Text by CLOT Magazine
Tate Exchange, founded in 2016, is a platform at Tate Modern and Tate Liverpool that explores how art makes a difference in society in response to an annual theme and through a participative, process-led and socially engaged art practice. Tate Exchange invites the public to test ideas and explore new perspectives, illuminating the value of art to society.
International Collective Hyphen-Labs are launching the fourth year of Tate Exchange this September. They will respond to the 2019-20 theme of ‘power’ with the programme Higher Resolution. Hyphen-Labs said Higher Resolution will explore our emotional, intellectual and physical relationships with power; those omnipresent entities in our physical and digital lives; the all-seeing powers that could hold the answers and solutions. We look forward to working with Tate Exchange audiences in September to interrogate power and technology and how we can work with and against it.
Founded in 2014 by experienced designer Carmen Aguilar y Wedge and architect Ece Tankal, Hyphen-labs has brought together an international network of women of colour with impressive backgrounds, ranging from scientists to architects, engineers and artists. Collaborating with Tate Exchange associates and global guest contributors, Hyphen-labs will examine what we share with machines and the algorithms that define our privacy, behaviour and digital rights, inspired by the question, how did we get here?
Focusing on technology and the next generation of ‘higher power’, participants will explore the creation of power and the tools to disrupt, resist and redistribute it through an immersive sequence of interventions and conversations, talks and workshops. The programme Higher Resolution runs at Tate Exchange from September 17 to 29. The highlights include: Alex Fefegha and Akil Benjamin Comuzi on How Does AI Augment Human Relationships?, Big Brother Watch: Cryptoparty – a space to ask any technology questions about secure passwords, social media privacy settings and internet cookies, and Caroline Sinders on Is a Feminist Machine Learning System Possible?