AI Ethical Framework: Three Things We Agree On

This series on AI is co-authored by Megan Notarte and Jason Grigsby.

We pride ourselves on doing right by the web and by the people who use it. So figuring out our approach to AI has been challenging. Some of us are excited by the possibilities. Others are skeptical or even hostile. 

But in our discussions, we found that even people with differing viewpoints agree on three things:

We’re wary of those who say AI is inevitable and use that self-fulfilling prophecy to justify actions. That’s not what we’re saying here.

Instead, we see it as inevitable that we will be asked to incorporate AI in our work whether that means including an AI feature in a client project or team members asking to use AI to help them complete their tasks. We’re curious about ways these tools might help us do our own jobs better.

We need some guidelines on how we answer these questions.

The most strident opposition to AI doesn’t feel right to us because there are uses of AI that don’t seem to have some of the biggest societal and ethical concerns.

For example, Apple uses AI in the iPhone 15 camera to automatically detect portrait mode and to create better photographs. Photoshop’s new AI features can extend the background in an image to fit an aspect ratio. Not to mention the more transformative and life-changing AI-based solutions like Apple’s Personal Voice.

It seems undeniable to us that some AI is not merely good, but amazing. Desirable even. And without some of the downsides of other AI uses.

If not all AI is bad, then how do we decide whether a particular use of AI is ethical or not? How do we know which AI services align with our values? How do we design and build AI features that are a benefit for our customers, their users, and are consistent with our values?

This is our initial attempt to define some criteria for evaluating decisions around AI. Our thoughts are still evolving. Our hope is that we can use these questions to guide us towards uses of AI that maximize its usefulness and minimize its harms.

Our framework consists of questions focused on two areas:

• AI Models — How do we evaluate competing AI services on criteria that goes beyond price and features?
• AI Usage — How do we shape the features we’re building to utilize AI well and reduce negative outcomes?

The next two articles in this series delve deep on these questions. Tune in tomorrow!