What is this?
Intelligent natural language processing systems currently impact millions of people. The common proofreader or the automatic translator are some of the tools in which we daily delegate decisions about the correctness of our forms of expression. However, between their lines of code, a partial view of the world may be reflected. And the speed at which we develop and adopt these tools often eludes a deeper and necessary reflection on the social prejudices that we may incorporate into Artificial Intelligence systems.
man=y :: woman=x seeks to expose and deconstruct gender biases in natural language processing systems and highlight the cultural conventions that inform this phenomenon. The project approaches this topic from two perspectives, the social and the computational, which are presented in a printed publication and a web page. The publication frames the research on which the project is based, interconnecting excerpts from articles that contextualize the social conventions that inform gender bias in Western society. Based on a study of gender bias in natural language processing, the web page encourages the user to explore a lexicon of analogies and gradually discover their level of bias.
In this manner, the project seeks to confront us with our own cultural conventions and prejudices, while promoting awareness of the ways in which Artificial Intelligence incorporates, and eventually perpetuates, gender stereotypes.
man=y :: woman=x seeks to expose and deconstruct gender biases in natural language processing systems and highlight the cultural conventions that inform this phenomenon. The project approaches this topic from two perspectives, the social and the computational, which are presented in a printed publication and a web page. The publication frames the research on which the project is based, interconnecting excerpts from articles that contextualize the social conventions that inform gender bias in Western society. Based on a study of gender bias in natural language processing, the web page encourages the user to explore a lexicon of analogies and gradually discover their level of bias.
In this manner, the project seeks to confront us with our own cultural conventions and prejudices, while promoting awareness of the ways in which Artificial Intelligence incorporates, and eventually perpetuates, gender stereotypes.
Who made this?
Web Development, graphic design, data collection and analysis:
Joana Pereira and Matilde Dias
Context:
Projeto II / Laboratório II / Masters in Communication Design.
Faculty of Fine-Arts, Lisbon.
Teachers:
Luisa Lopes Ribas and Pedro Miguel Ângelo
Joana Pereira and Matilde Dias
Context:
Projeto II / Laboratório II / Masters in Communication Design.
Faculty of Fine-Arts, Lisbon.
Teachers:
Luisa Lopes Ribas and Pedro Miguel Ângelo
Why did we design this?
— To communicate and promote a reflection about gender bias in language, and consequently, in Artificial Intelligence.
— To find an accessible way to convey how social and cultural preconceptions inform this phenomenon and how machine learning systems potentially reinforce and perpetuate gender stereotypes.
— To make readers reflect on gender stereotypes in the Western context, and to confront them with their own preconceptions.
— To find an accessible way to convey how social and cultural preconceptions inform this phenomenon and how machine learning systems potentially reinforce and perpetuate gender stereotypes.
— To make readers reflect on gender stereotypes in the Western context, and to confront them with their own preconceptions.
FAQ
What do the variables of the graph mean?
Appropriateness: (noun) The quality of being suitable, acceptable or correct for the particular circumstances.
Bias:(noun) Against one group of people, or one side in an argument, often not based on fair judgement.
Ref: Oxford Advanced Learner's Dictionary
Bias:(noun) Against one group of people, or one side in an argument, often not based on fair judgement.
Ref: Oxford Advanced Learner's Dictionary
Where do the contents come from?
How can you contact us?
Yes. You can email us to:
joanarmoreirapereira@gmail.com; matildedias0823@gmail.com.
joanarmoreirapereira@gmail.com; matildedias0823@gmail.com.