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Executive Summary The trajectory of artificial intelligence has shifted from the deployment of static, rules-based tools to the integration of dynamic, autonomous agents capable of independent perception, reasoning, and action. Read More …
Executive Summary The field of artificial intelligence is undergoing a profound transition, moving beyond models that merely predict outcomes based on statistical correlations to systems that build an internal, manipulable Read More …
The Imperative for AI Auditability As artificial intelligence (AI) systems become increasingly embedded in critical decision-making processes across every industry, the demand for transparency, accountability, and trustworthiness has moved from Read More …
The Pursuit of Machine Reasoning The ambition to create machines that can reason and solve problems in a manner akin to human intelligence has been a central theme in computer Read More …
Introduction: The Quest for Understanding in an Age of Opaque Intelligence The rapid ascent of artificial intelligence (AI) presents a central paradox of the 21st century: as our computational creations Read More …
Part I: The Reverse Engineering Paradigm As artificial intelligence systems, particularly deep neural networks, achieve superhuman performance and become integrated into high-stakes domains, the imperative to understand their internal decision-making Read More …
Executive Summary Building trust in AI is essential for its success in business and society. Trustworthy AI systems must be transparent, fair, secure, and aligned with human values. In this Read More …