Kindly generate 10 purely qualitative research topics that has not been research on for the past 12 years for Artificial Intelligence (AI) & Machine Learning (ML)

Identifying purely qualitative research topics in the realm of Artificial Intelligence (AI) and Machine Learning (ML) that have not been explored in the last 12 years can be challenging due to the rapid pace of technological advancement and research. However, here are ten potential topics that might fit the criteria:

**The Human-AI Collaboration Experience**: Explore how different professional sectors perceive and experience collaboration with AI systems — focusing on emotional and psychological aspects, trust-building, and team dynamics.

**Cultural Perceptions of AI Ethics**: Investigate how diverse cultural backgrounds influence perceptions and discussions around AI ethics, including the acceptance of biases and accountability in AI systems across different cultures.

**Narratives of AI in Popular Media**: Analyze how artificial intelligence is portrayed in literature and film, focusing on themes of identity, agency, and the future of work to understand societal attitudes toward AI.

**User Experience of AI-based Decision Support Systems**: Qualitatively examine how users in various fields (e.g., healthcare, finance, education) interact with AI decision support tools, focusing on usability, decision-making processes, and trust.

**Impact of AI on Professional Identity**: Explore how the integration of AI tools in various professions (e.g., journalism, law, finance) impacts individuals' sense of professional identity and job satisfaction.

**Public Discourse on AI Regulations**: Investigate the qualitative aspects of how community leaders and citizens discuss and conceptualize AI regulations and governance—focusing on fears, hopes, and misconceptions.

**AI Literacy Among Different Demographics**: Examine the narratives surrounding AI education and literacy among various demographic groups, including marginalized communities, and how these narratives influence access and engagement with technology.

**The Role of AI in Creative Processes**: Qualitatively analyze how artists, writers, and musicians perceive and incorporate AI tools into their creative processes, including the implications for originality and authorship.

**Intersections of AI and Mental Health**: Explore the qualitative experiences of individuals using AI-driven mental health apps and chatbots, focusing on therapeutic outcomes, personalization, and emotional responses.

**Feminist Perspectives on AI Development**: Investigate how feminist scholars and activists perceive the role of gender in AI development, including potential biases in algorithms and the portrayal of women in AI-related narratives.

These topics provide a foundation for exploring the qualitative dimensions of AI and ML in various contexts, emphasizing human experiences, perceptions, and narratives that may not have been extensively researched recently.