Over the past year, a team of as many as 260 contract workers in Hyderabad, India has ploughed through millions of Facebook Inc photos, status updates and other content posted since 2014.
The workers categorize items according to five “dimensions,” as Facebook calls them.
These include the subject of the post – is it food, for example, or a selfie or an animal? What is the occasion – an everyday activity or major life event? And what is the author’s intention – to plan an event, to inspire, to make a joke?
The work is aimed at understanding how the types of things users post on its services are changing, Facebook said. That can help the company develop new features, potentially increasing usage and ad revenue.
Details of the effort were provided by multiple employees at outsourcing firm Wipro Ltd over several months. The workers spoke on condition of anonymity due to fear of retaliation by the Indian firm. Facebook later confirmed many details of the project. Wipro declined to comment and referred all questions to Facebook.
The Wipro work is among about 200 content labeling projects that Facebook has at any time, employing thousands of people globally, company officials told Reuters. Many projects are aimed at “training” the software that determines what appears in users’ news feeds and powers the artificial intelligence underlying many other features.
The Wipro workers said they gain a window into lives as they view a vacation photo or a post memorializing a deceased family member. Facebook acknowledged that some posts, including screenshots and those with comments, may include user names.
THE PROJECT
Human-powered content labeling, also referred to as “data annotation,” is a growth industry as companies seek to harness data for AI training and other purposes.
Self-driving car companies such as Alphabet Inc’s Waymo have labelers identify traffic lights and pedestrians in videos to fortify their AI. Voice assistant developers including Amazon.com Inc have people annotate customer audio to improve AI’s ability to decipher speech.
Facebook launched the Wipro project in April last year. The Indian firm received a $4 million contract and formed a team of about 260 labelers, according to the workers. Last year, the work consisted of analyzing posts from the prior five years.
The Wipro labelers and Facebook said the posts are a random sampling of text-based status updates, shared links, event posts, Stories feature uploads, videos and photos, including user-posted screenshots of chats on Facebook’s various messaging apps. The posts come from Facebook and Instagram users globally, in languages including English, Hindi and Arabic.
Each item goes to two labelers to check accuracy, and a third if they disagree, Facebook said. Workers said they see on average 700 items per day. Facebook said the target average is lower.
Facebook confirmed labelers in Timisoara, Romania and Manila, the Philippines are involved in the same project.
Among Facebook’s other labeling projects, one worker in Hyderabad for outsourcing vendor Cognizant Technology Solutions Corp said he and at least 500 colleagues look for sensitive topics or profane language in Facebook videos.
PRIVATE POSTS
Facebook users are not offered the chance to opt out of their data being labeled.
At Wipro, the posts being examined include not only public posts but also those that are shared privately to a limited set of a user’s friends. That ensures the sample reflects the range of activity on Facebook and Instagram, said Karen Courington, director of product support operations at Facebook.
— source reuters.com | May 6, 2019