India AI Summit 2026: The Critical Need to Define AI Accessibility Beyond Technical Parameters
As the world approaches the landmark India AI Summit 2026, the global conversation surrounding artificial intelligence has evolved significantly. The discourse has moved beyond mere algorithmic efficiency and computational power to encompass more profound issues of digital sovereignty, ethical frameworks, and fundamental rights. At the heart of this evolution lies a critical legal and ethical gap that demands immediate attention: the comprehensive definition of 'AI accessibility.'
The Definitional Gap in Current Legal Frameworks
In India, the Rights of Persons with Disabilities (RPwD) Act of 2016 provides a robust legal foundation for protecting the rights of persons with disabilities (PwDs). However, this legislation defines accessibility primarily in negative terms, focusing on the removal of barriers rather than proactive inclusion. The Act broadly defines a 'barrier' as any factor—whether communicational, cultural, economic, environmental, institutional, political, social, attitudinal, or structural—that hampers full participation.
This approach treats accessibility as the mere absence of obstacles, which presents a fundamental challenge when applied to artificial intelligence. Unlike static physical structures such as ramps or elevators, AI represents a recursive form of software that continuously evolves and learns. If the upcoming summit aims to establish global benchmarks, it must transcend traditional calls for barrier removal and instead mandate what AI systems need to be from their very inception.
A Three-Tiered Framework for AI Accessibility
For artificial intelligence systems, accessibility must be understood as a dynamic spectrum operating across three distinct temporal and functional levels:
- Instant Stage Accessibility: This represents the entry threshold covering basic requirements for participation. It necessitates ensuring that foundational AI models and interfaces are compatible with assistive technologies from their initial deployment. For instance, within the context of the IndiaAI Mission's focus on multilingualism, speech-to-text tools for regional languages must account for the diverse vocal patterns of persons with disabilities. This level embodies the fundamental 'right to entry' principle.
- Medium-Term Accessibility: At this stage, AI must progress from mere compatibility to active facilitation. Accessibility here is defined by convenience and enhanced user experience. AI systems should deploy features that ease access to goods and services for PwDs compared to traditional means. Examples include AI-driven vision assistants for navigating government portals or predictive interfaces that reduce motor load, thereby improving the quality of AI interaction.
- Long-Term Accessibility: This represents the ultimate goal where accessibility translates into systemic inclusion. At this level, the recursive nature of AI is leveraged to eliminate historical biases and structural inequalities. AI systems don't merely assist persons with disabilities; they actively restructure digital and social environments to ensure equal participation in society and the workforce.
The Rajive Raturi Framework: A Legal Blueprint for AI
A pivotal moment in Indian accessibility jurisprudence occurred with the Rajive Raturi vs Union of India judgement of 2024. The Supreme Court made a crucial distinction between accessibility and reasonable accommodation, characterizing accessibility as an ex-ante obligation—a proactive, universal mandate that must exist from the moment an entity or service is created.
This legal precedent has profound implications for AI development. Ex-ante accessibility must be embedded into the very training datasets and model architectures of India's sovereign AI initiatives. Universal design principles must ensure that AI tools are usable by as many people as possible from their initial deployment, as corrective patches applied later would fail to meet this constitutional requirement.
Conversely, reasonable accommodation represents an ex-post duty—an individualized adjustment made after identifying specific barriers for particular individuals. This is where AI's greatest strength, its recursive learning capability, becomes transformative. Unlike static physical infrastructure, AI systems can adapt and fulfill customized duties through prompting or fine-tuning at the edge, bridging the gap between universal standards and individual needs in real-time.
The Summit's Transformative Opportunity
Scheduled for next month, the India AI Summit 2026 presents a historic opportunity to harmonize technological advancement with established disability jurisprudence. The summit must facilitate a shift from negative definitions focused on barrier removal toward affirmative national AI accessibility standards that could potentially influence global adoption.
These standards must recognize the dual responsibility framework: while developers have an ex-ante duty to build accessible models, the AI systems themselves must be trained to recognize when they need to provide ex-post reasonable accommodation. The recursive nature of modern AI models enables a self-correcting accessibility loop that was unimaginable in the era of traditional brick-and-mortar infrastructure.
Defining accessibility for artificial intelligence transcends technical challenges—it represents an imperative from the perspective of fundamental rights. By adopting the Rajive Raturi framework, the India AI Summit could help ensure that next-generation technologies are inclusive by design (ex-ante) and adaptive by nature (ex-post). If India aspires to lead the Global South in the AI revolution, it must demonstrate that its technological advancements respect the dignity of all citizens, ensuring that the 'barrier-free' environment promised by legal frameworks finally materializes within our algorithms.
