of artificial intelligence.

Amazon has shipped almost 20 million Echo devices, the connected appliance that holds their personal learning system, Alexa. Apple announced HomePod, a similar device that includes their AI Siri. Google Home delivers Assistant and Microsoft has partnered with Harman Kardon to bring Cortana to the living room. Samsung just announced its Bixby assistant will move to the core of its connected products, and it’s rumored that Facebook will introduce a similar hardware offering.

Right now we’re talking to objects in our homes that recognize our voices, understand our questions, model our behaviors, and even predict our needs.

This is the new battle for the human interface. From the web to smartphone apps and now into the living room, the largest players are following us and vying to capture our every request. Search queries, entertainment, appliance commands, appointments and purchases — the digital giants are trying to remove as much friction as possible between our wallets, our data, and their servers. In doing so, they’re weaving their ecosystems through everything we do.

Amazon has a first-mover advantage with a litany of partners integrating Alexa. Aside from standards like Spotify, Philips Hue, and August locks, they’ve announced notable partnerships with Mercedes Benz and BMW. Very soon, you can ask Alexa in your bedroom to tell your new Mercedes in the garage to turn on its heater and set the navigation from your next calendar appointment. This is just one example of the many ways these platforms are spreading across the networks that are increasingly penetrating so much our lives.

We’re shifting into a world of pervasive measurement.

Google would like your login to follow you everywhere — across Chrome, Gmail, Android, Android Auto, OnHub routers, Google Home, and any number of partner touchpoints. Your Apple ID is beginning to know what you look like, how your voice sounds, and who and what you commonly interact with. Behind Alexa is a rich model of our behaviors and affinities that can be used to predict demand for goods. Nest Cam (Alphabet) uses facial recognition to know who’s at the door or in the living room and to provision them with access, personalized media, lighting, and heating. Machine vision is now able to classify our emotions, like Disney’s efforts to better understand audience reactions to their films.

All of these solutions arise from the convergence of cheap sensing, connectivity, computation, and machine intelligence. All of them rely on a high-resolution model of our behaviors.

The offer is convenience and efficiency in exchange for a self-imposed corporate surveillance.

Data really is the new oil, illustrated by the simple fact that the world’s most valuable businesses are no longer energy companies. They’re data companies. We’re shifting into a world of pervasive measurement, always listening and watching, building more sophisticated models of each of us. In the near future, we may be identified everywhere we go, and even predicted to be there. We’re now socializing with machine intelligences that are becoming more and more human-like. Soon, they’ll be with us everywhere we go, in our devices, in our homes and cars, and finding us in the physical world wherever we brush up against their networks.

The benefits might be enormous if our homes are more sensitive and responsive to activity and environmental conditions. Energy and resource footprints could be optimized when each room knows if its empty, adjusting lighting and A/C accordingly. Solutions like Neurio could integrate with renewable power systems and weather forecasts to predict demand. The intelligent home could understand our moods, our anxiety, and our wellness and then modify ambience, prescribe exercise, and predict illness. ClinicAI is building toilets with biosensors and machine learning to identify early signs of diseases like colon cancer.

So far, the arc of AI has often been confounding and unexpected.

All of this relies on our willingness to allow our lives to be continuously observed and evaluated by unseen third-parties. The offer is convenience and efficiency in exchange for a self-imposed corporate surveillance. Even now there are regulatory discussions heating up about such intrusions, about data rights and security. Apple has been positioning itself as the safe and private option, trying to keep all data collection and processing in our hands rather than its cloud. This sets up a more difficult dynamic: those who can afford it, get to have convenience, efficiency, and privacy. The rest of us get access to the cheap seats in exchange for giving up the minutia of our lives.

There are always trade-offs with our inventions. Most tools can become weapons. The arc of human progress is driven by finding better solutions and then dealing with their unanticipated consequences. Yet, so far, the arc of AI has often been confounding and unexpected.

How might we be shaped by machine intelligence that sees more of the world than we do?

When a masked online Go player with a 60–0 victory streak recently revealed itself to be a new version of DeepMind’s AlphaGo, Go master Ke Jie wrote that “after humanity spent thousands of years improving our tactics, computers tell us that humans are completely wrong.” World grandmaster Lee Sedol, after his own historic defeat by AlphaGo, adjusted his play based on what he learned from his digital opponent.

We’re quite malleable to digital systems — think of how we now enter search queries or modify our speech in txt. How might we be shaped by machine intelligence that sees more of the world than we do?

As we undergo this unprecedented transition into a connected and computational world increasingly rich with its own type of inhuman intelligence, it’s imperative that we do so with both a keen analysis of the present and a critical eye towards the future. Otherwise, our exponential technologies will likely bring along exponential challenges.

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