Data Wars Intro
Hello everyone, my name is Kristina Bruhahn and I am the CEO of Continuum Market.
I'm here today to tell you a little bit about what we refer to as the “Data Wars”.
In my opinion, the data wars kicked off the day that Mark Zuckerberg changed the name of his company from Facebook to Meta.
Metaverse in general, at Continuum Market, we refer to as a giant shopping mall. That means there's tons of transactions happening not just with the purchase with Fiat or Cryptocurrency, but also with the exchange of information and your data, your behavior.
The reason it's so important to care about your data is that companies all over the world make trillions of dollars off of your data.
This is very important to understand if we're going to move forward in the next decade under an own your data infrastructure which would require self sovereignty of your data and your assets and treating your data as an asset.
Why is this important? If we go all the way back to Cambridge Analytica scandal, they were working with something called Ocean data. This was millions of data points that allowed Facebook to put you in categories and predict your behavior. Now, it's very hard to predict a single human. But there have been ways that have been evolving for the last 15 years in order to do it. And some of these things are used in everyday Fortune 500 companies. Some of these things are used for big research companies and AI big data companies and some of these things are used for nefarious purposes.
A lot of these are used to sell you things. That's basically how the internet is currently set up is a great sticky way to identify who you are and how brands might sell you something.
Okay, so a bit about Ocean data. First of all, data and data prediction in terms of human behavior, you're looking for binary information, it either is or isn't. It's a yes. Or it's a no. If it's a maybe or a kinda, that's a yes. And it requires further explanation. So computers think in binary terms, and so they've taught AI to think in binary terms.
Now, it's very difficult to take a panel of 100 random people and ask them all the same question. You will get different results for different reasons, but if you're just looking for yes or no, it reveals a lot about how that person came to that decision.
For example, we'll pick a controversial one. If you asked 100 random people, “Can you still love someone if they have cheated on you?” Yes or No answers only.
You'll get only one of two answers. But the reasons for that answer are built within the human psyche, within our biases, within where we grow up and what our experiences are. Our education level, our emotional attachments, things bad that have happened to us things, good that have happened to us. And if you plot on the long enough timeline, you can start to predict will this type of person say “No”, in this scenario, and so you can start to create kind of like painting with a big brush.
These concepts that indicate human behavior.
Now AI is already sophisticated enough to pick up on all that. And through all of these giant tech companies working together with all these data points, they've gotten pretty sophisticated. I need a better word than sophisticated here. In all of its grandeur, it's pretty impressive.
But it's scary to think that so many people out there know these things that you consider are personal to yourself, that are personal to your kids, that are personal to your family members.
That have no place being in someone's database.
And they know a lot of these things from the websites that you search; from the people that you interact with on social media; from the things that you watch on YouTube, from the things that you say in front of your Alexa machine. And from these great little geo tracking devices called our cell phones.
There's so much of data surrounding everyday human beings and their interactions that you can kind of assume someone is listening all the time.
So, someone's listening all the time. Where does that information get stored? It gets stored in centralized databases of the companies that are collecting this information. And they're running sophisticated algorithms on it to pinpoint exactly when they can get in front of you when you might make a purchase decision.
I know this because I helped fortune 500 build systems just like that.
Not everyone cares if their data is being used this way. Not everyone cares that these companies are making trillions of dollars off of it.
Not everyone cares that there can be and there is a better way but it will take lots of collective education around the world in order for us to live in this new data privacy world.
Having a roadmap to help educate baselines leads humanity to a “educational same spot” where we feel collectively enough about financial topics to change policies and push back on the systemic injustices that are happening with our data.
Let’s build a Web3 World.
~DataPoints
