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Design justice is the ethical and inclusive approach to designing products or systems that address and mitigate historical inequalities to ensure fair and equitable outcomes for all users. The article covers an overview of design justice, the 10 Principles of Design Justice, challenges in equitable design, and applications of design justice in Artificial Intelligence and Human-Computer Interaction.

Overview

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Design justice is defined by experts in interdisciplinary fields as a theory and practice of designing with action to mitigate risks and harms toward the marginalized, and oppressed. This action is taken by moving away from the idea of “designing for good” and moving towards designing with input from the affected communities.[1][2] Design Justice aims to balance the distribution of risks, harms, and benefits among users through the design process, by including people whose lives will be impacted by the product or system in addition to technical experts in the design process.[3][4] Design justice is built upon ten principles to ensure that communities can come together to lead to more equitable products.

Below are the 10 design justice principles:[5]

  1. Use design to sustain, heal and empower communities, as well as to seek liberation from exploitative and oppressive systems.
  2. Center the voices of those who are directly impacted by the outcome of the design process.
  3. Prioritize design’s impact on the community over the intentions of the designer.
  4. View change as emergent from an accountable, accessible, and collaborative process rather than as a point at the end of a process.
  5. See the role of the designer as a facilitator rather than an expert.
  6. Believe that everyone is an expert based on their own lived experience and that all people have unique and brilliant contributions to bring to a design process.
  7. Share design knowledge and tools with communities.
  8. Work towards sustainable, community-led and -controlled outcomes.
  9. Work towards non-exploitative solutions that reconnect to the earth and each other.
  10. Before seeking new design solutions, look for what is already working at the community level. Honor and uplift traditional, indigenous, and local knowledge and practices.

Challenges

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Equitable design in technology has been hard to achieve because of the overwhelming presence of heterosexual white men in product design leadership.[6] Designers in the tech industry stand in for the promise of innovation and entrepreneurialism, but also are part of one of the most unequal industries, with Black women only making up 1.7% of the tech workforce.[7] In an industry where meaningful efforts to diversify are not made and structural inequality is rarely mentioned or challenges, design justice is an important call to rupture current design practices.

Artificial intelligence and machine learning

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Design justice in artificial intelligence is the ethical and inclusive approach to designing and building artificial intelligence technology, aligning with the 10 principles outlined previously. It emphasizes the need to consider ethical, cultural, and social dimensions of designing technology to create a more equitable and overall positive impact on society.[8]

Designing artificial intelligence products

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Design justice in artificial intelligence aims to transform the design process of artificial intelligence products. Currently, the design of artificial intelligence is inequitable because of who has power in the design process, who the users of the technology are imagined to be, and where the design is taking place.[8] The benefit of designing artificial intelligence technologies flows to individuals who traditionally have more power in the design process and harms individuals who are already marginalized.[9] Design Justice in artificial intelligence aims to bridge the gap between the two groups and deconstruct the power dynamic in the artificial intelligence design process.[3]

Artificial intelligence products are designed using training data, which depends on human efforts to learn and deliver algorithmic results.[10] A specific case would be in resume screenings. Artificial intelligence has been used in resume screenings to automate and speed the process of resume screenings, helping employers find candidates faster, making sure qualified candidates are notified and making the hiring process smoother on both sides.[11] However, if the resume dataset contains past biases in the company, these biases will continue to be reflected by the artificial intelligence resume screening. Amazon had used a machine learning resume tool until machine learning specialists found that the tool was discriminating against women because the models were trained on resumes submitted to the company over a 10-year period, mostly coming from men.[12] Design justice could be used in this context to evaluate the dataset and make sure it adheres with Amazon’s goals to have a diverse workforce.

