Theme: Centering race, culture, and intersectional approaches in tech

Location: Long Beach, CA

Date: Monday, August 7, 2023

Overview

KDD 2023 EDI Day is a day-long event co-located with ACM SIGKDD 2023. Through talks, panels, and discussions, this event will:
1. cover various topics related to shifting power to marginalized communities in  AI,
2. bolster conversations about DEI in academia and industry.

Some topics include decolonizing methodologies, pivoting conversations from "bias" to power, subjugated epistemologies of trust, and structural barriers faced by marginalized AI researchers. The panel strives to bridge perspectives across industry/academia, positions of seniority, methodologies, and more! We also aspire to push beyond existing conceptualizations and operationalizations of trustworthiness in AI. Please join us!

The overarching goal of EDI Day is to bridge perspectives across industry and academia to foster deep-level conversations of what it means to build technology that is truly accessible across racial position and cultural lived experience, including consideration of intersectionality. Speakers and panelists will discuss theoretical considerations and practical suggestions for building and/or refining tech that is responsive to the needs of diverse communities.

Schedule
* all times are local (Pacific time)

09:00 AM - 09:10 AM Introduction
Arjun Subramonian, Christina Chance
09:15 AM - 10:15 AM Keynote
Elaine Nsoesie
10:20 AM - 11:00 AM Panel: Practical suggestions for building tech that responds to the
needs of diverse communities.
Serina Chang, Arnav Kumar,  Erika Torres, Christina Chance
11:00 AM - 11:15 AM [Break]
11:15 AM - 12:00 PM Discussion in breakout groups
12:00 PM - 12:20 PM Sponsor videos
12:20 PM -  12:30 PM [Break]
12:30 PM - 2:00 PM Industry Women of KDD Lunch + Sponsor spotlights

Sponsors

Speaker Bios

• Elaine O. Nsoesie (she/her)  is an associate professor at the Boston University School of Public Health, the faculty lead of the Racial Data Tracker at the Center for Antiracist Research at Boston University and a senior advisor to the Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity (AIM-AHEAD) at the National Institutes of Health (NIH). Her research is currently focused on the use of data science methods to study the impact of policy on racial health inequities. She also studies bias in health data and algorithms and works to increase representation of communities underrepresented in data science.

• Serina Chang (she/her/hers) is a final year PhD student in Computer Science at Stanford University. Her research develops methods in network science and machine learning to tackle complex societal challenges, with an emphasis on incorporating human behavior into computational models and reducing disparities in public health.

• Dr. Erika Torres (PhD) (she/hers/ella) is a licensed bilingual psychologist, educator, and scientist turned clinical program/product manager in mental health tech. She is passionate about the intersection between the use of tech for the greater good, health equity and DEAIB. She is currently a Sr. Manager for AbleTo/Optum/United Health Group leading bilingual and culturally responsive clinical program (product) development and health equity efforts in the mental health tech space. She is responsible for mental health clinical and coaching telehealth programs/products that serve those experiencing moderate to severe symptoms.

• Arnav Dev Kumar (he/him) is a rising third-year Computer Science student at UCSB, and his interests at large include, but are not limited to AR/VR for education, data analytics, systems engineering, and cybersecurity. His current research project focuses on inclusive virtual reality gaming for elementary English language learning, where he is a data analyst and cloud backend developer.

• Christina Chance (she/her/hers) is a first year PhD student in the UCLA NLP lab where her work focuses on fairness and ethics with a special interest in content moderation and low-resource languages. Outside of her research, she is interested in the recruitment and retention of marginalized communities in the computer science and technology field.

Organizer Bios

• Anaelia Ovalle (they/them) is an Afro-Caribbean and non-binary Computer Science PhD Candidate at the University of California, Los Angeles. Their research operates at 2 resolutions: (1) inclusive natural language processing (2) critically centering the socio-technical milieu these language technologies operate within to improve algorithmic fairness processes and design.

• Arjun Subramonian (they/them) is a Computer Science PhD student at the University of California, Los Angeles. Their research focuses on inclusive graph machine learning and natural language processing, including fairness, bias, ethics, and integrating queer perspectives. They are further a core organizer of Queer in AI.

• Christina Chance

Contact: EDI2023 [at] kdd [dot] org