privacy

MegaPixels

Adam Harvey (US), Jules LaPlace (US)

The project aims to provide a critical perspective on machine learning image datasets, one that might otherwise be overlooked by academic and industry-funded artificial intelligence think tanks. Each dataset presented on this site undergoes a thorough review of its images, intent, and funding sources.

Privacy Machine

Timm Burkhardt (DE)

An electronic way to say, “I want to be private today and not appear in your social media photos.” Privacy Machine is a working proof of concept: stand in front of the screen and take the badge or the scarf. Both have a special pattern on it. As long as this pattern is recognized by the camera, the software will pixelate your face. It‘s an unrealistic wish because manufacturers would have to integrate this software into their smartphones as a default.

Project Alias

Bjørn Karmann (DK), Tore Knudsen (DK)

Our relationship with technology is formed by how we interact with it. However, commercial smart products for the home tend to treat the user as passive consumers. Especially smart home assistance has shown design patterns that limit the possibilities of interaction and agency from the user perspective, even in the most private and personal sphere—the home. Our interaction patterns are highly determined by the designers of these products, and with Alias, we are interested in how this power relation can be redefined, especially when it comes to privacy. The exciting future that “smart” technologies can give us often comes with conditions that diminish our privacy and the feeling of being in control. With Alias we want to challenge this condition and ask what kind of “smart” we actually want in the future.