Google Photos is a photo and video storage and sharing service developed by Google. Google Photos was released in May 2015 as it separated from Google’s former social network, Google+. Google Photos was designed with the intent of creating a platform that allows people to store and easily access all of their pictures and videos from any device.
After its release, Google Photos's user base rocketed to 200 million after one year, 500 million after two years, and surpassed 1 billion after four years. As of 2020, Google reports that about 28 billion photos and videos are uploaded every week and that the service is home to more than 4 trillion photos.
Google Photos is available on Android, iOS, and online. Photos and videos can be uploaded and accessed via any of these platforms. The service organizes photos and videos by identifying any number of features present in the photo such as lakes, night, birthday, etc. It is capable of organizing photos by the faces of people and pets in them, even as the faces age. Users can manually fix or remove incorrect labels. Google Photos also can group photos and videos by location. It can determine a photo's location either by its embedded geotagging data, or by analyzing the photo for major landmarks (such as the Eiffel Tower).
The service includes a native photo and video editing software that can be used on any platform. Additionally, Google Photos offers a variety of ways to make sharing photos/videos easy and simple, such as generating web link to content that both users and non-users can access. Google Photos allows users to share albums with someone directly via their Google account. In 2020, Google added a heat map feature that displays the concentration of photos in the library as a function of location. In March of 2021, Google Photos started rolling out an advanced version of its video-editor for Android users. Users will be able to not only trim, stabilize, and rotate videos, but also crop to any aspect ratio, change perspective, and control brightness, contrast, highlights, and shadows. Google plans to release this feature to iOS in 2021.
Another feature that Google offers is Google Lens. Google Lens is part of the Google Photos application. Google lens is a type of image recognition technology. Image recognition technology uses artificial intelligence technology to identify objects in images.   In the case of Google Photos, Google Lens allows users to take a picture of an article of an object, such as an article of clothing, and then the image recognition technology software follows up with suggestions on places that carry similar objects to the ones in the image such as an article of clothing. This links to Google Shopping. Google Shopping is an e-commerce platform that gives users the ability to shop online using Google’s search engine. By linking Google Lens to Google shopping, users are able to use the Image recognition technology in order to shop for specific items that they only have a photo of without having to ask the person who was wearing the article of clothing.
Another feature that Google offers is 15GB of cloud storage. Cloud storage is a type of storage that relies on the cloud storage provider’s hardware rather than the user’s hardware.   This allows users who have limited storage on their physical devices to offload their storage needs unto the cloud storage provider’s hardware. In addition, Google gains access to a lot of image data that is valuable in order to train the image recognition technology software. This is because artificial intelligence requires a lot of data in order to be able to be trained. By providing cloud service to its users, Google is able to acquire a large amount of image data that allows the image recognition technology software to be trained in a more holistic manner. In addition, users are incentivized to continue using Google Photos past their allotted 15 GB of cloud storage into the more premium cloud storage paid subscriptions which is a long term financial investment.
In late 2020, Google rolled out a subscription-based service that ships Google Photos users 10 prints of that months best photos. The images are selected by a machine learning algorithm, but users can alter any choices. After some negative feedback through user-testing, Google now allows higher customization of the look, and finishing of the prints along with a reduction in subscription costs from $7.99 to $6.99. Users are able to cancel the service at any time, and are also able to skip a month, if they so choose to. Customers can order prints in multiple sizes, and also ask for a same-day pick-up at their local Walgreens. The most prominent feedback received for the service is the "outrageous cost", charging many times the price for printing at a traditional store.
Photos and videos are each uploaded to Google Photos in one of three ways: "original quality", "high quality", or "express." "Original quality" uploads maintain their original resolution and use part of the associated Google account's 15GB of storage shared between all Google products (including Gmail, Google Drive, etc.). Meanwhile, "high quality" uploads have their resolution downgraded to 16 megapixels and 1080p. Finally, "express" uploads are compressed to 3 megapixels and 480p. The free tier of Google Photos allows unlimited uploads in resolutions up to "high quality."
In November 2020, in an effort to increase the number of Google One subscriptions and reduce Google's reliance on ad-based revenue, Google announced that Google Photos will no longer offer free unlimited storage at "express" or "high quality" starting June 1, 2021. Existing photos and videos will remain unaffected. After all 15GB of account storage have been used, users will either have to maintain a Google One subscription or upload from a Google Pixel 5 or older device. Future Pixel devices will be unable to upload in "high quality" for free.
A foremost concern regarding Google Photos is ensuring that the user who uploads photos and videos is the only one who can control access to and view that content. These worries are substantiated by occurrences like Google accidentally sending users’ private videos to strangers in November 2019. To alleviate future incidents, Google continuously works to improve its security infrastructure to ensure that its privacy goals are upheld for the benefit of all users.