Transition to artificial intelligence products

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In addition to the design process of artificial intelligence products, design justice principles can be applied to how artificial intelligence products are used, as many industries transition to using artificial intelligence products.[13][14] For example, consider the importance of design justice in the process of transition to using artificial intelligence products in mental healthcare.[13] Researchers advocate for a more ethical and well-rounded approach to the implementation of artificial intelligence in the healthcare industry to make sure that all users of the product, the patients, are a part of the decision making process in the transition to using artificial intelligence in healthcare.[13] As artificial intelligence products and usage increases, experts in the field call to using design justice principles not only in the design of the products, but in the implementation of them as well.[15]

Human-computer interaction

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Design justice in Human-Computer Interaction (or HCI) is a branch of design justice focused on the principles of design for digital interfaces.[16] Considering issues of power, privilege, and access within the design of digital products, interfaces, and systems is the cornerstone of HCI-centric design justice.[16] Not only does design justice in HCI include the development of accessible websites and interfaces, but it also reexamines the core principles and practices that HCI designers rely on.[4]

User interface and experience

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Design justice has become increasingly prevalent in the user interface/user experience (UI/UX) field in recent years.[17] The goal of design justice in UI/UX is to increase the usability of interfaces and products by focusing on the needs of marginalized communities in the design process.[18]

Design justice principles encourage designers to involve the user in the design process more in order to work towards this goal. One such strategy of increased user involvement is participatory design. This entails finding a set of users to test the product, surveying them on their experience with the product, and adjusting the product design to accommodate for feedback. For this strategy to follow design justice principles, the pool of users should include representation for various marginalized communities.[17] This approach can be helpful in identifying areas of design to increase inclusivity. In a case study from the University of Illinois Champaign-Urbana, designers were able to create an interface inclusive of color-blind individuals after receiving feedback from their user pool.[19] Another strategy, co-design, involves users from marginalized communities throughout the development process. In contrast to participatory design, users actively participate in the design lifecycle and directly contribute their experiences to the product. This lessens the divide between designers and users, allowing both to have equal ownership and contribution to the product. Co-design also encourages designers and users alike to recognize and understand their identity and how it may impact the product outcome. The core of both participatory design and co-design strategies is for designers to be empathetic and educated in order to empower all users through the use of interfaces and technological experiences.[17]

Principles

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Bu combining design justice with HCI principles, designers and researchers can contribute to technology that is not only usable but also promotes social justice, inclusivity, and intersectionality.[4] The goal of design justice within the HCI field is to generate social change through digital platforms.[4] Sasha Costanza-Chock outlines the problems within the field of HCI and how designers can address them in their article "Design Justice: towards an intersectional feminist framework for design theory and practice". One of the problems in interface design is inclusivity. Most designers make an assumption when creating interfaces: their users have privileges such as U.S. citizenship, English language proficiency, access to broadband internet, a smartphone, no disabilities, and more.[4] The principles of HCI promote the continuous iteration and testing of designs with real people, and design justice suggests that including the intended audience of an interface in the design process will aid in the creation of inclusive interfaces.[20]

Another issue that Costanza-Chock highlights is intersectionality. When designers consider equality during development, most employ a single-axis framework, leading to most interfaces ignoring the complex identities of marginalized peoples.[4] HCI principles encourage the early determination of the users and tasks that a user interface will support, and principles of design justice, like principles 2 and 6, place the unique identities of individuals at the forefront of creating user interfaces. Costanza-Chock also emphasizes the affect that design justice has on the empowerment and participation of marginalized peoples. Many organizations have been created to support gender equality in STEM fields.[4] Design justice recognizes that employment in paid design fields for marginalized people is important, but that other aspects of design, like the intended beneficiaries of design, are equally as important.[4][16]

