Data / Set / Match

Data / Set / Match is a year-long programme at The Photographers' Gallery seeking new ways to present, visualise and interrogate contemporary image datasets. The essays in this theme draw attention to, and explore, the uses, influence and politics around image datasets and contemporary visual culture.

November 2019

An Introduction to Image Datasets

In 2019 The Photographers' Gallery digital programme launched 'Data / Set / Match', a year-long programme that explores new ways to present, visualise and interrogate contemporary image datasets. This introductory essay presents some key concepts and questions that make the computer vision dataset an object of concern for artists, photographers, thinkers and photographic institutions.

November 2019

Where Did ImageNet Come From?

In September 2019 the ImageNet creator Fei-Fei Li gave a talk at The Photographers' Gallery talking through the events and key people that led to the creation of visual datasets.

November 2019

I’m looking at you, looking at me

In Heather Dewey-Hagborg’s artwork ‘How do you see me?’, commissioned for the Data/Set/Match programme at The Photographers’ Gallery, the artist explores how machines see us. A question that has been carefully slipping through several areas of production and research during the past couple of decades. At the same time an essential need has also emerged to understand the processes and internal mechanisms that are usually hidden from or mysterious to the user: commenting on those who code, train, build these mechanisms and how this translates into what happens outside of the screen.

November 2019

From Spectacle to Extraction. And All Over Again.

I met with Kate Crawford and Trevor Paglen on the press preview of their exhibition Training Humans in Milan at Osservatorio Prada. It was the morning of September 11th –not a neutral day to unthink photography and the power operations of vast populations of images. On the contrary, it was the most apt one to seriously consider Crawford and Paglen’s proposition that "images are no longer spectacle but they are in fact looking back at us, being actors in a process of massive value extraction".

Unevenly Distributed

The Future Is Here!, the title of Mimi Onuoha’s video project reflecting the human side of crowdsourced image labelling, is spot on. The stories I have been told by crowd workers from across the globe doing this work full-time indeed often have an eerily Gibsonian ring to them. Especially the stories from Venezuela.

April 2020

Tunnel Vision

When a computer vision algorithm recognises something in a picture, it soberly frames what it ‘sees’ in confetti-coloured rectangles, digital hues that contrast with the everyday shapes and colours that we see in a space with plain eye. Each neatly labelled with a single category, these annotations highlight answers but don't give explanations. To the uninitiated, it seems almost magical, or at least akin with some sort of intelligence.

Recovering Lost Narratives in Epic Kitchens

This article is an overview of the projects 'Epic Handwashing in a Time of Lost Narratives' and 'A Kitchen of One's Own' weaving a thread between the technical and the conceptual: the projects are linked historically by the writing and arguments put forth by Virginia Woolf, technologically by computational juxtapositions of text and image, as well as poetically in the viewer’s experience through a speculative remix.

June 2020

On MIT’s Moments in Time (and Being Dead-Alive)

I write this from my small New York apartment in my fourth month of isolation. The pandemic has required each of us to slow down and do less, and I keep thinking of a childhood friend who once told me, “We’re human beings, not human doings”. Even as a teenager, I knew this was an important paradigm shift: it meant that we could rethink how we define ourselves beyond endless production and consumption. Allowing oneself to be a human being seemed to resist the gig economy, workerism, the idea of “a calling”— all the ways that society has been structured to combine a person’s work into their core identity. The way busyness became a humblebrag. Human doings.

July 2020

On Lacework: watching an entire machine-learning dataset

I proposed what would become Lacework in the Summer of 2019. In my proposal, I describe a cycle of videos curated from MIT's 'Moments In Time' dataset, each then slowed down, interpolated, and upscaled immensely into imagined detail, one flowing into another like a river...