GLIAnet FAQ Series, Part Two

 

Q.  In your talk at SXSW, you touched on some emerging technologies that will further deepen this unfortunate trust and accountability gap in the Web.  Can you go into a bit more detail?

A.  Sure  For starters, it’s a truism that all technologies are tools, which can be used in a variety of ways.  

When they are embedded into the current “MOPs” ecosystems, these tools become subject to the same Web inputs, Net effects, and Platform dynamics I mentioned previously.

As it turns out, a host of cutting-edge technologies are being introduced, intended to become another set of tools to collect and control my data.  And once the tech is established, we may be less able to break free from the dominant Platform-User paradigm. Some of these technologies are already here, but just becoming more effective and pervasive.  These include:

  • Maturation of Big Data: more sophisticated tools employed by data brokers, for data profiling and inferencing

  • Cloud computing: massive data processing and storage capabilities, sitting on server farms worldwide

  • AI algorithms: machines programmed by others, so they can constantly learn, adapt, evolve, and decide -- for us.

Other more advanced tech is being deployed as we speak.

  • Internet of Things: billions of devices and sensors, from fixed cameras to drones, everywhere in our physical environment.

  • Biometrics: are those technologies that measure and analyze our bodies and behavior and even our bearing -- facial recognition, voice recognition, iris scans, gait analysis, brain waves, DNA, and heartbeats.  When layered on top of IoT, biometrics will give others a far deeper understanding of our emotions, thoughts, and desires;

  • Augmented reality: as Kevin Kelly notes in a Wired cover story, a completely immersive mirrorworld, with every atom linked to a corresponding bit; Kelly calls it a “total surveillance state.”

  • Quantum computing: all our bits will be processed thousands of times faster, and basic encryption protocols may become useless.

Taken together, these technologies will give some companies a near total profile of you and your world.  And use it to their financial advantage.

Imagine, for example, a platform using facial recognition technology to analyze your emotions, and learning that when you are feeling sad you are prone to impulse purchases of expensive items—clothes, liquor, what have you. Then, the next time their sensors detect sadness in you, the algorithms will ply you with ads for that really pricey blazer you like—and maybe, at the same time, raise the price.

The point is—unless something changes, none of this tech will be within the end users’ direct control.  What can we do, if anything? We should build alternative ecosystems that put people in charge.  We need to democratize tech.

Richard Whitt