References

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  1. ^ Costanza-Chock, Sasha (March 2020). Design Justice. The MIT Press.
  2. ^ Zielke, Julia; Morawe, Jan Marc; Aktan, Alev Nazli; Miani, Céline (2023-11-24). "'That Sounds to Me Like You Are Making This Too Complicated …': Reflections on a Social Media Recruitment Effort for a Study on Masculinities and Contraception". Qualitative Health Research. 34 (4): 280–286. doi:10.1177/10497323231203631. ISSN 1049-7323. PMID 37997352.
  3. ^ a b Katyal, Sonia; Jung, Jessica (Jan 3, 2022). "The Gender Panopticon: AI, Gender, and Design Justice". UCLA Law Review.
  4. ^ a b c d e f g h Costanza-Chock, Sasha (28 June 2018). "Design Justice: towards an intersectional feminist framework for design theory and practice". Design Research Society. DRS2018: Catalyst. 2. doi:10.21606/drs.2018.679. hdl:1721.1/136329. ISBN 978-1-912294-27-5.
  5. ^ "Design Justice Network". Design Justice Network.
  6. ^ "Diversity in High Tech". www.eeoc.gov. Retrieved 5 December 2023.
  7. ^ Jackson, Ashton (24 February 2022). "Black employees make up just 7.4% of the tech workforce—these nonprofits are working to change that". CNBC. Retrieved 5 December 2023.
  8. ^ a b Costanza-Chock, Sasha (27 July 2018). "Design Justice, A.I., and Escape from the Matrix of Domination". Journal of Design and Science. 3 (5). doi:10.21428/96c8d426. Retrieved 5 December 2023.
  9. ^ Kalluri, Pratyusha (2020). "Don't ask if artificial intelligence is good or fair, ask how it shifts power". Nature. 583 (7815): 169. Bibcode:2020Natur.583..169K. doi:10.1038/d41586-020-02003-2. PMID 32636520.
  10. ^ Megorskaya, Olga. "Council Post: Training Data: The Overlooked Problem Of Modern AI". Forbes. Retrieved 6 December 2023.
  11. ^ Hu, James. "Over 98% of Fortune 500 Companies Use Applicant Tracking Systems (ATS) - Jobscan Blog". Jobscan Blog. Retrieved 6 December 2023.
  12. ^ Dastin, Jeffrey. "Amazon scraps secret AI recruiting tool that showed bias against women". Reuters. Retrieved 6 December 2023.
  13. ^ a b c Zidaru, Theodor; Morrow, Elizabeth (August 2021). "Ensuring patient and public involvement in the transition to AI-assisted mental health care: A systematic scoping review and agenda for design justice". Health Expectations. 24 (4): 1072–1124. doi:10.1111/hex.13299. PMC 8369091. PMID 34118185.
  14. ^ Obermeyer, Ziad; Emanuel, Ezekiel J. (2016-09-29). "Predicting the Future — Big Data, Machine Learning, and Clinical Medicine". New England Journal of Medicine. 375 (13): 1216–1219. doi:10.1056/NEJMp1606181. ISSN 0028-4793. PMC 5070532. PMID 27682033.
  15. ^ Bohr, Adam; Memarzadeh, Kaveh (2020-01-01), Bohr, Adam; Memarzadeh, Kaveh (eds.), "Chapter 2 - The rise of artificial intelligence in healthcare applications", Artificial Intelligence in Healthcare, Academic Press: 25–60, doi:10.1016/b978-0-12-818438-7.00002-2, ISBN 978-0-12-818438-7, PMC 7325854
  16. ^ a b c Dombrowski, Lynn; Harmon, Ellie; Fox, Sarah (2016-06-04). "Social Justice-Oriented Interaction Design: Outlining Key Design Strategies and Commitments". Proceedings of the 2016 ACM Conference on Designing Interactive Systems. ACM. pp. 656–671. doi:10.1145/2901790.2901861. hdl:1805/12029. ISBN 978-1-4503-4031-1.
  17. ^ a b c Caruso, Christine; Frankel, Lois (2010). "Everyday People: Enabling User Expertise in Socially Responsible Design" (PDF).
  18. ^ Rose, Emma J.; Edenfield, Avery; Walton, Rebecca; Gonzales, Laura; McNair, Ann Shivers; Zhvotovska, Tetyana; Jones, Natasha; de Mueller, Genevieve I. Garcia; Moore, Kristen (2018-08-03). "21". Social Justice in UX: Centering Marginalized Users. SIGDOC '18: Proceedings of the 36th ACM International Conference on the Design of Communication. ACM. pp. 1–2. doi:10.1145/3233756.3233931. ISBN 978-1-4503-5935-1.
  19. ^ Han, Yingying; Markazi, Daniela M.; Narang, Samual (2021-11-08). "Outlining a design justice-based social media website for university students in the age of COVID-19". 19th CIRN Conference 2021: Communities, Technology and This Moment. hdl:2142/114351.
  20. ^ Nkonde, Mutale. "Automated Anti-Blackness: Facial Recognition in Brooklyn, New York". Harvard Kennedy School Journal of African American Policy (2019–20): 30–36.
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