Digital welfare’s potential dark side looms, threatening human rights. Activists highlight how welfare’s dark algorithms can bias and discriminate. To combat this dark aspect, transparent governance and ethical coding practices are essential. Ensuring welfare’s light overshadows its dark possibilities is a modern societal imperative.
Digital welfare systems have often been portrayed as neutral tools designed to enhance access to social benefits, streamline eligibility criteria, expedite processes, and boost government efficiency. However, beneath the surface, these systems carry their own set of pros and cons, some of which raise concerns about potential infringements on human rights.
Digital welfare’s increasing prevalence in countries with data-driven social protection and welfare systems has led to the automation, prediction, identification, estimation, detection, and even punitive actions driven by technology. While efficiency and cost reduction are potential benefits, the motives behind these initiatives aren’t always transparent. Some programs may aim to cut social spending and create intrusive government surveillance systems, potentially leading to profits for private companies.
The expansion of digital welfare systems has the potential to exacerbate inequality. Not everyone has equal access to the internet or possesses the digital skills necessary to navigate these systems. Increasingly, public services are transitioning to digital-only platforms, deepening disparities between those with digital literacy and access and those without.
The case of India’s “Aadhaar” biometric identification program exemplifies both the potential benefits and pitfalls of digital welfare. While Aadhaar has helped establish the legal identity of over a billion Indian citizens and streamline access to public services, it has also excluded vulnerable populations. When Aadhaar registration became mandatory, millions of poor families without Aadhaar cards were denied access to government-subsidized food rations. The lack of internet access and issues with biometric data collection machines further complicated authentication for these individuals.
