Exploring AI-Based Tools for Facilitating Ethical Decision-Making in Digital Environments

Thesis Abstract

The rapid expansion of digital environments has heightened the necessity for ethical decision-making in technology-driven contexts, raising concerns about moral compliance, user trust, and societal impacts. This study investigates the potential of artificial intelligence (AI)-based tools to enhance ethical decision-making processes within digital platforms, aiming to fill the gap in empirical understanding of their effectiveness and practical implementation. The primary objective is to evaluate how AI tools can facilitate ethical choices, identify predictive factors influencing ethical decisions, and develop a conceptual framework for integrating AI ethically in digital environments. Employing a mixed-methods research design, the study combines quantitative surveys and qualitative interviews to provide a comprehensive understanding of the phenomena. The quantitative component targets a sample of 350 digital platform developers, ethicists, and users selected through stratified random sampling, to examine perceptions and usage patterns of AI-based ethical tools via structured questionnaires. The qualitative phase involves semi-structured interviews with 25 key stakeholders from technology firms and ethics committees, purposively sampled to garner diverse expert perspectives. Data will be collected using validated Likert-scale questionnaires and interview protocols. Quantitative data will be analyzed through multiple regression analysis and structural equation modeling (SEM) to explore relationships between variables such as perceived ethicality, user trust, and AI tool efficacy, while thematic analysis will be used to interpret qualitative data, emphasizing emerging themes and stakeholder attitudes. Expected findings suggest that AI-based tools significantly influence ethical decision-making by providing timely, context-aware recommendations that enhance moral clarity and consistency. The analysis is anticipated to reveal that factors such as user familiarity with AI ethics modules, perceived transparency of AI algorithms, and organizational ethical culture predict the degree of AI tool acceptance and efficacy. Furthermore, the research will test the applicability of two theories—the Normative Ethical Theory and Technological Acceptance Model (TAM)—to explain the adoption and perceived effectiveness of AI tools in ethical contexts. It is expected that the integration of these theoretical perspectives will offer a robust conceptual framework for understanding how AI can serve as an ethical mediator in digital decision-making. This research will contribute novel insights into the design, deployment, and user acceptance of AI-based ethical decision-support tools, bridging gaps between technological innovation and moral philosophy. It will provide empirical evidence on the conditions under which AI tools effectively promote ethical standards in digital environments, informing policymakers, technologists, and ethicists about best practices and potential pitfalls. Additionally, the study will propose a model illustrating the pathways through which AI facilitates ethical decision-making, emphasizing the influence of user perceptions, organizational factors, and AI transparency. Concluding, the study affirms that AI-based tools hold significant potential to support ethical decision-making in digital platforms, provided they are designed with transparency, user engagement, and contextual sensitivity. The recommendations include establishing standardized ethical design frameworks for AI tools, promoting awareness of AI ethics among developers and users, and implementing regulatory guidelines to ensure accountability. Future research directions highlighted comprise longitudinal studies to assess long-term impacts of AI ethical tools and cross-cultural analyses to explore contextual differences in AI acceptance. Overall, this thesis underscores the transformative role of ethically-aware AI in fostering responsible digital environments, contributing to both theoretical development and practical policy formulation in the domain of AI ethics.