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Deep (Blue) Fake

Deep (Blue) Fake delves into the intricate relationship between artificial intelligence and human labour, examining the hidden complexities behind seemingly automated tasks.

Deep (Blue) Fake

‘Deep Blue Fake’ is an interactive artwork that draws inspiration from the documentary 'Game Over: Kasparov and the Machine.' It delves into the intricate relationship between artificial intelligence and human labour, examining the hidden complexities behind seemingly automated tasks.


The artwork takes its cues from the historic 1997 chess match between Russian Grandmaster Garry Kasparov and IBM's chess-playing computer known as 'Deep Blue.' This monumental event symbolised the ongoing battle between man and machine, as Deep Blue's victory over one of humanity's intellectual titans suggested that AI was rapidly approaching human intelligence.


Image of Garry Kasparov playing IBM’s supercomputer ‘Deep Blue’ during the 1997 rematch. Image source: https://www.kasparov.com/timeline-event/deep-blue/ 


‘Deep Blue Fake’ reflects elements of the circumstances faced by Kasparov during the match. It features a specially designed chessboard that invites participants to engage with an apparently independent ‘AI’ opponent, whose pieces move autonomously across the board.


As visitors make their moves on the chessboard, their opponent's pieces will respond, strategizing and countering their actions in real-time. However, behind the scenes, the movements of these pieces are orchestrated by the contributions of multiple human workers connected through MTurk. MTurk, short for 'Mechanical Turk,' is an online platform where businesses can hire remote workers to perform tasks that computers are presently unable to accomplish.


Screenshot of the custom-made interface shown to remote workers on Amazon’s MTurk platform. Image credit: Artist


The platform's name pays homage to an 18th-century automaton called 'The Mechanical Turk,' which was initially believed to possess chess-playing capabilities until it was revealed to be an elaborate deception, controlled by a person concealed within. MTurk is commonly used to outsource labour-intensive tasks, such as dataset labelling, which are critical for the advancement of machine learning systems, often at low wages.


A cross-section of the Turk from Racknitz, showing how he thought the 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 


The artwork delves into the intricate interplay between artificial intelligence and human labour. It highlights the fact that numerous seemingly automated tasks involve the covert contribution of human workers, shedding light on the hidden complexities and ethical considerations that accompany the fusion of AI and labour. By participating in the game, visitors become part of the exploration of the intricate connection between AI and human labour in the era of artificial intelligence. 


Technical


The system behind the artwork consists of Open Frameworks, Amazon’s MTurk API, Python and Arduino. Addons used in Open Frameworks are: ofxIO, ofxPoco, ofxOSC and ofxSerial. The flow is:


  • openFrameworks generates the virtual board, recording all chess piece locations in a map.

  • The human plays white and makes the first move, recording their move within openFrameworks, which updates the map of chess locations and writes it to a JSON file.

  • openFrameworks calls a Python script, which generates a MTurk hit containing a digitised version of the current gameplay using the updated JSON file. 

  • An MTurk remote worker accepts the hit and chooses the next move of the game.

  • The results are returned to the Python script, which sends the new coordinates to openFrameworks via OSC.

  • openFrameworks updates the location of the chess piece and sends a message with the new coordinates to an Arduino via serial communication.

  • The Arduino moves the MTurks chess piece via a custom made XY table, an electromagnet, motors and drivers.

  • Returns to Player 1.


Credits


Collaborators: Rod Dickinson (UWE Bristol), Claire Reddleman (University of Manchester)

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