This artwork is an extended version of the former work, Be a Hong Kong Patriot, Part 3 – The Red Scout, adopted for the group exhibition Art Machines – Past/Present, shown in the Indra and Harry Banga Gallery, City University of Hong Kong.
In the Hong Kong Legislative Council election in 2016, a number of pro-democracy law-makers were disqualified from the membership after the oath-taking process, even though they were elected by the Hong Kong voters. In November 2020, four additional members of the Legislative Council were disqualified due to the accusation of not upholding the Basic Law of the Hong Kong Special Administrative Region. Disqualification (DQ) seems to be an effective way to remove council members even though they are lawfully elected. And the criteria of disqualification are subject to interpretation with great controversy too.
The artwork is a speculative response to the DQ incidences and the process. In the age of artificial intelligence, shall we automate the disqualification process? Is it possible to train a piece software to execute the process? To take it to extremes, shall we simplify the process to employ facial recognition technology to do the job?
In a hypothetical situation, the artwork maintains a database of portrait photos of the existing Legislative Council members as of year end 2020. A piece of custom software builds a model of all the facial features extracted from the individual portrait photos, together with information related to the political affiliations of the members. The images are then classified into three categories
- High risk of being disqualified
- Low risk of being disqualified
The Eigenface (average face) of the 3 categories are:
The artwork is equipped with a camera. It will scan the face of the visitor. Upon comparison and matching with the stored data, it will assess the visitor’s risk of being disqualified if he/she would like to run for the Legislative Council election in Hong Kong.
The artwork features a magic mirror that can detect the face of the visitor and determine according to machine learning how likely he/she may be disqualified from running the Hong Kong Legislative Council election. Through the mirror, the visitor’s face will also be transformed into one of the existing Legislative Council member’s face based on a closest match algorithm.
Installation view of the Art Machines exhibition
Two face transformation methods had been experimented with. The first one is the Face Morphing.
The second method is the Face Swapping.
The face matching algorithm is done by the Python scikit-learn library. The following images are demonstration of the matching results.
Finally, the classification and matching details are included in one single interface.
The artwork also summarises the detection and classification statistics in form of a pie chart.
The source code of the project is in the artist’s GitHub repository iFaceDQ. The individual images are, however, not included. They are in the public domain of the Hong Kong Legislative Council website.