The Atlas of AI Incidents
in Mobile Computing

keep scrolling down

In our connected world, our mobile devices – those omnipresent smartphones and ubiquitous fitness trackers - extend deep into our lives, dissecting and cataloging every heartbeat, every restless night.

1/5

The new EU AI Act classifies each application of mobile devices into one of three risk levels: unacceptable, high, or low.

2/5

Unacceptable uses are strictly forbidden.

High-risk applications , crucial in domains such as safety and education, walk a fine line between importance and risk.

3/5

Then there are the low-risk applications , those seemingly benign chatbots and innocuous recommender systems. They appear benign but harbor potential dangers.

4/5

Click icon Discover the hidden dangers of low-risk applications by clicking on . Even the most innocuous tools can unveil unexpected and deleterious consequences.

5/5


Research

This visualization showcases a dataset of 54 real-world uses of AI in mobile computing, linked to incidents reported in the news and sourced from the AI Incident Database. As of March 2024, there were 649 incidents reported from 3,412 news articles, primarily from the US. Most of these incidents were reported between 2013 and 2024. To create the dataset, we initially downloaded all 649 incidents. After removing duplicate entries, we were left with 639 distinct incidents. We analyzed ther key variables such as title, description, AI deployer, AI developer, and harmed subjects. We then manually filtered the incidents to include only those relevant to mobile and wearable devices, paraphrased them into AI uses, and consulted experts to list their risks and benefits.



Team

Edyta Bogucka, Marios Constantinides, Julia De Miguel Velazquez, Sanja Šćepanović, Daniele Quercia, Andrés Gvirtz