Tasker (2024)
Above Tasker, Technical prototype video, CVPR AI Art Gallery, Seattle, US, June 2024.
It can be argued that the age of ‘AI’ began on February 10th, 1996 when Garry Kasparov, the world chess champion, first lost against IBM’s Deep Blue computer in a highly publicised chess match (and a rematch in 1997).
Image of Garry Kasparov playing IBM’s supercomputer ‘Deep Blue’ during the 1997 rematch. Image source: https://www.kasparov.com/
The loss was a significant moment in the history of chess and artificial intelligence, signalling the increasing automated capability of computers. With its limited, abstract rules chess has been a metric for testing and thinking about automated systems since the original Mechanical Turk automaton in 1770 (a fraudulent chess-playing machine constructed in 1770, which appeared to be able to play a strong game of chess against a human opponent). This and the hidden labour behind AI systems is the starting point for Tasker.
A cross-section of the Mechanical Turk from Racknitz, showing how he thought the hidden operator sat inside as he played his opponent. By Joseph Racknitz - Humboldt University Library, Public Domain, https://commons.wikimedia.org/w/index.php?curid=3266027
Much of the public debate about ‘AI’ and language models like OpenAI’s ChatGPT has focused on the jobs they will apparently automate. But behind all machine learning systems are huge numbers of anonymous people who are employed to label images, text, audio and video to produce annotated datasets, or to test and train machine learning systems.
This huge army of labellers are often called taskers or annotators and work remotely, for low pay, on piece work across platforms like Amazon Mechanical Turk / mTurk or Remotasks.
Tasker challenges our perception of what ‘AI’ is and creates tangible interactions between users and remote taskers, humanising them and highlighting the unseen work that they do.
