Here at Canopy, we pay a lot of attention to how platforms handle user data and all of the problems that come with scraping and storing that data. We’ve built a new technology architecture that gives users great personalized recommendations while keeping data safe and secure on devices. We’ve been working on this for the past 18 months and we will be rolling out our first products in the coming weeks.
One of the things that we have been surprised to see is that the rest of the tech world is starting to wake up to privacy and data security issues.
Earlier this year, Mark Zuckerberg began his keynote at F8 by stating that “the future is private.” He went on to describe options given to users to lock down their accounts. Google, in an op-ed by Google CEO Sundar Pichai, talked about this new horizon of choice and privacy, framing the issue as one of individual responsibilities. Most recently, at WWDC this summer, Apple made data privacy a major theme for their opening keynote address. Amazon has notably said very little on this subject.
So “privacy” is clearly the new tech buzzword of 2019 but let’s take a step back and talk about what privacy means today and why big tech is now focused on it, and more importantly, why you should care about how tech companies are using your data.
Imagine your data as a piece of a puzzle -- your location history, the amount of time you’ve spent looking at someone’s picture on Instagram before scrolling away, every purchase you’ve ever made, every song you’ve listened to, the accumulated words you’ve spoken into an Alexa, every website you’ve ever clicked on, every tweet you’ve faved -- this is one microscopically tiny piece of a gigantic puzzle. Other peoples’ data are other pieces of this grand puzzle.
Now if I wanted to, could I sell my one individual puzzle piece? Probably not. It’s not even that valuable. But imagine all of these tiny data puzzle pieces fitting together into one very large, very lucrative puzzle comprised of data on a grand scale. When people talk about artificial intelligence, they’re generally speaking to the capacity to do machine learning on the whole puzzle, not to the value of individual pieces. The ultimate goal isn’t just to learn about you, but about all of us together: the entire world, having the capacity to serve personalized ads but also predicting behavior, markets and trends. The never-finished, ever-completing puzzle is the real prize, and only the biggest companies in the world have access to this puzzle as a whole.
There are only a handful of these companies in the world that own infrastructure capable of predictive machine learning at scale. American companies like Facebook, Google, Microsoft, IBM and Amazon are some of them, but Baidu, Alibaba, Tencent and other Chinese companies also have the capacity.
Facebook and Google have spent the last decade and a half accumulating social data (all the puzzle pieces) and acquiring competitors (puzzle analyzers), but they have now come under scrutiny for their corporate practices, with YouTube’s algorithms and Facebook’s content moderation click farms receiving a lot of negative press. Neither company has historically been very sympathetic to privacy advocates. For example, in 2009 Google’s Eric Schmit famously said, “if you have something that you don’t want anyone to know, maybe you shouldn’t be doing it in the first place.” Facebook bragged about changing the standard for what and how much people share online. “People have really gotten comfortable not only sharing more information and different kinds, but more openly and with more people,“ Mark Zuckerberg said in 2010, “and we decided that these would be the social norms now and we just went for it.”
What is happening now in the tech landscape that would prioritize pivoting, especially considering its historical disinterest in privacy? One hurdle is that Google, Apple, Facebook and Amazon are all facing regulatory scrutiny for anti-competitive practices. The pivot to privacy, at least in terms of messaging, allows them to minimize the need for outside influence. For example, moving people into private Facebook groups that are independently moderated also increases the pool of free content moderator labor. Simultaneously, over the past fifteen years these companies have already accumulated a massive amount of social data while eliminating or acquiring competitors.
But the reality is that the new big social app is neither owned by an American company nor will be directly subjected to American regulation; it’s TikTok, which is owned by Bytedance, a Chinese company valued at $78 billion. The refrain that you will hear amongst tech companies and some Congressional members is that tech companies should remain unregulated because they need to compete with Chinese AI capacities, and so the very worst algorithmic practices -- that promote discrimination, that exploit children, that radicalize for profit, dragnet surveillance -- are justified in this zero-sum game.
We don’t think the world is a zero-sum game, and we don’t think that compromising in quality is worth it in the long run. There is a very important place here for us to create the infrastructure to fix the internet, to give people completely private, algorithmic recommendations, and we’re doing it in a way that solves many of the problems that currently justify scrutiny. We want to get these big platforms out of the data business for good so we can start rebuilding a better internet.