AI & People: What Kind of History Will We Write Together? (Part 2)
How do you define privacy? Is privacy still possible? More to the point, has privacy actually ever been possible?
How do you define privacy? Is privacy still possible?
More to the point, has privacy actually ever been possible?
If you haven’t yet read Part 1, you can find it here 😃.
In Part 1 of this Series we talked about privacy. Not a new subject in the digital world, of course, but what I’m hoping to make very real in this 3-part series (and it may already be very real to many of you) is this:
Privacy is not exclusively a digital-world problem. Privacy has never been exclusively a digital-world problem.
Part 1 talks about AI and it’s relationship to digital privacy. It is subtitled “Is privacy still possible?” for the simple reason that when most people think of information privacy, they think of digital information privacy, so this was a good place to start. In Part 2 we ask the question:
Has privacy ever been possible?
We live in a world that runs on digital data
Every day an increasing amount of your information, in the form of digital data, is uploaded, stored and shared, BUT…
- how your data is collected
- who can see it and who can use it
- your right to know when it is used
- your right to remove it, or to say “no” to its collection in the first place
… these are age-old issues.
The difference today is that our information can be shared, analyzed, manipulated, stolen and used at lightning speed. And it can be cross-referenced with more petabytes of data than we can ever imagine.
Privacy retention is a balancing act
How can we utilize the power of AI to make advances in areas like medical research (just one of many possible examples), while retaining as much of our personal privacy as possible? Whether privacy loss happens through legitimate information-sharing or through criminal activities, it is still lost privacy and we must balance positive gains against this loss. Sometimes the privacy loss is absolutely worth the cost, we just need to be vigilant and know when this is the case:
We must Advocate
We must advocate for ourself and others. We must ask questions about our data, and require accountability in the answers.
We must Educate
Get the info before we click. For example, before we allow apps like Snapchat to map our face and movement by adding funny glasses to our webcam image, let’s take a step back and consider how much privacy we will lose.
We can also slow the watershed of personal data that we voluntarily share through social media, online shopping, fitness devices, convenience apps (how many times do we click “sign in with Google”) and more.
And what about the times we are not even aware that AI-powered analysis is being used:
We must Participate
AI affects us EVERY DAY, so let’s educate ourselves, advocate for ourselves and others, and be a part of this ongoing conversation.
Let’s circle back to the question we asked at the end of Part 1:
Wherever AI is going, how will it get there?
Time to put our thinking caps on… We’ll dig deeper in Part 3!
Let’s keep the conversation going!
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Originally published at https://www.linkedin.com.