Introduction
Algorithms are rapidly influencing and monitoring citizens’ movements, transactions, and decisions, under the pretext of development and government. Traffic cameras at major crossroads are part of an e-challan network deliberately strategically installed in the city’s busiest areas. Algorithmic cameras attempt to minimise road fatalities and enhance traffic flow by automatically enforcing regulations. Violations, such as not wearing a seatbelt or running a red light, are automatically recorded, analysed, and penalised. Algorithmic governance is reshaping daily life in the city through the subtle enforcement of driving habits. However, traffic enforcement represents only one aspect of this phenomenon. Furthermore, facial recognition systems monitor office entries, while AI-driven systems manage transactions, assess fraud risk, adjust credit scores in real-time, and tailor advertisements on social media and billboards based on past online behaviour. Ultimately, citizens’ digital footprints over their lifetime are analysed by various governmental organisations, which assess potential health risks and security concerns, subtly influencing future interactions with state services.
This situation exemplifies Algorithmic Constitutionalism, an emerging paradigm where core ideals of the Indian Constitution- equality, privacy, and the rule of law- are redefined within the digital age. In this new world, algorithms transcend their role as tools; actively shaping public life and altering, the foundation of democratic governance. However, the increased dependence on these systems presents several important problems, such as: What exactly does the word algorithmic governance mean, and what is its scope? How can algorithmic governance affect constitutional rights when the procedures are hidden by opaque code? What role do the legislative and judicial branches play in resolving these issues? What steps may be made to improve justice and equality in algorithmic systems?
Constitutional implications and judicial role in algorithmic decision-making
Algorithms have become an essential component of decision-making in modern public administration and law enforcement. From predictive policing models that foresee crime hotspots to automated legal guidance, digital technologies are rapidly taking on roles previously held by human authorities. This shift from human judgement to data-driven decision-making marks the rise of ‘algocracy’, where algorithms take over tasks once managed by experts. While these tools are more accurate and objective, they run the danger of reducing complex human experiences to simple data points, thereby missing subtleties in governance processes. A core issue is algorithmic opacity or the “black box” problem, where AI systems’ processes remain unclear to those affected. Citizens may see such systems as opaque and lacking accountability, making it difficult for them to understand, for example, why a traffic charge has been enforced. This, lack of transparency and accountability can lead to perceived arbitrariness, undermining due process protections guaranteed by Article 21 of the Indian Constitution which ensures that legal proceedings are fair and essentially implies that the legal system will operate in an unbiased and just manner; as a result, a decision will be rendered free from bias and transparency, a cornerstone of due process requires that the processes and justifications for choices be transparent, or accountable. Furthermore, the ideals of justice and non-discrimination entrenched in Article 14 of the Indian Constitution are prone to degradation as a result of inherent biases in algorithms. These biases are sometimes caused by the data used to train AI algorithms, which can reflect and exacerbate societal preconceptions rather than neutralise them. For example, face recognition technologies, which are commonly used in law enforcement and surveillance, have been demonstrated to create much greater mistake rates for persons of colour, disproportionately affecting underprivileged populations.
In India, the regulation of AI and algorithmic governance is a dynamic terrain with major problems. The Digital Personal Data Protection Act of 2023 is a significant step towards full data protection. However, the regulatory environment for AI is still fragmented and inadequate. Existing legal laws are largely concerned with data protection, rather than the larger implications of AI governance. These systems often fall short in addressing critical challenges like algorithmic bias, transparency, and accountability. This emphasises the necessity for a thorough rethink of the law as it connects with AI. Traditional legal frameworks designed for human-centred decision-making must evolve to handle the difficulties of algorithmic governance. For example, the implementation of artificial intelligence in welfare schemes, like Samagra Vedika in Telangana, has highlighted how such systems led to unequal outcomes, such as unequal access to security benefits for marginalised individuals. This disparity needs more than simply minor tweaks or technological fixes; it necessitates a fundamental change towards a bottom-up approach that includes feminist, decolonial, and anti-caste viewpoints. This involves investigating who holds the data, how openness is maintained, and the safeguards in place to avoid abuse of power.
Meanwhile, the judiciary can help bridge regulatory gaps and protect constitutional rights in the context of AI. Indian courts have long been aggressive in resolving privacy and civil rights concerns. In Justice K.S. Puttaswamy v. Union of India, the Supreme Court established privacy as a basic right under Article 21 of the Indian Constitution, establishing a precedent for personal data protection. The courts have the authority to require openness in AI decision-making processes and hold people accountable for algorithmic prejudice. This includes investigating incidents where AI applications result in discriminatory practices or breach privacy rights, highlighting the necessity for strong regulatory safeguards.
Promoting fairness in Algorithmic Governmentality
The challenges posed by algorithmic governmentality, such as violations of due process and principles of fairness and non-discrimination, can be addressed through proactive strategies grounded in legal principles, such as Firstly, the “no detriment” concept ensures that algorithmic decisions do not harm individuals while maximising their benefits. While maintaining the positive potential and protecting people’s rights and welfare, this approach seeks to lessen unfair disadvantages brought about by algorithms. In order to put this into practice, authorities must set objective benchmarks to gauge how fair the algorithms are and adjust their code if they depart from them. While the idea seems feasible in theory implementing this concept requires proactive planning and collaboration among stakeholders. Secondly, in order to mitigate the polarising impacts of algorithmic governance, it is imperative to move towards universal ideals of equality and shared access, such as universal education. In order to promote the ethical use of algorithms and critical thinking about their use, education is essential. This strategy aims to create a more just society by ensuring equitable access to technological benefits and addressing algorithm-driven inequalities that fragment social experiences. Thirdly, Theoretical frameworks like liquid modernity and queer theory can challenge restrictive algorithmic classifications. Queer theory, as a part of outsider jurisprudence, critiques the heteropatriarchal legal systems and advocates for examining state institutions to promote justice and equity. Liquid modernity argues that while individuals in a globalised society have freedom of choice, this freedom introduces new challenges. As a result, it implies that the social structure needs to acknowledge the “diversity of the choice” and refrain from establishing some options as universal standards. By adopting these viewpoints, the digital system will become more inclusive, enabling people to stand up for their independence and reject being limited.
In order to challenge algorithmic governance, it is essential to cultivate a dedication to common humanity. By critically examining algorithms and decision-making procedures, we can make sure that these instruments uphold democratic principles and serve society in an ethical manner. This entails advocating for policies that align technology with constitutional ideals of fairness and justice under Articles 14 and 21 of the Indian constitution.
Conclusion
Algorithms have the ability to improve decision-making consistency and efficiency, but they also present serious problems with regard to individual rights, justice, and transparency. Current legal frameworks must change to reflect these new digital realities in order to handle the complexity of algorithmic governance. The creation of a technically and legally sound AI fairness code is required for this adoption. Because of India’s distinct socioeconomic circumstances, varied populace, and diverse linguistic, cultural and economic disparities in India that demand localized AI solutions, hence the use of Western-centric AI fairness models may not be sufficient there. As a result, AI technologies need to be inclusive of all groups and customised for local circumstances. This entails reassessing the basic presumptions of AI systems critically, integrating a variety of representative data sources, and interacting with local populations to comprehend their particular requirements. An inclusive approach can ensure the equitable distribution of AI benefits, aligning with the constitutional values of justice and equality. The ultimate objective should be to establish a government structure that protects each citizen’s constitutional rights while allowing algorithms to make constructive contributions to society.
This blog is written by Jaiveer Singh and Yagya Agarwal, 3rd Year and 4th Year Law Student respectively, Rajiv Gandhi National University of Law, Patiala.
