The paper critically evaluates the global discourses on algorithmic fairness,reviews key Western literature on artificial intelligence(AI)fairness,identifies twelve documented cases of algorithmic discrimination in We...The paper critically evaluates the global discourses on algorithmic fairness,reviews key Western literature on artificial intelligence(AI)fairness,identifies twelve documented cases of algorithmic discrimination in Western contexts,and extends them for their analytical relevance to non-Western socio-political environments.The study applies these frameworks in particular to the Indian context,and proposes that India’s entrenched socio-cultural structures—caste,religion,language,regional identity,and minority status—tends to misalign with Western paradigms of fairness.The proposed study identifies identity-specific factors unique to India that are likely to contribute to algorithmic oppression if unaddressed.A critical policy analysis of major documents shaping India’s AI and digital governance landscape reveals that these critical factors remain largely unacknowledged.Indian policy responses tend to replicate Western techno-legal models without engaging indigenous socio-structural realities.The paper concludes that ethical AI governance in India must transcend imported normative models and instead be rooted in context-sensitive approaches that accommodates the nation’s distinct social fabric,in order to prevent algorithm induced structural discrimination and ensure inclusive algorithmic justice.展开更多
文摘The paper critically evaluates the global discourses on algorithmic fairness,reviews key Western literature on artificial intelligence(AI)fairness,identifies twelve documented cases of algorithmic discrimination in Western contexts,and extends them for their analytical relevance to non-Western socio-political environments.The study applies these frameworks in particular to the Indian context,and proposes that India’s entrenched socio-cultural structures—caste,religion,language,regional identity,and minority status—tends to misalign with Western paradigms of fairness.The proposed study identifies identity-specific factors unique to India that are likely to contribute to algorithmic oppression if unaddressed.A critical policy analysis of major documents shaping India’s AI and digital governance landscape reveals that these critical factors remain largely unacknowledged.Indian policy responses tend to replicate Western techno-legal models without engaging indigenous socio-structural realities.The paper concludes that ethical AI governance in India must transcend imported normative models and instead be rooted in context-sensitive approaches that accommodates the nation’s distinct social fabric,in order to prevent algorithm induced structural discrimination and ensure inclusive algorithmic justice.
