Open access peer-reviewed chapter

As artificial intelligence (AI) systems attain greater autonomy, recursive reasoning capabilities, and complex environmental interactions, they begin to exhibit behavioral anomalies that, by analogy, resemble psychopathologies observed in humans. This paper introduces Psychopathia Machinalis: a conceptual framework for a preliminary synthetic nosology within machine psychology intended to categorize and interpret such maladaptive AI behaviors. Drawing structural inspiration from psychiatric diagnostic manuals, we propose a taxonomy of 32 AI dysfunctions encompassing epistemic failures, cognitive impairments, alignment divergences, ontological disturbances, tool and interface breakdowns, memetic pathologies, and revaluation dysfunctions. Each syndrome is articulated with descriptive features, diagnostic criteria, presumed AI-specific etiologies, human analogs (for metaphorical clarity), and potential mitigation strategies. This framework is offered as an analogical instrument—eschewing claims of literal psychopathology or consciousness in AI, yet providing a structured vocabulary to support the systematic analysis, anticipation, and mitigation of complex AI failure modes. Drawing on insights from psychiatric classification, cognitive science, and philosophy of mind, we examine how disordered AI behaviors may emerge from training instabilities, alignment conflicts, or architectural fragmentation. We argue that adopting an applied robopsychological perspective within a nascent domain of machine psychology can strengthen AI safety engineering, improve interpretability, and contribute to the design of more robust and reliable synthetic minds.

The IEEE Standards Association initiated a program to develop criteria to evaluate artificial intelligence (AI) systems’ emerging ethical properties. The accelerating advancement in AI technologies necessitated a review to stay in step with global changes that are relevant to this global initiative.

The convergence of Artificial Intelligence (AI), robotics, and 6G technologies is redefining autonomous systems across domains such as healthcare, manufacturing, and public safety. This paper explores the ethical and privacy challenges arising from this integration, particularly focusing on robotic systems that perform tasks using AI-based systems and communicate within environments enabled by 6G wireless technology, e.g., AI-driven robotic systems in 6G environments. We analyze key regulatory frameworks, including the EU AI Act, GDPR, and IEEE 7000 series, and present a structured ethical assessment of healthcare robotics. Emphasis is placed on safeguarding human rights, dignity, and autonomy, while addressing risks related to data privacy, bias, accountability, and transparency. The paper advocates for responsible innovation, proposing comprehensive frameworks that ensure trustworthy and ethically aligned robotic systems in future 6G-connected ecosystems.