Ambient Intelligence

The most likely ways in which ambient intelligence will capture public space is via security and economic surveillance. Police forces will seek as much data on those inhabiting public spaces in the name of predicting and preventing crime or disorder. The Chinese social credit system is one possible dystopian endpoint. Companies will want similarly voluminous data from which to build consumer profiles and generate means through which to nudge us toward their doors.
Smart technologies, and the Internet of Things (IoT), are contemporary instances of ambient intelligence. In the late 1990s Philips and Palo Alto Ventures came up with this idea to characterise a future in which technologies invisibly interact with and adapt to human needs. This version of techno-utopianism included technologies that anticipate what we might want and act autonomously to curate the environment around us. Ambient intelligence would be a way for human environments to be optimised for us in terms of what we want. But they also make otherwise predictable elements of outward reality unpredictable.
We ought to protect the shared interests we have in public spaces. Systems hoping to profit from our general living should not get much priority. If we cut out the data streams that would furnish these systems, we could cut out the incentive to deploy them at all.
As long as someone is snapping a selfie and putting it on the web, the scene they capture is a technological interface. It’s a source of data for open-ended processing. Clearview AI allowed any customer to scrape internet picture archives, using facial recognition technology. This could in principle supply a visual record of anyone’s presence in any location, at any time, as long as they were present in a photo. The advantages of such latent records of activity stay with unaccountable groups, such as security forces or those leading tech companies. Only the risks remain public.
The varieties of sensor data and processing applications are not yet wholly integrated with one another. But this snapshot suggests the way in which one form of ubiquitous ambient intelligence is emerging. This sort of data recording and synthesis allows unprecedented quantification of social environments and the people in them. But the techno-utopian aim of optimising reality for human desires is missing. The data collection is happening, but no rationale has emerged.
An unfortunate socio-political preoccupation with security, and an unguided technological turn toward powerful handheld devices, has resulted in ambient intelligent sensor networks logging a great deal of what we do. Our phones collect and share all manner of data with anonymous databases all over the place. Smart objects, a class of technology-enabled devices that include sensors and artificial intelligence, use data to react to or predict user preferences. There are also applications in marketing, such as smart billboards, whose aim is to read physical characteristics of those passing by in order to tailor advertising to them.
In terms of personal data, device-based processing would (literally) put control back in users’ hands. In terms of social imaging, this would be a good way to update outdated photography laws. Current UK legislation widely permits photography in public spaces. But such lack of regulation was written for times of physical photographic media, film, chemical processing, and private picture ownership. Now, take a walk past the Bodleian Library or through Trafalgar Square and you’re likely to appear in hundreds of pictures, and a fair few live video streams. A far cry from holiday snaps of old, likely to go largely unseen in albums.
Written by Stephen Rainey
An excitingly futuristic world of seamless interaction with computers! A cybernetic environment that delivers what I want, when I want it! Or: A world of built on vampiric databases, fed on myopic accounts of movements and preferences, loosely related to persons. Each is a possibility given ubiquitous ambient intelligence.
We may find ways to cope with environments that actively scan us, or that inform on our movements and habits to anonymous databases. But these intrusions on our freedom are nonetheless difficult to justify. For one thing, in the case of data monetised for corporate gain, our very being around is objectified, commodified, and enriching for a few. It’s strangely grotesque. And it can’t be resisted in the same way facial recognition might be, through wearing masks to baffle cameras. Such rent-seeking is based on our mere presence. To resist is to accept alienation from the space as the price.
Two initial steps in resisting this would be (a) to point ambient intelligent data processing toward user-devices, away from cloud databases, and (b) to geo-fence public spaces from social media imaging. With these data removed from wider databases and corporate interests, the security and market value of their collection would be diminished.
In all cases, sensors are deployed to record the environment, process the data derived from the recording, and select features relevant for some application. As these sensor networks include our phones, the public at large is both being monitored and providing the sensors. As data is amassed upon our movements and activities, it becomes increasingly valuable to those with the capacity to crunch the numbers.
The smooth-functioning of security and economic systems ought to be predicated on how they interact with and account for the wider social world they serve. Ambient intelligence gets things backward.