<![CDATA[The concept of scientific objectivity has long been regarded as the epistemic cornerstone of modern science, grounded in neutrality, reproducibility, and observer-independence. However, the rapid integration of algorithmic systems, artificial intelligence, and data-driven infrastructures into scientific processes has fundamentally transformed how knowledge is produced, validated, and disseminated. This paper offers a philosophical inquiry into the evolving nature of scientific objectivity in the age of algorithmic mediation. It argues that objectivity is no longer solely a function of human rationality and methodological rigor but is increasingly co-constructed by computational systems that embed implicit biases, design assumptions, and socio-technical constraints. Drawing on contemporary philosophy of science, digital epistemology, and critical algorithm studies, this study critically examines how algorithmic mediation reshapes epistemic authority, transparency, and accountability in scientific practices. Using a descriptive qualitative approach, the paper synthesizes theoretical perspectives to propose a reconceptualization of objectivity as a relational and situated construct rather than an absolute ideal. The findings suggest that algorithmic systems simultaneously enhance and undermine objectivity by increasing analytical capacity while obscuring interpretive processes. Consequently, this paper calls for a reflexive framework of “augmented objectivity,” where human judgment and algorithmic processes are critically integrated. Such a framework emphasizes transparency, ethical design, and epistemic responsibility, ensuring that scientific knowledge remains trustworthy in increasingly automated environments.]]>
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