A seldom acknowledged facetof large scale data storage as seen in Gooogle Photos, is the presence of unknown persons present at the physical locations which store the massive collection of photos and videos, who may have access to private user data. At the physical data storage level, a cloud service provider must ensure that data is properly segregated, prepared for data recovery situations and ensure that no person who is not authorized can locally access the database storing sensitive or private information. 
Google Photos automatically runs every photo and video through visual recognition algorithms to identify objects and places. Once "face grouping" is enabled by the user, Photos will also start to categorize images by the people and pets who appear in them. There is some uncertainty surrounding Google collecting the information embedded in the photos and selling it to third parties or using it to display more relevant advertisements, even though Google ensures users that "face groups and labels in your account are only visible to you."
If a user allows Google to keep track of their location history under "Your Timeline" in Google Maps, Google Photos uses this alongside geotags embedded in photos to allow users to search their gallery by location and even review past trips minute-by-minute.
Even without geotags, Google Photos is capable of intuiting a photo’s location by analyzing for major landmarks. As a result, concerns have been raised about how this information is used and if it is secure.
Google is upfront that it uses this information to show users more relevant advertisements, but at the same time assures users that this information is never shared with advertisers. To accommodate these concerns, Google Photos gives its users the capability to turn off location history, remove location information from already existing photos, and choose whether or not to share a photo's location when shared.
Data Collection Motivations
There have been suggestions that Google released Google Photos in the interest of collecting more information about users through visual data. It has also been speculated that it was intended as a method of outsourcing work to train their visual recognition algorithms; the app frequently asks its users to manually verify (or reject) its proposed tags.
Bias in Algorithms
Bias in artificial intelligence is a widely discussed topic, with researchers voicing concerns that flawed training data can exacerbate or create unfair assumptions. One example is facial recognition algorithms misidentifying people of color more frequently than white people.
In 2020, Google made a change to its API tool Cloud Vision, which uses AI to analyze images in order to identify people, places, and things. The change involved eliminating gender labels on images, because a person’s gender can’t be determined just by how they look in a photo. Instead of using terms like “man” or “woman”, Google will tag images with labels such as “person” in order to avoid instilling AI algorithms with human bias.
Regarding its own AI principles, Google acknowledges that algorithms and datasets can reinforce bias: “We will seek to avoid unjust impacts on people, particularly those related to sensitive characteristics such as race, ethnicity, gender, nationality, income, sexual orientation, ability, and political or religious belief. We will design AI systems that provide appropriate opportunities for feedback, relevant explanations, and appeal. Our AI technologies will be subject to appropriate human direction and control.”
The nature of a computer analyzing and captioning a photo through a machine learning algorithm involves training from a data set. This is where a large amount of bias comes from, in the form of capture, category and negative bias.  Capture bias refers to all the variables involved with acquiring images, such as lighting conditions or camera used. Category bias refers to a poor definition of categories in which the image can exist, while negative bias involves the inability to train a model on categories which are not included in the data set.  Machine learning models only know what they are taught, and as such, any of these biases appearing in Googles training data will resurface when categorizing photos uploaded by users. 
Shortly after its release in 2015, Google Photos found itself under fire for a particularly offensive error: user Jacky Alciné reported that he and his friend were classified as "Gorillas" by Google Photos's visual recognition algorithms. In response, Google Photos promptly removed all labels relating to primates as a temporary fix. A spokesperson from Google stated that the labels "gorilla", "chimp", "chimpanzee", and "monkey" were blocked on the platform. According to Mr. Alcine, Google has intensified their search for qualified people of color to hire in order to correct issues stemming from under representation of minorities in technology companies.  With enough data and computing power, software can be trained to categorize images to a high level of accuracy, but it can’t easily go beyond the experience of that training. Even the very best algorithms lack the ability to refine their interpretation of the world as humans do.
In an effort to quantify the accuracy of Google Photos image recognition model, a study was performed by uploading a wide range of commonly recognizable photos and recording the results of categorization. The test was setup by uploading over one hundred photos, both with significant (descriptive) and insignificant (arbitrary) file names and placing them into albums organized by country of origin for that image. After leaving the images for one day, they had been organized into 9 broad categories with varying degrees of accuracy. The least accurate were photos of blue, incorrectly identified as the sky, while the most accurate were mountains, cars and sunsets. Nieuwenhuysen states that the system is satisfactory considering it can be used free of charge, reporting that it excels at recognizing any photo to at least a vaguely specific category, even when the image is named arbitrarily. 
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