主  题

Inclusive AI: Bridging the Ontological Gap between Design and Data

时  间
18:00 - 19:30
Thursday April 25th, 2024

地  点
同济大学设计创意学院 鱼缸报告厅
Aquariums Lecture Hall, College of Design and Innovation

Tencent Meeting
会议号 503909453 
密码 666666

宗诗婷 博士
Priscilla Chueng-Nainby

Priscilla Chueng-Nainby博士是一位经验丰富的数字服务设计专家,拥有超过25年的设计经验。她的设计之旅始于90年代,尽管最初攻读计算机科学学位,但Chueng-Nainby博士的求知欲驱使她进一步探索设计的复杂性。多年来,她在服务设计、工业设计和用户体验/用户界面(UX/UI)设计方面不断积累经验,拥有协同设计博士学位的她致力于推动设计方法的发展,特别是关于信息学和医疗保健领域,重点关注人工智能和数据的融合。作为一名知名设计机构的客座教授,她将自己的知识传授给下一代设计师,强调人工智能驱动的设计解决方案的重要性。


Dr. Priscilla Chueng-Nainby is a seasoned digital service design specialist with over 25 years of experience. Her design journey began in the 1990s, Despite initially pursuing a degree in computer science, Dr. Chueng-Nainby's insatiable curiosity led her to explore the intricacies of design further. Over the years, she has honed her expertise in service design, industrial design, and user experience/user interface (UX/UI) design. With a Ph.D. in co-design, she is dedicated to advancing design methodologies, particularly in informatics and healthcare, with a focus on the intersection of AI and data. As a visiting professor at esteemed design institutions worldwide, she imparts her knowledge to the next generation of designers, emphasizing the importance of AI-driven design solutions. 

In consultancy roles, Dr. Chueng-Nainby has led digital transformation initiatives for UK government departments, including pioneering projects for the National Health Service and the Cabinet Office, leveraging AI and data analytics. Her leadership skills, coupled with proficiency in budgeting, business strategy, and mentorship, have been pivotal in her success. Committed to positive social impact, she leverages her expertise for societal betterment, harnessing the power of AI and data to create inclusive and human-centric design solutions.




In this thought-provoking presentation, we delve into the intricate relationship between Design Ontology, Data, and Artificial Intelligence (AI), shedding light on the significant disparities that exist between traditional design principles and the ever-evolving landscape of AI technology. Our exploration begins with a critical examination of the pervasive issue of bias and discrimination within AI algorithms, particularly as it pertains to marginalized communities. We underscore the pressing need for social innovation to address these challenges head-on.

Central to our discussion is the adoption of co-design methodologies, which serve as a powerful tool for gathering insights directly from these communities, thereby informing more inclusive and equitable AI development practices. Moreover, we confront the inherent disparities between community insights data and AI training data, highlighting their pivotal role in machine learning and language model processing.

Join us on this transformative journey as we advocate for a paradigm shift towards AI development that is not only more inclusive and equitable but also fundamentally human-centric. By fostering a culture of transformative innovation, we can challenge systemic biases embedded within technological systems, ultimately paving the way for a more just and equitable future.

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