Search

Feminised by design, AI companions commodify intimacy and risk hardwiring gendered stereotypes into our digital lives.

India’s consent-driven data rules may unintentionally hinder AI by limiting access to the large datasets essential for training

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

Questions around legal personhood for AI systems loom large given the potentially adverse consequences and the need to determine liabilities and remed

Although anthropomorphisation in AI can improve user interaction and trust in systems, it can lead to unrealistic expectations, ethical dilemmas, and

Given the rapid pace of change in AI systems, the development of AI standards and certification programmes has become more urgent

Concerted efforts need to be undertaken to close the gender data gap before gender bias becomes an inextricable part of emerging generative AI ecosyst

How AI systems impact the environment and how we can be more sustainable in their design, development, and deployment

Artificial Intelligence (AI) systems are showing promise in addressing the complex and interrelated challenges facing the world. During the pandemic, for example, AI voice enablement helped in broadcasting advisories in the vernacular and acted as a fact-checking tool. Yet, most AI systems are designed and developed in countries of the Global North. Policymakers in developing economies remain wary of AI systems, especially for use in soci

The Observer Research Foundation’s first Tech Huddle was held on 23 November 2023 and focused on the governance of artificial intelligence (AI) in India, highlighting the rapid growth and adoption of AI as well as the complexities associated with developing regulatory frameworks for it. AI governance is in its infancy, both globally and in India, and grapples with issues such as the explainability of AI systems as well as the embedded biases, s

Stakeholder groups have produced various guidelines on ethical Artificial Intelligence (AI) in recent years. However, translating principles into practice continues to be a massive challenge, as AI markets expand and AI risks are heightened. AI audits—or the process of investigating an algorithm against existing regulations and known harms—are emerging as a way of bridging the gap between principle and practice. This paper scans the landscape

India, like much of the rest of the world, is faced with the twin but opposing conditions of economic potential and social concerns that need to be negotiated to realise the digital dividends from artificial intelligence (AI) and achieve sustainable and balanced growth. AI systems involve layers of technological dependencies that necessitate and enable social and institutional interdependency between stakeholders, enabling conditions, and resourc

Defence structures around the world are seeing a technological upheaving as new and emerging technologies like artificial intelligence (AI) are being added to military arsenals. However, military AI largely lacks precision and is often developed without any threat-modelling which takes gender into account, examples of which are already being seen in civilian applications of AI. Translated into a conflict environment, deploying such AI systems cou

The rapid uptake of artificial intelligence (AI) in the military in the past couple decades has been accompanied by a slow but gradual build-up in attempts to understand how these AI systems work to achieve better results in military operations. The idea behind what is called ‘eXplainable AI’ (XAI), and the technologies driving it, are a manifestation of this trend. The question, however, is if XAI in its current form is the solution

The European Union (EU) Artificial Intelligence Act is a landmark regulation capable of propelling the bloc to the forefront of AI governance. Implementing a novel risk-based tiered approach, the Act has the potential to become a policy template for other states aiming to regulate the development and use of AI. Although the regulation represents a pioneering effort in governing a technology as impactful as AI, it suffers from certain gaps such as