India's largest platform for AI & Analytics leaders & professionals

Sign in

India's largest platform for AI & Analytics leaders & professionals

3AI Digital Library

Facebook is testing an AI-powered tool to Summarize News

3AI January 2, 2021

Facebook has been trying to get a foothold in the news space for many years. Last year, the company launched a dedicated section on its site called Facebook News for users in the US. It also wants to expand this program to other countries such as Brazil, Germany, and India.

According to a report from BuzzFeed News, Facebook is testing an AI-powered tool called TL;DR (Too Long; Didn’t Read) to summarize news pieces, so you don’t even have to click through to read those articles.

The report noted that the company showed off this tool in an internal meeting last night. It’s also planning to add features such as voice narration and an assistant to answer queries about an article.

At the outset, this seems like a great idea — getting a short summary of an article you don’t have time to read, right. There are already some similar tools such as the AutoTLDR bot on Reddit. However, given Facebook‘s sketchy history with news and publishers, there are many ways this could go wrong.

At best, the AI makes silly mistakes in parsing the article content, so you can’t make sense of the summary it spits out. After all, We’ve seen many incidents where bots picked out problematic portions of content from their training algorithms and spewed racist gibberish.

At worst, there’s potential to create or distribute misinformation. There are a ton of news sources on Facebook that are not known for their accuracy. If a skewed summary of those articles starts floating around, it might create more trouble.

Facebook will also need to train its algorithm to avoid taking quotes or sentences from articles out of context. A seemingly non-problematic summary could be contradicting the article or the subject and vice versa.

In the past, researchers have successfully tricked AI systems that are designed to detect toxic comments on the internet with ‘positive’ words. If the people behind propaganda operations could crack Facebook’s algorithm for summarizing articles, they could write stories in such a way that the summaries include the messages they want to spread.

Many reports have pointed out the social network’s massive misinformation problem, and a lot of it was because of poorly designed software. While Facebook’s TL;DR product is not public yet, it already sounds like it could be a disaster.

Picture from freepik.com

    3AI Trending Articles

  • Online learning will pave the way for a digital future

    Online learning has emerged as a critical tool that promises the potential to prepare business and professionals for a digital future. While skilling has become a hot trend in the current job climate, professionals should know that simply having basic digital skills won’t cut it because disruptive digital skills are now a necessity, not a […]

  • AI is changing the way doctors think about providing care

    While robots and computers will probably never completely replace doctors and nurses, machine learning/deep learning and AI are transforming the healthcare industry, improving outcomes, and changing the way doctors think about providing care. Machine learning is improving diagnostics, predicting outcomes, and just beginning to scratch the surface of personalized care. Imagine walking in to see […]

  • Blockchain Powered Smartphones by Fesschain

    Firm has tied up with a private manufacturer that can produce 10,000 pieces a day. But Fesschain is now scouting for a suitable location in Noida to set up its own production unit Homegrown blockchain technology company Fesschain is targetting almost 10 shipments of its smartphones in the next 6-12 months. The company, which has recently entered mobile handset […]

  • ADKAR – Driving Behavioural Change for Smoother AI Adoption

    Featured Article: Author: Abhishek Tandon, LTIMindtree As mentioned in chapter 1, AI projects generally suffer from abandonment because they are left at the point of execution and not thought through from a consumption perspective. One of the key reasons for that is lack of understanding of the “bigger picture” that ends up causing a lot […]