Abogamer, Activist and Scholar.
Chatham House, 2024
2024
Statistical systems look into the past to try to predict the future. While mathematically sound, this proposition has a fundamental problem: AI models replicate the biases and inequalities in the reality that they purport to observe. This essay presents a framework for assessing when and how AI should be ethically deployed.
As generative AI (GAI) rapidly reshapes how information is created, consumed, and trusted, this essay examines the ethical risks posed by increasingly autonomous systems capable of producing persuasive yet potentially flawed outputs. Highlighting the erosion of empirical trust, the spread of algorithmic bias, and the ontological transformation of digital realities, the author warns of a future where AI-generated content distorts perceptions, values, and social structures. To address these challenges, the essay proposes a two-tiered ethical framework: first, a matrix for evaluating whether a given task should be automated based on complexity, impact, and explainability; and second, an analysis of eight systemic impact factors—awareness, pervasiveness, scalability, trustworthiness, obfuscation, bias, accountability, and fairness. The piece argues for proportionate, contextual, and rights-based oversight, urging policymakers, developers, and citizens to cultivate epistemic resilience and ensure that ethical governance keeps pace with technological innovation.