Abhinav Saxena
Philosopher · Researcher · Writer
I work on what happens to our oldest concepts — knowledge, testimony, consent, responsibility — when they meet machines that seem to know, answer and decide.
Who I am
I am a philosopher and independent researcher based in New Delhi. My area of specialisation is epistemology, with a focus on testimony and the social epistemology of artificial intelligence; my areas of competence are philosophy of technology, political philosophy, ethics and environmental ethics. I studied philosophy at Mahatma Jyotiba Phule Rohilkhand University and the University of Delhi.
Two lines of work run through what I write. The first asks what it takes for a source to transmit knowledge, and argues that large language models, on the best current evidence, do not: the truth of what they say does not figure, through their own operation, in why they say it. The second asks what institutions owe the people their algorithmic systems govern, and argues that where a system produces a person's standing rather than merely acting on it, consent cannot be what legitimates it.
I work in the analytic tradition, with wider interests in philosophy of mind and in classical Indian philosophy, phenomenology and existentialism. I write for philosophers, and also for the engineers, policymakers and readers who have to live with these questions before philosophy has finished with them.
Academic background
- 2023–2025
- M.A. PhilosophyUniversity of DelhiDegree to be conferred December 2026. Dissertation: Psychocentrism: A Cognitive Reorientation of Environmental Ethics. Supervised by Dr Narmada Pujari.
- 2023
- B.A. PhilosophyMahatma Jyotiba Phule Rohilkhand University
Research interests
- EpistemologyTestimony, and what a source must do for a hearer to know from it.
- Social EpistemologyKnowledge we hold together, and what a machine link does to a chain of it.
- Philosophy of AIWhat current AI systems are, described without inflation or dismissal.
- Ethics of AIWhat institutions owe the people their algorithmic systems govern.
- Political PhilosophyLegitimacy, recognition and consent when institutions work through algorithms.
- Ethics & TechnologyTechnologies judged by their architecture, not their technique.
- Environmental EthicsPsychocentrism, a cognitive reorientation of environmental ethics.
- Philosophy of MindBelief, understanding and representation, tested on systems that produce language without a life.
- Indian PhilosophyClassical Indian epistemology as a resource for questions about testimony and knowledge.
- PhenomenologyAttention to how things show up, before theorising about what they are.
- ExistentialismSelfhood as a task rather than a fact — and what technologies do to the task.
Current work
Two questions organise my current writing:
- Is a model's answer testimony, evidence, or a third kind of thing?
- What does an institution owe the people whose standing it produces?
Assertion Without a Speaker is forthcoming in Episteme. Under review: Consignation Without Custody (AI & Society, minor revisions requested) and The Legitimacy of Foundation Models (Philosophy & Technology, minor revisions requested).
Recent talks: Beyond Consent (Interdisciplinary Speaker Series on the Ethics of AI, Indian Institute of Technology Delhi, April 2026); Assertion Without a Speaker (AI and Knowledge, University of Delhi, February 2026).
Selected publications
Beyond Consent: Algorithmic Welfare, Constitutive Dependence, and the Limits of Liberal AI Ethics
AI and Ethics 6, 414
Within the data-protection-derived legal and governance frameworks that regulate algorithmic systems (the GDPR, the EU AI Act, and the principlist codes that track them), consent and individual authorisation are the load-bearing mechanism of legitimation and redress, and the same frame organises the remedial debate over large-scale algorithmic welfare systems, the Indian Aadhaar architecture being the paradigm case. This paper argues that for a distinctive class of such systems consent is not merely practically strained but conceptually misplaced, and develops a positive alternative. Its central contribution is the concept of constitutive dependence: a condition in which an algorithmic system does not constrain or coerce agents recognised as rights-bearers but produces their operative standing as subjects of recognition and entitlement. Where it obtains, the standpoint of refusal on which consent depends is foreclosed by the system’s algorithmic architecture, which enforces its criteria of recognition without the discretionary judgement by which a human-mediated bureaucracy can recognise the manifestly entitled.
Locating the condition within the recognition-theoretic tradition (Honneth, Fraser, Butler; Waelen) as a distinctively infrastructural form of misrecognition, the paper articulates the Constitutive Obligation Principle: where an institution produces its subjects’ operative standing as entitlement-bearers, its legitimacy depends not on their authorisation but on discharging non-waivable obligations of legibility, non-abandonment, and remediation. Developed through the Aadhaar case and offered as a framework for the algorithmic welfare state more broadly, the argument reads Aadhaar not as an outlier but as an early instance of an architectural form toward which algorithmic governance is converging.
Assertion Without a Speaker: Testimony, Tracking, and Large Language Models
Episteme
Large language models produce assertion-shaped outputs that often bring their users to true belief. I argue for two conclusions of different strengths: that on the best current evidence these systems do not transmit testimonial knowledge, and that hearers are not now positioned to accord their outputs testimonial uptake, which does not wait on the first. From Burge, Williamson, Goldberg, Faulkner, and Lackey I derive a Tracking Minimum: a source transmits testimonial knowledge that p only if the truth of p, or the evidential support for p, figures in the explanation of its producing that assertion, and does so in virtue of the source’s own production process rather than of a proxy on which that process depends. It is this endogeneity requirement, not any modal profile, that the five accounts share and current systems fail.
The argument engages Burge’s extension of his framework to computational sources, the interpretability literature, and the published case for AI testimony, whose dispute with mine turns on an empirically decidable question, for which an experiment is specified. The positive proposal places LLM outputs within an extended epistemology of instruments, with a result that has gone unremarked: a working barometer satisfies the condition these systems fail.
Consignation Without Custody: Answerable Provenance as a Framework for Responsible AI in Art Creation and Archival Practice
AI & Society
Profiles
- ORCID 0009-0002-6424-4197
Correspondence: abhinav.philosophy@gmail.com