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Women for Ethical Artificial Intelligence (W4EAI) 

Dept/Center/Lab: AMMACHI Labs- Amrita Multi Modal Applications Using Computer & Human Interaction

School:

Women for Ethical Artificial Intelligence (W4EAI) 

Amrita Vishwa Vidyapeetham, in collaboration with UNESCO, is spearheading the South Asia Chapter of the Women for Ethical AI (W4EAI) Network to address systemic gender biases in AI and amplify women’s leadership in the region’s AI ecosystem. In collaboration with various entities of the SA Chapter of the W4EAI Network and drawing from Amrita University’s efforts in this domain, the project seeks to develop inclusive, ethical AI frameworks that reflect South Asia’s unique challenges and drive global standards by integrating regional cultural contexts and intersectionalities.  

Objectives: 

  • Ensure equitable participation of women in AI design, development, and governance. 
  • Mitigate biases in AI systems through culturally sensitive, gender-inclusive practices. 
  • Equip women with technical skills and leadership opportunities in AI. 
  • Integrate gender perspectives into national AI strategies and global ethical guidelines. 
  • Create a platform for South Asian women leaders to share insights and innovations. 
Workstream Key Activities Deliverables 
Research & Innovation -Study barriers to women’s participation in AI  -Document AI biases in South Asia -Report on “Gender and AI for South Asia”.  -Regional case studies on AI bias 
Policy & Advocacy -Gender audits of national AI policies  -Advocate for gender-sensitive regulations -Policy briefs for governments.  -Monitoring framework for gender equity metrics 
Inclusion & Equity -Mentorship programs for women in AI  -Hackathons targeting marginalized groups -200+ women trained by 2025.  -3 regional hackathons on gender-inclusive AI solutions 

Research Questions: 

  • Gender Representation in AI: 
  • What systemic barriers exist to women’s participation in AI education and employment?
    • Exploring the nature of career options available for women in the AI domain 
    • Mapping the skill gap and related challenges  
  • How do socio-cultural norms shape gender biases in AI tools, particularly in the context of
    • Identifying the nature and typologies of gender biases in AI? 
    • Reflecting on the impact of social, cultural, and systemic factors on inducing biases in AI? 
  • Policy and Governance: 
  • What are the challenges, gaps, and plausible pathways for gender inclusion in national and regional AI policies? 
  • Adoption of AI Technology: 
  • How effectively do women adopt AI technology, and what strategies can enhance their informed and meaningful adoption of these technologies? 
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