Brainwaves as a Future-Resistant Biometric: Human-Detection, Identification, and Authorization

Brainwaves are the only biometric still untapped by governenments and corporations that possess fluid properties; Human-Detection, Identification, and Authorization. They are also a source of wealth.

“Human detection” is the act of proving whether or not an internet user is a robot, or a human. Google’s ReCaptcha2 (“I’m not a Robot”) is very convenient; It only takes about 10 seconds to complete. Unfortunately, the tasks required by Google’s reCaptcha are problematic for the following reasons:

  • These tasks are not future-proof. Eventually, A.I. will be smart enough to pass any image recognition task.
  • As Google trains their algorithms, they become the only ones with the algorithms capable of bypassing their own human detection protocols. They can then lease these algorithms to generate fake accounts. These fake accounts, paid for by a wealthy person or persons, or just a hacker, can be used to create a false sense of consensus on a discussion board regarding a government, product, or cultural content.

Project Oblio possesses a network component that is decidedly human-only. Transactions on this network can be decidedly human-only, as the network revolves around the idea that the most resilient form of human detection derives from the power of the human brain. Signals emanating from the brain and muscle areas around them are a cheap and efficient form of human detection, one that is vastly more future-proof that that currently implemented by Google.

Each of us is born with a multi-billion dollar supercomputer, capable of generating outputs immeasurably more complex than that capable of being understood by an A.I. For example, predicting whether a human will find something funny is much harder for A.I. than it would originally seem, even with plenty of data. This humor response manifests itself in an EEG recording, a piece of data that can simultaneously be conveniently monetized to the user on a decentralized network.  Common recording parameters like the P300 (a measure of whether a human brain has detected something “surprising”) are easily elicited over an EEG and probably just as difficult for a computer to simulate. Any form of human detection becomes significantly stronger when you’re simultaneously recording outputs from billions of live, biological neurons.

When we combine this type of human detection with transcranial direct current stimulation (tDCS: an “input” method, as opposed to EEG, which primarily records a brain’s output), we may get even stronger, faster human detection. Considering that tDCS has also been shown to improve memory, concentration, and relieve depression, it would seem to be the perfect technique for improving both inward and outward human communication.

Although non-invasive brain-machine-interfaces require a lot of data for most tasks we’d like them to be useful for (such as control of virtual reality), they are tremendously accurate at identifying us (like a “fingerprint”, but more accurate) with comparatively minimal data. While the more desirable tasks often have only 60-80% accuracy, identification of human beings by brainwaves can typically achieve 99% accuracy with minimal data. This is evidence that each brain and its corresponding outputs vary tremendously from person to person, and that collecting a lot of data from a single person is just as valuable, if not more valuable, than comparing data across persons. If you need more evidence for the uniqueness of human brains, check out the Human Connectome Project.

So. At this point we have two new terms: Human detection, and identification.It’s important now to realize that not only do human brains have tremendous power to human detect us, but they can simultaneously perform these two steps as well. No other biometric available can do this simultaneously, and it’s a crucial enhancement in a decentralized network’s stability. Fingerprints and DNA are both static – once you have the image or the code, it can be copied and used to impersonate you. Voice data is as fluid as brainwave data and could theoretically be used to human detect, but it is not as good at identifying you and is also (nowadays) easily forgable (see Alexa, Siri, etc.).  If data were easily foregable, a person could use the same data to receive multiple rewards, spamming the system and making themselves very rich (that is, until the markets crash due to the flaw they exposed in the network).

The last step in the three-pronged approach is authorization. While human detection is like reCaptcha, and identification is like a username, authorization is like a password. Authorization is as simple as you thinking a “password thought” recognized by a machine learning algorithm. There are tons of papers already out there about this, so I’ll point you to Google Scholar for this topic.

Combining these three methods: identification, authentication, and human detection, into a single protocol creates a triad of network security not found in other biometrics or in purely digital security. This is  interchangeably called “proof-of-person”, “proof-of-cognition”, “proof-of-humanity”, and “proof-of-individuality”. Its consequences are described further here.

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