Intelligentsusesse

Intelligentsusesse is a neologism used in speculative discussions of intelligence, ethics, and technology to describe an integrated approach to deploying intelligent capabilities across human and artificial agents in a way that emphasizes transparency, accountability, and collective welfare. The term is not widely established in formal scholarship and often appears in thought experiments, fiction, and early policy debates about future intelligent ecosystems.

Etymology and usage context

The word appears to be a compound of intelligence, usage, and the Latin esse (to be), signaling an attempt to capture the essence or being of intelligent practice within social systems. It emerged in online forums and speculative essays in the 2020s and has since appeared in some interdisciplinary discussions about governance, education, and AI design. In most sources, intelligentsusesse is treated as a conceptual umbrella rather than a settled theory.

Core ideas

Intelligentsusesse centers on coordinated intelligence across domains, prioritizing explainable reasoning, cross-boundary collaboration, and value-aligned outcomes. It emphasizes decoupled yet interoperable modules of intelligence (human and machine), transparent decision processes, and mechanisms for accountability and feedback. The concept is often framed as a spectrum rather than a fixed doctrine, ranging from everyday responsible use of smart tools to envisioned social-technical regimes that guide collective decisions.

Variants and applications

Some writers describe a weak form focused on responsible adoption of AI in daily life and institutions, while others discuss a strong form that envisions integrated governance structures and cooperative problem-solving among humans and AI systems. Potential applications include policy design, system evaluation, ethical guidelines, and educational programs to improve data literacy and critical thinking.

Criticisms

Critics argue that intelligentsusesse can be vague, culturally contingent, or overly aspirational. Detractors caution against semantic drift that obscures concrete policy and technical requirements, and they urge clearer definitions and measurable criteria for implementation.

See also

AI ethics, alignment problem, governance, transparency, human-in-the-loop, cognitive science.