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New feature: Blurring faces with no-code AI

February 23, 2021

As of today, you can set a Fulcrum photo field to automatically inspect any photos you take to see if they include faces and, if they do, to blur them out (or “de-identify” them) automatically.

(If you’re the type of person who wants to jump straight to doc, go for it.)

It’s a cool feature, for sure, and a great application of AI in particular. But why start with privacy? Why are photos a privacy issue? Why use AI instead of having human beings review photos? And what does all of this imply about Fulcrum?

The short answers: Privacy regulations such as GDPR and CCPA are developing teeth in the form of fines and significant penalties. Since faces can be used to identify people, these regulations require organizations to blur faces in photos. AI is actually better than humans at identifying faces at scale. And this new feature demonstrates one way Fulcrum is innovating by tapping the power of AI for automated image processing.

For the longer answers, let’s start with a broad perspective and drill in.

How most of us will use AI

The majority of us will never create new AI functionality per se: It still takes a lot of knowledge to do so, and not only do we humans need training in AI algorithms and tooling, the AIs that people create need to be trained as well. (“Training,” for an AI, is looking at lots and lots of examples of the thing you’re applying AI to.)

So, while the hype may tell us that AI is a semi-miraculous, strategic technology that can do almost anything, most of us are better off getting practical and tactical with it, focusing on specific, well-understood use cases that maximize value in our particular circumstances.

AI-based computer vision

Computer vision is one of those specific use cases that’s worth focusing on. It’s a form of AI-based image processing that enables a computer to tell us something about the contents of an image. We can use it pretty reliably to identify specific items in photos, such as soda cans, cranes, or faces. And because these are pre-built, pre-trained AI models, there’s no code necessary to use them.

For example, this is a photo taken by Fulcrum, in the Fulcrum labs, where we use artificial intelligence to identify a beer can and the text that’s written on it.

An example of computer vision. Note the automatically generated descriptive data on the right hand side of the screen.

(This is something that we’re shaking out — if you’re interested in working with us on it, contact the Product Manager, Dale Wilson, to discuss your potential use cases.)

Where AI does better than people

Humans still tend to be far better at general-purpose applications than AIs are. That’s why visual CAPTCHAs are so common, and why we do better than AIs at funny games like “Muffin or Chihuahua?”

I admit it, this one makes me feel confused, too.

But a construction site, utility plant, or office looks nothing like the carefully laid-out set of muffins and dogs we see above; instead, it contains things like cranes, transformers, and desks. If there’s something that looks like a face to an AI, it’s almost certainly a face. And that means you can let an AI scan photos for faces instead of relying on humans, and enable software to blur out the faces it finds.

In fact, humans are arguably much worse at this kind of task than an AI. We may be better at general-purpose image identification, but we’re lousy at repetitive tasks. We get bored and hungry. We want to go home on a Friday afternoon. We daydream and start flipping through pictures without really looking at them. We miss stuff.

We’re only human, after all.

But once you put an AI to work, it works tirelessly. Here’s a photo taken in Fulcrum that has been de-identified with no human intervention whatsoever.

Targeting privacy

To get some perspective on why we should place such a high priority on using AI for facial blurring specifically, I spent some time with Kristin Carrington, the founder and CEO of Carrington Risk. Her company provides risk management for commercial properties, which includes using Fulcrum to perform property inspections.

Kristin told me that it has become absolutely essential for her business.

Privacy laws, such as GDPR in the EU and CCPA in California, are becoming more stringent on the subject of personally identifiable information, or PII. Since a face in a picture “relates to an identified or identifiable living individual” (as per the EU definition), it qualifies as PII. Soon, Kristin said, it will become difficult or impossible to do business in global markets without having some way of “de-identifying” the faces in photos.

She has looked at how that could be done manually, and it’s very cumbersome — and she’s not even sure that manual processes would be permitted by her clients.

Moreover, manual review is an additional, unnecessary risk. It’s better to allow the AI to take over, thoroughly reviewing every photo with equal effort, than to have the potential for a human worker to overlook a photo at the end of a long day.

Between the high risk of human error and the poor productivity that it would involve, Fulcrum’s AI-based feature is the obvious answer. It’s opening more business opportunities for her company while ensuring that she can engage with those opportunities in a highly productive way.

Resources and getting started

For more information, you can download the data sheet or explore the documentation.

Or you might just start working with the feature: It’s as simple as checking a box.

Wait — you can’t use the feature because you’re not a Fulcrum customer yet? No problem: Get started with a 30-day free trial.