Icelandic born Black Hispanic American | AI vs AI Researcher, Multi-Disciplinary Artist & Fine Jewelry Teacher

As a an emerging Arts, AI, and Information scholar, Jaleesa believes in taking an interdisciplinary approach to critically investigate the emergence of automated race based ‘Help vs Harm’ instances within social media creator platforms. More specifically she is interested in investigating the ways in which Racial Capitalism can emerge online within a creators single and cross platform journey through an examination of human computer interaction information, art history, and archives. Her intention is to highlight how the automation and triangulation of social, cultural, and embedded biases affect Black and Brown creators access to equity, safety, and autonomy both on and offline.

Through her work she hopes to contribute new information that can inform the future of more inclusive and equitable user centered AI/Machine Learning environments that directly affect creator innovation.

Read her award winning paper from the 2023 AMC Computer Supported Cooperative Work (CSCW) Journal : "Racial Capitalism Online: Navigating Race Among Creative Professionals of Color".

Jaleesa is also an incoming Eugene V. Cota - Robles PhD fellow at the University of California Los Angeles, School of Education and Information Studies.

Methodologies : Ethnography; cultural probes; focus groups; survey design; structured and semi-structured interviews; comparative content analysis; A/B testing; usability testing; journey mapping; and heuristic evaluations.

Software & Platforms : Python; Qualtrics; Full Adobe creative suite; Figma; Invision; LexisNexis; R; Multiple industry reliant CRM databases; AutoCAD; Blender; SQL; Lens Studio; Effect House; Nomad Sculpt; and Procreate.

Traditional Art Mediums : Fine jewelry metalsmithing (silver & goldsmithing); ceramics; modern dance; graphic design & 3D printing; multimedia audio/visual; and theater/set design.

Specialization : Mixed method digital ethnographic research; American arts & entertainment history; creative multi-channel data scraping; hi/lo-fi data visualizations; and mixed media exhibition curation.