A snapshot of AI-powered reminiscing in Google Photos
By: People, Ai Research
Tags: Human Centered Design, Photos, AI, UX, Machine Learning

If you were alive before smartphones and digital cameras, you might remember when your photographic memories were in physical photo albums or a shoebox that you thumbed through when you got the urge to reminisce.

Now that we carry high-quality cameras in our pockets to snap selfies and take videos of our cats, our photo and video libraries are getting huge. It’s great — so many pictures😃; and overwhelming — so many pictures 😩. Special moments that we capture are quickly buried in an overwhelming black hole of digital obscurity, and the majority of photos backed up in Google Photos might never be viewed again.

Still we took them for a reason — to document, to share and to remember those meaningful moments. We on the Google Photos team saw an opportunity to reconnect people with their memories, and we used AI to understand what photos are meaningful and worthy of reminiscing. That said, because a large, diverse group of people use Photos, and because reminiscing is so personal, we knew that we’d need to give individuals control over their experience.

How AI helps us reminisce

In Google Photos we use AI to make your images easier to search and organize by people, places, and things. It also powers features that go beyond search and organization. We use AI to automatically combine photos and videos into a short movie set to music and generate animations from photo bursts. If face grouping is on, AI creates collages featuring a recent photo of someone next to an older photo of them in a similar pose. Personally, I love that these show how someone has grown over time, like this one that shows my daughter at age one and age three.

Google Photos collage; photo credit: Thryn Shapira

A few years ago, we introduced AI-powered reminiscing features. Rediscover This Day resurfaced photos from the same day in previous years, and They Grow Up So Fast compiled photos and videos of a loved one over time into a short movie. These quickly became some of our most loved features; people enjoyed seeing these meaningful moments they might not otherwise revisit. We wanted to build on this and resurface more photos and videos buried in people’s digital libraries.

“Rediscover this day” feature in Google Photos

Make Memories from mountains of pictures

We started working on our Memories feature with the goal to make reminiscing a central and everyday part of the Google Photos experience. With the help of AI, we set out to curate meaningful content from your photo library and display it in an immersive story player.

Memories experience in Google Photos

That said, Memories needed to be enjoyable for everyone — no matter the size of their photo library, whether or not they travel, have kids or pets, or if they take hundreds of pictures a week or a few pictures a month. To create an engaging reminiscing experience that everyone would enjoy we needed to make tough decisions about what types of content to include or filter out.

In addition, reminiscing is personal and not all memories are welcome. Some memories are intensely sad, upsetting, or painful — such as photos of an ex-partner or a loved one that has died. When we expanded our reminiscing features and automatically brought more photos and videos out of obscurity and put them front and center in the Photos app, the impact of getting things wrong became much higher.

With this in mind, we knew that we needed to give each individual some control over their experience. AI-driven products are probabilistic by nature and the experience won’t be perfect for everyone, every time. It’s important to allow people to adapt the output to their needs, edit the experience, or even turn it off.

Curate The Right Photos in Memories

To build Memories, we didn’t just start with AI — we started with people. We conducted research with a diverse set of users and those learnings guided how we defined the AI models that power Memories.

To start, AI curation for Memories takes a set of photos and filters out the bad, boring, and sensitive stuff — from receipts and parking lots to all the blurry photos you took of your fast-moving toddler before you snapped a sharp one. We do this in two ways: non-pixel-based detection models produce signals and labels (i.e. things, people and pets) that determine how likely it is that a photo could be a receipt or picture of your tax forms that shouldn’t be included; and pixel-based models filter out near-duplicates, and score photos on a set of aesthetic qualities like blurriness and lighting.

Then a set of non-machine learning filters based on photo metadata (image resolution, file formats, photo dimensions) filter out things like screenshots and low-resolution photos. We use rule-based filters because AI models simply aren’t needed for this. The camera codes information, like the resolution and whether or not it’s a screenshot, directly into the image file. Because of these filters I’ll never encounter the 64 screenshots of my phone’s lock screen that my daughter took while I’m reminiscing.

Finally, the set of photos is packaged into a memory.

Giving people control

Even if we could accurately predict the significance of each photo, we can’t accurately predict how someone will feel about revisiting a particular moment. And we’d heard from some people that photos surfaced from our earlier Rediscover This Day feature were sometimes unwelcome. In Rediscover This Day, users could turn off the feature or swipe the card away.

For Memories to be positive and meaningful, we needed to continue to include explicit controls so people had the final say over their own reminiscing experience. I understood this need myself. For a while after my dad died it felt too painful to see photos of him resurface unexpectedly. But a year later I was ready to revisit the photos from his funeral where my siblings and I were all together sharing grief and reminiscing about his terrible dad jokes and astonishing life-long devotion to the San Diego Chargers.

With Memories prominently placed at the top of the main app view, we had to be especially sensitive to needs like this. While our AI models do their best to filter out sensitive content, they won’t — and can’t — always get it right. For example, it may seem obvious to automatically detect and filter out photos of funerals. But many photos of funerals and weddings in Western countries share the same objective characteristics: people wearing dark suits, people seated in an assembly or around tables. Funeral traditions are also not universal, and don’t always fit the stereotypical western image. Hindu widows wear white, and at a funeral I attended when I lived in Cameroon, community members wore bright colors and patterns. Even at my Grandma’s funeral, very few people wore black because we knew how disappointed she would be if we treated it like a somber affair. Instead we dressed in bright springtime florals while we celebrated her long and very productive life.

To give people control in Memories, we used existing controls and added new ones. Shortly after we launched Rediscover this Day, Google Photos gave people the ability to hide specific faces in their library. You can hide photos of an ex-partner or an obnoxious in-law, and their face won’t show up in reminiscing features ever again (and you can of course bring those memories back if you change your mind). We felt strongly that the ability to hide dates was also important, and research supported this hypothesis. So we built controls to hide dates and date ranges directly from the memory player. And you can also remove memories all together. The result is key controls for people to adjust and personalize their reminiscing.

User controls in the Memories feature

In the end, it was rewarding to see how AI could be used to power such a personal experience that lets people get more out of their photos: reliving memories and seeing a snapshot into the past. Of course we learned a few things along the way, including how AI shouldn’t be the only tool thrown at every problem, in this case rule-based filters work well, and that there’s room for personal control even with automatic features.

For more on balancing user control and automation when designing with AI, check out the People + AI Guidebook.