Research

Insights and Perspectives: Exploring Data, Technology, and Society

By Saira Shaikh; Saira is a LLM candidate at Stanford Law School August 13, 2024
Data has become a powerful tool in the fight for social justice, providing concrete evidence to highlight systemic inequalities and support movements advocating for change. In this comprehensive piece, we will explore how data can be leveraged to support social justice movements, examine the impact of data on highlighting systemic inequalities, and discuss specific case studies where data played a crucial role. We will also consider the ethical considerations and potential pitfalls associated with using data in this context.
By Arvind Arora, Arvind is a practicing advocate at the Supreme Court of India August 4, 2024
Over the last three decades, data has emerged as a powerful tool for shaping public policy, driving business decisions, and informing the general populace. Despite its potential, the use of data often faces skepticism and mistrust from the public. This distrust can stem from concerns over privacy, misuse, misrepresentation, or a lack of understanding about how data is collected and utilized. Building public trust in data is therefore crucial, particularly for initiatives aimed at public engagement and education. This piece explores methods to build public trust in data through education, transparency, and community engagement.
By Antara Chaudhary July 24, 2024
Introduction  The digital age has ushered in an era of unprecedented reliance on algorithms for decision-making in various sectors, from finance and healthcare to law enforcement and social media. These algorithms, often powered by artificial intelligence (AI) and machine learning (ML), have the potential to transform society by enhancing efficiency and enabling new capabilities. However, this transformation comes with significant challenges, particularly regarding transparency and accountability. The lack of transparency in algorithmic decision-making can lead to biases, discrimination, and a loss of public trust. This paper discusses the critical need for transparency and accountability in algorithmic decision-making to prevent biases and discrimination, exploring the implications for different sectors and proposing solutions to ensure ethical and fair use of these technologies.

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