Governing the Digital Cradle: Medico-Legal Frameworks for Artificial Intelligence in Reproductive Health

Artificial Intelligence (AI)-Infused Reproductive Technology is the waning of human instinct in medicine and AI's rise as data-informed precision health care.It opens the door to "robotic" diagnostics that identify prime embryos for In-Vitro Fertilization (IVF) with near-perfect success rates, augmented possibilities of gene and stem cell therapy (it uses stem cells to treat or prevent a disease or condition) as an alternative to Assisted Reproductive Technologies, and promotes Sustainable Development Goal 3 (Good Health and Well-being).But at the same time, it challenges medico-legal and ethical understandings that our legal systems were premised on for years.In this backdrop, the paper aims to explore the overlap of the fields of AI, law, and ethics within the sphere of reproduction, particularly focusing on analyzing India's embryonic regulation through these entanglements.In an IVF cycle, a data-fueled embryo-selection algorithm not only "silences" and removes the need for informed stakeholders, but it also sets the stage for the exponential growth of algorithmic paternalism with uninterpretable "black box" diagnostics.Legally, the Assisted Reproductive Technology (Regulation) Act, 2021, and the Digital Personal Data Protection Act, 2023, have faltered in not acknowledging the sui generis nature of errors by these autonomous diagnostic tools in allocating liability.Further, it has not even sufficiently protected the users' right to informational privacy and dignity in the case of reproductive big data.Ethically, the scope for digital eugenics due to biased training data is both concerning and disconcerting.Further, the disproportionate impact this digital transformation is bound to have on access to these technologies, given the existing rural-urban digital divide.In the given backdrop, by dovetailing international human rights norms with a comparative critique of Indian law, this paper attempts to strike a balance between both the negative and the positive rights to usage of AI in reproductive technology in a gamut of ways: using a "human-in-theloop" approach as the standard for assigning liability in medico-legal cases of AI-malpractice, and mandating algorithmic auditing to thwart algorithmic bias and thereby promote the same rights-based approach as a crucial regulatory principle for the "digital cradle."