MusicMakers Hacklab – The Hacked Mind Finale

HAU2, Hallesches Ufer 32, 10963 Berlin Map
Tickets: 8 / 5 € reduced


17:00 19:00

Performances by Hacklab participants
Hosted by Peter Kirn and Ioann Maria

The MusicMakers Hacklab is a weeklong open, collaborative laboratory hosted by Peter Kirn of Create Digital Music. Now entering its 6th edition within the CTM Festival, Hacklab brings on co-host Ioann Maria to reflect on the promise and danger of artificial intelligence and machine learning in music.

Machine learning technologies have created the opportunity to make the machine a more relatable collaborator – allowing it to listen, see, and respond in a way that more closely mimics human expectations. There’s growing hope that these techniques can externalise our own perception and potential. But there are justified worries about these technologies. Can artists help calm some of our fears by hacking or transforming AI technology into something more open and transparent?

For this year's MusicMakers Hacklab, participants will invent collaborative performances that embrace the chaos, strangeness, and cultural anxiety surrounding the theme of AI, echoing the titular Turmoil of this year's CTM festival. Just-created performance designs, circuits, code, and ideas will be put to the test in front of a live audience as a multidisciplinary group of creative performers share the work they've constructed over the course of the CTM festival week. Expect new work in live musical performance, movement, visuals, and surprises.


The CTM 2018 MusicMakers Hacklab is presented in collaboration with CDM, with the kind support of Native Instruments and the SHAPE platform, which is co-funded by the Creative Europe programme of the European Union.


Ioann Maria[PL/UK]

Ioann Maria is a new media artist, filmmaker, and computer scientist. Ioann’s work is focused on hacktivism, electronic surveillance, computer security, human-machine interaction, and interactive physical systems. In her solo and collaborative projects she explores new methods in real-time audio-visual performance.

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