CLEAR Protocol is not your typical Silicon Valley company.
In Data Protection and Privacy we are light years ahead of the industry. Let us go through how user Data Security and Privacy Management has evolved, and where we are heading.
Under my Garage Ping Pong table
The first Silicon Valley entrepreneurs couldn’t believe their ideas became reality. The whole industry was still in 'proof of concept mode'. Who could even foresee that user data would be an issue. As data accumulated, they just kept it in a server in their garage.
How do we monetize?
This was a critical stage in Silicon Valley business models. Now that 'Proof of Concept' has been demonstrated, the question became how to monetize it . The vanilla play was 'let Venture Capitals finance you until you reach critical mass, and then monetize on user's data'. This strategy believes users are willing to exchange their data to get convenience, and once a critical mass level is reached, that meta-data becomes the server's real asset.
Remember that scene in 'The Social Network' when Eduardo Savarin goes to Madison Avenue to sell 'advertising' and Zuckerberg tells him 'he wants to end the party at 11'; although that’s probably over-dramatization, the debate was live and well until Venture Capitals accepted data was the real asset to trade for their investment.
Amazon Web Services – "Pay As You Go"
Once data was accepted to be the true commodity in Silicon Valley, the question then became where to store it. Building servers for every new startup was costly, time consuming, and labor intensive.
Amazon was the real pioneer when it came to user data. It was the first to make it out of the 2000’s in one piece, and one of the first to experience a glut of user data. The invention of AWS, or a spinoff of homegrown outsourced remote servers in the ‘cloud’, was hailed as an innovation in numerous conferences around the world.
New startups no longer had to reinvent the wheel and build their own server-farms, they could simply pay only for what they used. This drove ridiculous amount of traffic to AWS, with profits margins of 25-30%.
AWS led the way to the talk of the ‘Cloud’, VMware was next with Virtualization. This lead to the birth of a new industry of data custodians that allowed you to outsource maintenance, real estate space, noise reduction, cooling, and most importantly security of data from hackers. Think about it this way: AWS, Azure, Google Cloud, and the others, are essentially 'data bankers'.
General Data Protection Regulation (GDPR) 1000 steps forward, 1 step back
Fast forward to today, and GDPR is official. Data brokers lurking in the shadows, moving copious amounts of meta data back and forth. Identity theft, numerous hacks of significant scales, leaks, and other machinations all have caused regulators to take action. 'Everyone has to behave' and so GDPR goes through the EU. Zuckerberg testifies in front of senate, and the industry takes a step back.
Governments are, by definition of their mandate, lagging and reactionary to industry. Governments cannot legislate the future, they must wait for industry to catch up to them, and then stop abuses. So what if it took 20 years?
The problem is that after the industry has spent 20 years moving forward in the speed of light, monetizing and dissecting its users. We're to the point where Facebook has more data on its users in its shadow files than East German secret police had on its citizen. GDPR is really a drop in the bucket; too little, too late.
Hulu Model vs Netflix Model
In the debate over monetization, new approaches came to life: Hulu lets you choose: “Either you pay or your data will pay for you”.
In this approach commercials target users using their location, history, preferences and other data, Or, if you pay another $3/month, we will not pray on you.
Netflix is a pioneer in the tech space as well. Potentially because of its victorious rivalry with BlockBuster, the history of the mail-in DVD, and its straight forward model: no commercials, binge all you can, and a revenue model of recurring mothly subscriptions only. The only way Netflix uses it's client's data is to improve its product.
We also see a similar tendency towards this model in the journalism industry. In the early 2000's content was free and abundant. Fast forward 20 years, and the industry has pretty much agreed that the only way to survive is to move towards pay walls, subscriptions, and other recurring revenue models.
The CLEAR Protocol Model
The Clear model solution is unique, because unlike the typical Silicon Valley company:
We do not want your data
We do not want to mine your data
We do not want to store your data
We do not want to own your data
We want to connect the market under a unified protocol, a standardized railway everyone can sync to, and yes, we also believe in service. Automating process with artificial intelligence will get you 3/4 of the way, the remainder is done by fixing a broker process.
How does CLEAR accomplish that? We build a container, a set of instructions with our software. We then place it in a server the user controls and hosts: this can be under your desk, on the cloud, in a remote island, you name it. We then 'divorce' CLEAR from user data. In other words imprison the data in a lock-box which the user owns, and works only for the user. There is no third party affiliates, no data sharing agreements, nothing. We serve one agenda – that of our customer.
Zero Knowledge Proofs
There is a higher level of privacy – zero knowledge proofs. Here, two protocols communicate with one another to verify and approve certain functions. The key advance is that they can communicate and verify without knowing key data that is otherwise exchanged in current commercial settings.
This is the dream, it is ideal, but the problem is that the infrastructure, both technological and legal, has not yet matured enough for a wide scale adoption. This is still in 'proof of concept mode' and we are eagerly following its development.