Using African Fashion to Correct AI Bias

AI
Seidenberg School of CSIS

Meet Christelle Scharff, PhD, a computer science expert focusing on the limitations and biases of AI systems. She and her team are tackling the intersection of AI and African fashion to explore the impact of diverse datasets.

multicolor ai generated geometric repeating pattern
stylized portrait of pace professor christelle scharff
Johnni Medina

Artificial intelligence (AI) and Machine Learning (ML) are constantly in the headlines, from advancements in access to ethical concerns about the impact on human labor and specific groups. For computer science experts like Christelle Scharff, PhD, the focus lies less on what AI can and will do and more on its current limitations, especially when it comes to incomplete datasets that illustrate bias in these AI systems.

Scharff has been at Pace for 22 years as a professor of computer science, and she’s currently associate dean of the Seidenberg School of Computer Science and Information Systems. When she began exploring AI as a PhD student, she described her work as mostly “theoretical”, working on theorem proving problems. She was fascinated with studying how a computer can understand mathematical and logical concepts like deduction rules, equality, commutativity, and associativity. As AI technology developed, so did her interest in machine and deep learning and also in mitigating potential biases in AI. Scharff’s research has been focusing on Africa since 2009 when she received a grant to work on entrepreneurship and mobile app development in Senegal. Since that time, more opportunities to study AI in Africa arose and now Scharff and her students are continuing to explore how to ensure AI keeps up with growing global inclusivity.

As AI technology developed, so did her interest in machine and deep learning and also in mitigating potential biases in AI.

Two of her most recent projects with PhD students, Kaleemunsia and Krishna Bathula, center on African fashion. The first sought to expand the scope of a popular fashion dataset called Fashion MNIST. Datasets are the pillars of the AI movement, and safeguards are required to create and use datasets.

While Fashion MNIST is able to identify certain garments, fashion items that fall outside its very limited descriptions (which mostly fall under Western terminology and trends) are easily misclassified. “If you ask this dataset to recognize a sari, it’ll probably tell you it’s a dress,” Scharff says as an example. She explains that like with the sari, this dataset doesn’t know how to identify specific African fashion items. “Because I worked in Africa as a Fulbright Scholar, I focused this project on African fashion and involved graduate students from Senegal.” The plan was to create a dataset to address African fashion and recognize two popular Senegalese garments: boubou and taille mame. To put the importance of incorporating a wider, more global language into these AI models, Scharff explains, “If you were to go to the tailor and say, ‘I want a dress’ the tailor wouldn’t know where to start.”

"The other step in any project related to AI is that you need to ask the subject matter experts."

—Scharff

The other African fashion project Scharff and her team worked on is likely more tangible to those outside of the AI community. They worked to recreate a popular pattern in Africa called wax—a colorful, geometrical pattern that is often shined with wax.

The team collected a dataset of around 5000 free wax patterns and created new, satisfying patterns that are AI-generated. From there, the team printed select patterns and partnered with local artisans in Senegal to create fashion items including bags. The dataset was built to generate a variety of patterns. To get a proper sample, one needs upwards of 10,000 different images, Scharff estimates. If a dataset had mostly blue patterns, the generative patterns would stick mostly to blue, or if there weren’t enough floral images, they would need to add those images to the dataset to get them. The very nature of exclusion changed what the AI could produce, demonstrating the need to expand these datasets to reflect the world as it is, not just what has been inputted thus far.

Her students are hard at work, building out that dataset and corresponding models to generate interesting wax patterns.

"My biggest concern is diversity biases. But I think right now the discussion is much more open, at least everybody is aware of the issue. So, then it's a question of having the policies, tools, processes, practices to make it completely happen."

—Scharff

And for those worried about the AI takeover of jobs? “The other step in any project related to AI is that you need to ask the subject matter experts,” Scharff says. She explains that once these patterns were created, they need to be reviewed by fashion experts to understand what was working and what wasn’t. A computer can create a pattern, but it can’t (as of yet) also categorize it as what is fashionable for everyday wear, artistic, or what kind of aesthetic category it belongs to.

Scharff is excited for where AI is going, and how ubiquitous it’s becoming. Her greatest concerns are exactly what her work is doing, balancing datasets to be representative and diverse. “My biggest concern is diversity biases. But I think right now the discussion is much more open, at least everybody is aware of the issue. So, then it's a question of having the policies, tools, processes, practices to make it completely happen.”

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Female Publishing program alum from Pace University, Mae Martinez, standing on the Brooklyn Bridge
Mae Martinez ’20, ’21

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Female Publishing program alum from Pace University, Asante Simons
Asante Simons ’17

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Female Publishing program alum from Pace University, Sabeen Aziz, standing near water
Sabeen Aziz ’16

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Currently Studying: MBA in General Business

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Pronouns: She/Her

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I was able to gain confidence in my work thanks to group projects and encouragement from my professors, which has and will help me be successful in my current and future professional experiences and internships. I would specifically like to thank Professor Chris Ramos for proactively helping me in my internship search. He went through my resume and contacted people in his network who he thought would be a match with my skills and knowledge.

What attracted you to this internship?

After completing my undergraduate degree in film studies with a minor in entrepreneurship at The New School, I became even more passionate about film and the many different steps it takes to develop and produce a film. Additionally, upon graduating from the Lubin School of Business with my MBA, I will pursue a career in film production. The knowledge that I am accumulating during this internship will enable me to understand the business aspect of film production and how it can affect or benefit the creative aspect of a project. Becoming a film producer is my ultimate career goal, so having direct contact and access to someone currently in that role allows me to obtain real knowledge on this position.

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A typical day with producer Marisa Vitali and Emergent Pictures includes going through a collaborative board and completing the tasks that are required of me for that week. Every Monday, Marisa and I meet to go over the status of my tasks, any questions about what we have worked on together, and the different strategies that are required for specific aspects of the projects that we are working on together.

What has been the highlight or most enjoyable aspect of your internship so far?

While there have been many highlights during this experience so far, I am most enjoying having an ongoing dialogue with Marisa about my career goals and how she can best cater this internship to me to help me gain as much knowledge about this field and position as possible.

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This experience has made me even more interested in this field. I cannot wait to start working on my own projects where I will be able to handle production.

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This experience allows me to fully grasp the area of film I would like to work in after graduating in May 2024. Next semester, I will be taking an arts and entertainment management course that will reinforce the knowledge that I have gained during this internship and will prepare me for my job search.

Regardless of the industry you are looking to pursue an internship in, make sure to take advantage of every opportunity that arises... Having experience across many industries will help you better understand what interests you and what doesn't.

Do you have any advice for other Lubin students who would like to pursue an internship in the future?

Regardless of the industry you are looking to pursue an internship in, make sure to take advantage of every opportunity that arises. This will help you form personal communication skills while also allowing you to develop an understanding of how to navigate your upcoming professional life. Having experience across many industries will help you better understand what interests you and what doesn't.

Connect with Eden:

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