12,445 papers · continuously updated · last export: 10 Aug 2026livingmeta.ai
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Research theme

Responsible AI Use

The Responsible AI Use theme comprises 2,407 papers in this corpus published between 1991 and 2026. Work here is dominated by Conceptual, Literature Review, Qualitative. 5 open research gaps have been surfaced in this area.

Methodology profile

  • Conceptual397 (16%)
  • Literature Review296 (12%)
  • Qualitative291 (12%)
  • Experimental203 (8%)
  • Position Paper199 (8%)
  • Empirical Study193 (8%)

Research domains

  • AI Governance803 (33%)
  • Human-AI Collaboration741 (31%)
  • Research Integrity527 (22%)
  • Doctoral Training88 (4%)
  • Academic Writing70 (3%)
  • Bias & Epistemic Risk56 (2%)

Frequent sub-topics

algorithmic harm and digital social pollution from automated decision-making · 2industry-academic collaboration in context of generative AI · 1AI-assisted amateur research; epistemic authority boundaries; autoethnography · 1AI awareness and adoption in library institutions · 1AI-friendly assignment design for undergraduate education · 1Institutional AI fluency and faculty training · 1genai_acceptance_and_adoption · 1AI Guard-Down Effect and cognitive offloading in cybersecurity and privacy behaviors · 1

Open research gaps

  • The authors identify a gap in understanding how stakeholders perceive fairness in hybrid decision-making: "understanding how stakeholders perceive its fairness remains limited. While studies have prim
  • The abstract does not explicitly identify specific research gaps or future directions beyond the general applicability statement that the materials "can support work on AI adoption, policy, and method
  • The paper implicitly identifies gaps regarding the integration of constitutional principles with algorithmic governance, the operationalization of Explainable AI in legal contexts, and the balance bet
  • Not explicitly stated in the abstract.
  • The authors identify gaps in current teacher training programs regarding: (1) training in ethical AI frameworks, (2) security preparedness, (3) algorithmic responsibility, and (4) the need for compreh

Representative papers

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