Abstract

Online hate targeting women and female-passing individuals is a growing issue that discourages participation in digital spaces and threatens online safety.

This paper explores two AI-driven strategies to combat sexism and misogyny by integrating insights from existing research and tools. The first approach, Content Shield, automatically detects and filters offensive comments, reducing users’ exposure to harmful content. The second, Counter Narratives, generates AI-driven responses to challenge and mitigate hateful messages. Qualitative user testing demonstrates that both strategies are intuitive and contribute to fostering safer and more inclusive online environments.

Keywords Online Hate against Women, Social Media, AI-driven Approaches, Responsible AI, Role of Designers, Interface Prototypes

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Conclusion

The course once again highlighted the importance of designers coming together as a community to address complex and pressing issues of our time and to contribute to meaningful solutions. I really enjoyed diving deeper into the topic of Responsible AI and exchanging thoughts and ideas with others. Even though my project is just a first step into this challenging field, I have gained valuable insights into the responsibility of the design discipline and my specific topic.