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A mother’s health shapes her child’s future, yet gender bias, poor nutrition, and weak policies put millions at risk. Urgent action is the need of
AI मॉडेल ही सामाजिक-तांत्रिक उत्पादने आहेत जी अनेकदा ऐतिह�
AI models are socio-technical products that often reflect historical and socio-political biases. As AI development is largely Western-led, addressing
Closing the gender data gap will enable more effective policymaking, driving significant advancements in gender equality and contributing to broader s
डिजिटल क्रांतीमुळे महिलांच्या आर्थिक सहभागासाठी संधीं�
The digital revolution opens new avenues for women's economic participation, however, to ensure true inclusion, this revolution must be steered by gen
एआय विकसित करण्याच्या प्रक्रियेत, त्याच्या डिझाइनपासून
The AI development process from design to deployment perpetuates gender bias. Future legislation should recognise these gender-based risks to mitigate
Concerted efforts need to be undertaken to close the gender data gap before gender bias becomes an inextricable part of emerging generative AI ecosyst
Historically, the values of gender-caste-based minorities have been systematically kept aside from being even counted, and this bias leads the prior data to be gender-biased or rather gender-invisible.
The growing socialisation with female virtual assistants in AI is rapidly diminishing the significance of women to 'a gendered female who responds on-demand'.
Rapid advancements in medicine and falling fertility rates have contributed to the rise in the population of India’s older adults in recent decades. This demographic and epidemiological shift has a gendered impact: A higher proportion of women over the age of 60, compared to their male counterparts, suffer from Non-Communicable Diseases (NCDs) such as diabetes, hypertension, heart and bone diseases, cancers, cognitive decline, and depression. T
भारत सरकारच्या सरोगसी विधेयकामधील त्रुटी, त्यातून उत्पन्न झालेल्या लिंगभावविषयक समस्या आणि त्यासंदर्भात आवश्यक असलेल्या सुधारणा यांची चर्चा करणारा लेख