"The API of Me" in the age of AI
Our computing ability intersects with our own personal dataset to create new and differentiated solutions with AI at the center. But it’s confusing to know whether it’s safe or dangerous to interact with these solutions.
How do we know what we’re sharing? These systems are in a cloud environment that we don’t control and are subject to a user agreement that most non-lawyers will have trouble comprehending.
About a decade ago I wrote an essay on the API of Me - a description of how we could take back control of our personal preferences while keeping space for commercial use.
What is “an API of Me”?
An API is an Application Programming Interface - a way for computers to speak to each other and share a “handshake” that allows them to broadcast how they will request and respond to information.
Understanding the information blueprint provided by an API lets you know how to communicate with another system.
There’s a lot of stuff going on in the background when we use these systems. I believe we need to design these interfaces to better direct consumer choice to match the outcomes they want.
As consumers, we don’t have an easy way of expressing our preferences across applications, devices, and situations. We use operating system preferences (Apple or Android), application preferences (depending on an individual application), and add-on preferences (ad blockers or VPN programs).
We need a solution that takes our preferences into account.
Why does this matter?
AI models will soon be present on local, private devices. Understanding the data contract we make with applications is even more important when we think about the data we’re sharing intentionally and inadvertently.
The original essay made points that resonate today:
A decade later, these questions are not solved.
We have many of the parts we would need to create a solution that lets people understand and control the information they share with the larger world while maintaining the ability to build commercial products on top of this structure.
Towards an API of Me
If we wanted to build an API of Me today, what are some key building blocks to address?
Learning and usability - The biggest obstacle to an “API of me” is a design hurdle.
It’s confusing to know what information you are making available, for what period of time, to whom, and where it might be used.
A local AI, running only on your device, might be the breakthrough we need to be able to explain the choices you are making with your data so that you are more informed. (Of course, you’ll need to narrow the context and set rules so that it accomplishes what you need.)
Authentication - you need to prove that you are who you say you are. You’d need a multi-factor auth scheme that combines something you know (a password) with something you generate (a device password, run locally) with some other factor (a passphrase, a physical key, or similar).
I’m on the fence about biometrics and hopeful that they can be secured on-device so that you could use a thumbprint or a facial scan if you want.
Authorization - you need to know what you are allowed to do, based on who you are.
This one’s the most tricky of the available items, mostly because authorization comprises policies that combine the following concepts:
There’s a lot of ground to cover, but much of this sounds like the work we’ve done to build systems into local and enterprise software.
If the API of Me is easier to configure than the equivalent choices presented by Apple and Google, we’ll have a truly personal experience while protecting our information in the ways we expect.
What’s the takeaway??Locally run AI models – with the right context – provide a promising way to inform consumers about the information they share (or choose not to share) with third parties. The trick? Figuring out a way to be transparent when AI agents communicate with other AI agents.
Solutions Specialist at Google
1 天前Reminds me of the Solid project by Tim Berners-Lee, didn't catch on but I agree something is needed https://solidproject.org/about
Lead Data Analyst @ CF Search | Founder of @DataWavves | Demand Generation & Marketing Data Leader | Revenue, Marketing and Digital Operations Expert |
6 天前Great point on running local LLMs rather than cloud ones in the API of Self