At the Marketing AI Institute, we read dozens of articles on artificial intelligence every week to uncover the most valuable ones for our subscribers (become a subscriber today), and we curate them for you here. We call it 3 Links in 3 Minutes. Enjoy!

Similar to snowflakes, every individual’s walking style is unique to him or her. Gizmodo shares that work is being done to create a new footstep recognition tool that could replace retinal scanners and fingerprinting at security checkpoints.

“Each human has approximately 24 different factors and movements when walking, resulting in every individual person having a unique, singular walking pattern,” says Omar Costilla Reyes, the lead author of the new study and a computer scientist at the University of Manchester.

Reyes created the largest footsteps database in existence by collecting 20,000 footstep signals from 120 individuals. Using this database, Reyes trains the artificially intelligent system to scour through the data and analyze weight distribution, gait speed, and three-dimensional measures of each walking style.

The results so far show that, on average, the system is 100 percent accurate in identifying individuals.

Which Online Conversations Will End in Conflict? AI Knows.

According to The Verge, researchers at Cornell University, Google Jigsaw, and Wikimedia have created an artificial intelligence system that can predict whether or not an online conversation will end in conflict.

To do so, they trained the system using the “talk page” on Wikipedia articles—where editors discuss changes to phrasing, the need for better sources, and so on.

The system is trained to look for several indicators to gauge whether the conversation is amicable or unfriendly. Signs of a positive conversation include the use of the word “please,” greetings (“How’s your day going?”), and gratitude (“Thanks for your help”).

On the contrast, telling signs of a negative dialogue include direct questioning (“Why didn’t you look at this?”) and use of second person pronouns (“Your sources are incomplete”).

Currently, the AI can correctly predict the sentiment outcome of an online discussion 64 percent of the time. Humans still perform the task better, making the right call 72 percent of the time. However, this development shows we’re on the right path to creating machines that can intervene in online arguments.

AI Across Industries

In a recent Forbes article, author Bernard Marr shares 27 examples of artificial intelligence and machine learning currently being implemented across industries. If you don’t have time to read the full list, we’ve shared a few of our favorites below.

In consumer goods, companies like Coca-Cola and Heineken are using artificial intelligence to sort through their mounds of data to improve their operations, marketing, advertising, and customer service.

In energy, GE uses big data, machine learning, and Internet of Things (IoT) technology to build an “internet of energy.” Machine learning and analytics enable predictive maintenance and business optimization for GE’s vision of a “digital power plant.”

In social media, tech giants Twitter, Facebook, and Instagram are using artificial intelligence to fight cyberbullying, racist content, and spam, further enhancing the user experience.

Photo by Marcus Wallis on Unsplash.