The New School Archives Digital Collections

Parsons School of Design MFA Design and Technology program theses2019 ➔ DAIQUAN

Thesis


Related people/organizations

Jason Agyekum (designer)
Katherine Moriwaki (thesis advisor)
Jessica Marshall (thesis advisor)

Date

May 21 2019

Description

What does the future feel like when we are judged and discriminated against by machines? What happens when we recognize the discrimination but don’t do anything to correct it? If people cast judgement on me based on what I look like and wear, how would a machine treat me? DAIQUAN is an installation that emulates the possible dangers of machine learning when fed biased information. In recent years machines have been becoming more connected and getting smarter due to advancements in data science and neural networks. But, they are also known to displaying acts of discrimination to minorities due to the biased datasets they are trained on. The goal of this project is to highlight and stress the importance of human bias in datasets when it comes to the future of implementing artificial intelligence.

Identifier

PC020402_2019_agyej484

Citation

Jason Agyekum. DAIQUAN. May 21 2019. Parsons School of Design MFA Design and Technology program theses; 2019. New School Archives and Special Collections Digital Archive. Web. 20 Sep 2019.

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