Colony cohesion is stable even as ant-level network measures vary more for ants when they switched functional groups; thus ant colonies maintain a high level of information flow as determined by network analysis and ant functional groups play different roles in maintaining colony cohesion.
The paper starts by considering the technology itself, providing an overview of AI assistants, their technical foundations and potential range of applications, then explores questions around AI value alignment, well-being, safety and malicious uses, and considers the deployment of advanced assistants at a societal scale.
AI in current practice is deteriorating the authors' theoretical understanding of cognition rather than advancing and enhancing it, and this situation could be remediated by releasing the grip of the currently dominant view on AI and by returning to the idea of AI as a theoretical tool for cognitive science.
FRODO is introduced, a framework to tailor small-sized LMs to generate correct reasoning steps and robustly reason over these steps and is found that FRODO's rationales are more faithful to its final answer predictions than standard supervised fine-tuning.
It is argued that, while not infallible, CoT monitoring offers a substantial layer of defense that requires active protection and continued stress-testing, and introduces a conceptual framework distinguishing CoT-as-rationalization from CoT-as-computation.
The paper explores how bias, lack of transparency, and challenges in maintaining patient trust can undermine the effectiveness and fairness of AI applications in healthcare, and outlines pathways for achieving more responsible and inclusive AI implementation in healthcare.
It is argued that traditional technocratic standards are failing to integrate normative considerations into biomedical translation, and a translational domain that moves beyond safety and efficacy toward anticipating how proposed technologies will be effective in society as it exists is needed.
For LLMs to serve as relevant and effective creative engines and productivity enhancers, their deep integration into all steps of the scientific process should be pursued in collaboration and alignment with human scientific goals, with clear evaluation metrics.
It is argued that the public discourse is not simply a less complex way of speaking, but instead transcends its technical basis and introduces a non-exhaustive list of four central aspects of GenAI: (multi-)modality, interaction, flexibility, and productivity.
This work proposes a post-training framework called Reinforcement Learning via Self-Play (RLSP), and proposes a theory as to why RLSP search strategy is more suitable for LLMs inspired by a remarkable result that says CoT provably increases computational power of LLMs.
The transformation of educational environments from hierarchical instructionism to constructionist models that emphasize learner autonomy and interactive, creative engagement is discussed, providing insights for educators and policymakers seeking to harness digital innovations to foster adaptive, student-centered learning experiences.
This study examines recent advances in AI-enabled medical image analysis, current regulatory frameworks, and emerging best practices for clinical integration, and proposes practical solutions to address key challenges, including data scarcity, racial bias in training datasets, limited model interpretability, and systematic algorithmic biases.
It is argued that whether AI is conscious is less of a concern than the fact that AI can be considered conscious by users during human-AI interaction, because this ascription of consciousness can lead to carry-over effects on human-human interaction.
Questions about human centrality and agency in the research process are raised, and about the multiple philosophical and practical challenges the authors are facing now and ones they will face in the future are raised.
The socio-technical nature of RAI limitations and the resulting necessity of producing socio-technical solutions are considered, bridging the gap between the theoretical considerations of RAI and on-the-ground processes that currently shape how AI systems are built.
Although there is a consensus that RAI practices are a necessity, their implementation in real-world is still in its early day and the involvement of all relevant stakeholders is irreplaceable in driving and shaping RAI practices.
A typology is proposed that distinguishes the different stages of the AI life-cycle, the high-level ethical principles that should govern their implementation, and the tools with the potential to foster compliance with these principles, encompassing both technical and conceptual resources.
It is found that bioethicists' normative commitments predict their views on bioethical issues, and that the field of bioethics is far less diverse than the U.S. population-less diverse even than other academic disciplines- suggesting far more work needs to be done to build an inclusive field.
This Essay proposes a new hierarchical model linking genes to vital rates, enabling us to critically reevaluate the DST and DTA in terms of their relationship to evolutionary genetic theories of aging (mutation accumulation and antagonistic pleiotropy).
The research investigates epistemological and theological considerations related to the application of machine learning algorithms in interpreting sacred Islamic texts, proposing that AI applications adhere to principles of justice, transparency, and the preservation of human dignity and autonomy.
This paper argues for the epistemological necessity of such a passage and the inclusion of trained reflective awareness in neurophenomenological empirical approaches, and showcases incremental explanatory gains for the scientist that arise from incorporating the participants' epistemic insights.
The value of plankton to humanity is presented across six themes of human interest: biogeochemistry; ecology; climate; the evolution of science; economy; culture, recreation, and well-being; and culture, recreation, and well-being.
The results of the study show that effective character education can increase students' awareness of ethical behavior, digital responsibility, and empathy, and that character education programs have been proven to reduce cases of cyberbullying, and the spread of false information, and improve the quality of social interaction in cyberspace.
The study develops a reframed understanding of Responsible AI as a dynamic, negotiated, and context-sensitive process and advances a composite theoretical model and a layered ecosystem framework that redistributes responsibility across design, deployment, governance, and public deliberation.
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