Skip to main content

Fake news? A.I. algorithm reveals political bias in the stories you read

Here in 2020, internet users have ready access to more news media than at any other point in history. But things aren’t perfect. Click-driven ad models, online filter bubbles, and the competition for readers’ attention means that political bias has become more entrenched than ever. In worst-case scenarios, this can tip over into fake news. Other times, it simply means readers receive a slanted version of events, without necessarily realizing that this is the case.

What if artificial intelligence could be used to accurately analyze political bias to help readers better understand the skew of whatever source they are reading? Such a tool could conceivably be used as a spellcheck- or grammar check-type function, only instead of letting you know when a word or sentence isn’t right, it would do the same thing for the neutrality of news media — whether that be reporting or opinion pieces.

That is what the creators of a new algorithm developed by The Bipartisan Press claims to be able to do. They have built an A.I. that can, they say, predict whether text leans left or right with more than 96% accuracy.

“The A.I., which is based on state-of-the-art technology like BERT and XLNet takes in text input, and outputs a numerical value to denote the bias,” Winston Wang, managing editor at the Bipartisan Press, told Digital Trends. “We used a scale of -1 to 1 for simplicity, where a negative value shows left bias, while a positive value shows right bias. The absolute value of the result shows the degree of bias. For example, an article with 0.8 has a considerable amount of pro-right bias.”

The system uses a variety of A.I. approaches, some of which are described here. The excitement of being able to use A.I. for a task such as this is that it opens up the possibility of assessing news coverage and other content at a scale that would be impossible for human raters. (And, provided it works as well as described, potentially with more consistent accuracy, too.)

Wang said that the team is currently working to create a Chrome browser plugin. This could be used to help educate readers on the biases of news articles they read. The A.I. could also potentially be utilized for better content-recommendation systems. Finally, it could help news writers be aware of biases they may not even realize they have, thereby giving them prompts for more objectivity.

You can check out a demo of the A.I. here. For what it’s worth, this story has “minimal” bias.

Editors' Recommendations

Luke Dormehl
I'm a UK-based tech writer covering Cool Tech at Digital Trends. I've also written for Fast Company, Wired, the Guardian…
How the USPS uses Nvidia GPUs and A.I. to track missing mail
A United States Postal Service USPS truck driving on a tree-lined street.

The United States Postal Service, or USPS, is relying on artificial intelligence-powered by Nvidia's EGX systems to track more than 100 million pieces of mail a day that goes through its network. The world's busiest postal service system is relying on GPU-accelerated A.I. systems to help solve the challenges of locating lost or missing packages and mail. Essentially, the USPS turned to A.I. to help it locate a "needle in a haystack."

To solve that challenge, USPS engineers created an edge A.I. system of servers that can scan and locate mail. They created algorithms for the system that were trained on 13 Nvidia DGX systems located at USPS data centers. Nvidia's DGX A100 systems, for reference, pack in five petaflops of compute power and cost just under $200,000. It is based on the same Ampere architecture found on Nvidia's consumer GeForce RTX 3000 series GPUs.

Read more
Algorithmic architecture: Should we let A.I. design buildings for us?
Generated Venice cities

Designs iterate over time. Architecture designed and built in 1921 won’t look the same as a building from 1971 or from 2021. Trends change, materials evolve, and issues like sustainability gain importance, among other factors. But what if this evolution wasn’t just about the types of buildings architects design, but was, in fact, key to how they design? That’s the promise of evolutionary algorithms as a design tool.

While designers have long since used tools like Computer Aided Design (CAD) to help conceptualize projects, proponents of generative design want to go several steps further. They want to use algorithms that mimic evolutionary processes inside a computer to help design buildings from the ground up. And, at least when it comes to houses, the results are pretty darn interesting.
Generative design
Celestino Soddu has been working with evolutionary algorithms for longer than most people working today have been using computers. A contemporary Italian architect and designer now in his mid-70s, Soddu became interested in the technology’s potential impact on design back in the days of the Apple II. What interested him was the potential for endlessly riffing on a theme. Or as Soddu, who is also professor of generative design at the Polytechnic University of Milan in Italy, told Digital Trends, he liked the idea of “opening the door to endless variation.”

Read more
Emotion-sensing A.I. is here, and it could be in your next job interview
man speaking into phone

I vividly remember witnessing speech recognition technology in action for the first time. It was in the mid-1990s on a Macintosh computer in my grade school classroom. The science fiction writer Arthur C. Clarke once wrote that “any sufficiently advanced technology is indistinguishable from magic” -- and this was magical all right, seeing spoken words appearing on the screen without anyone having to physically hammer them out on a keyboard.

Jump forward another couple of decades, and now a large (and rapidly growing) number of our devices feature A.I. assistants like Apple’s Siri or Amazon’s Alexa. These tools, built using the latest artificial intelligence technology, aren’t simply able to transcribe words -- they are able to make sense of their contents to carry out actions.

Read more