Cultural Studies QA Lead - Remote

Key Responsibilities

• Quality monitoring: Spot-check art history/cultural studies items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues.
• Humanities review: Evaluate AI-generated art historical explanations, visual analyses, cultural comparisons, museum-style descriptions, critical interpretations, and context summaries for accuracy and nuance.
• Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and art history/cultural studies-specific review standards.
• Question handling: Respond to trainer/QA questions clearly and promptly, especially around visual analysis, attribution, periodization, cultural context, interpretive claims, representation, ethics, and rubric interpretation.
• Trainer/QA activation management: DM contributors who are inactive or not working, encourage activation, track follow-ups, and flag availability issues when needed.
• Documentation: Create and maintain art history/cultural studies project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials.
• Onboarding and training: Schedule and run onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and art history/cultural studies-specific review requirements.
• Quality alignment: Ensure all trainers and QAs apply art history/cultural studies review guidelines consistently and understand updates as projects evolve.
• Bias and ethics review: Flag culturally insensitive, Eurocentric, decontextualized, stereotyping, misattributed, or unsupported claims about art, culture, artists, or communities.
• Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for art history/cultural studies AI training projects.

About the role

In this hourly, remote contractor role, you will work as an Cultural Studies Quality Assurance Lead to oversee quality, consistency, and trainer performance across art history, visual culture, cultural studies, and humanities AI training projects. You will review AI-generated art history/cultural studies content and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure that all contributors follow the expected quality standards.