Publication of IJGHMI
Technocratic Empathy: Algorithmic Decision-Making and the Simulation of Care in Welfare Systems
Author : Dr. Jonas Lindberg
Open Access | Volume 2 Issue 1 | Jan–Mar 2025
https://doi.org/10.63665/IJGHMI_Y2F1A003
How to Cite :
Dr. Jonas Lindberg, "Technocratic Empathy: Algorithmic Decision-Making and the Simulation of Care in Welfare Systems", International Journal of Global Humanities and Management Insights [IJGHMI], Volume 2, Issue 1 (Jan–Mar 2025), pp. 21–28.
Abstract
Abstract - The algorithmic coding of systems into welfare rule has refigured practice to reveal a new technocratic ideal of compassion where machine logic attempts to mimic human concern in assessing citizens' needs for commodities. This article is concerned with the ethical, political, and social outcomes of these types of systems, and how algorithmic processes can reproduce inequality, individualize care, and render accountability transparent. Recalling critical algorithm studies, welfare studies, and digital ethics, the article resists an either-or solution between outcome maximisation through machines and some of those humanising values which are at the heart of welfare provision. Discussion of automated predictive welfare algorithms, risk assessment systems, and automated eligibility determination calls upon them as examples of how systems render empathy quantifiable compliance and outcomes optimised instead of context dependent relational care. It presumes algorithmic rule promises impartiality and expansiveness but achieves a simulation of care technically flawless but morally barren raising questions of gravity and persistence concerning justice, dignity, and the conception of social citizenship. Lastly, it seeks avenues for reinscribing human judgment, moral vigilance, and participatory accountability into algorithmically facilitated welfare, encouraging a model in which technological efficacity is not replaced by ethical duty.
Keywords
Algorithmic governance, technocratic empathy, welfare systems, predictive analytics, digital ethics, social policy, simulation of care, automated decision-making, accountability, social justice
Conclusion
The alignment of algorithmic regimes with welfare governance is a fundamental shift in the provision of care that has the potential to bring both efficiency and depersonalization. This article has maintained that whilst algorithms are able to mimic empathy through predictive modelling, score eligibility, and automated allocation of resources, they are not capable of reproducing the relational, moral, and contextual aspects of human judgment. Depersonalization, embedded bias, and clear decision-making erode both the moral integrity of welfare systems as well as public trust, creating an estrangement between computational effectiveness and authentic care. Hybrid models combining algorithmic accuracy with human supervision, ethical audit, and participatory involvement are required in order to confront these problems. Integrating human judgment ensures that algorithmic outputs are read and applied in a way that is respectful of dignity, justice, and fairness, whereas participatory designs and algorithmic literacy make it possible for citizens to co-design and critically interact with welfare systems. Ethical integration throughout all stages from design and coding to deployment and assessment provides a framework of accountability and transparency that ensures that technology functions as an instrument of relational care rather than a substitute for it. Last, social and ethical legitimation of welfare government is based on the perception that visibility, efficiency, or technical expertise is insufficient to guarantee justice; care must remain relational, contextual, and morally rooted. If policymakers are able to reimagine welfare as a collaborative arrangement in which algorithms support but not replace human judgment, policymakers can weigh the performative advantages of technology against humanist principles guiding social policy. In the era of big data, responsible algorithmic welfare is more than a technical engineering function; it is an ethical responsibility, which requires constant introspection, ethical examination, and democratic engagement so that citizens are served with care as both effective and meaningful. It is only through these synthesized approaches that welfare institutions shall be able to maintain legitimacy, re-establish public trust, and in still the spirit of social justice in a more data-driven society.
References
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