Digital Media Ethics and Algorithmic Accountability

<p dir="ltr">This paper examines the intertwined challenges of algorithmic bias, digital disinformation, and media ethics within contemporary digital ecosystems, proposing an integrated governance framework that bridges technical, ethical, and regulatory dimensions. We first situate algorithmic bias as a structural issue emerging from data-driven systems that reproduce historical and social inequities, impairing fairness in information exposure and decision-making. Concurrently, we analyze how algorithmic amplification mechanisms and automated content distribution contribute to the propagation of disinformation, undermining trust and democratic discourse. Through a multidisciplinary review of literature from computer science, communication studies, and ethical theory, the paper identifies key ethical tensions-such as autonomy vs. automation, transparency vs. proprietary constraints, and accountability vs. opacity-in digital media platforms. Building on these insights, we propose a governance model that integrates ethical principles (fairness, transparency, accountability) with practical mechanisms (algorithmic audits, content moderation standards, stakeholder participation) to coherently address both bias and disinformation. The framework highlights the necessity for cross-sector collaboration among policymakers, platform designers, civil society, and scholars to ensure that digital media ecosystems support equitable access to information, respect user rights, and mitigate harms associated with biased systems and misinformation. Our findings aim to inform ongoing debates about responsible technology governance and contribute to the development of robust ethical guidelines and policy interventions for the digital age.</p>