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Can We Really Control AI?

AI is playing an increasingly larger part in our lives and the world around us. By some projections, we will have AGI, or Artificial General Intelligence, in less than a decade. Some are even arguing we are already there. Regardless of this timeline, it is clear that AI unchecked has potentials to cause great harms. Can we control or contain AI such that we can stop those harms? It’s not easy.

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FeaturedTranslation

Towards human-like perception: Learning structural causal model in heterogeneous graph

In recent years, the growing demand for modeling complex systems has brought heterogeneous graph neural networks (HGNNs) into the spotlight. However, existing methods often suffer from fixed inference processes and spurious correlations, limiting their interpretability and generalization ability. To address these challenges, this study proposes a novel heterogeneous graph learning framework that simulates human perception and decision-making processes, enhancing both predictive performance and interpretability.

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FeaturedProfessional Development

To Succeed, Find a Career Partner

Super-partnerships exist between scholars connected within densely-knit collaboration networks. Understanding how such relationships affect scholars’ careers is of great importance. In this paper, focusing on the longitudinal aspects of scientific collaboration, we analyze collaboration profiles from the egocentric perspective and use analytic extreme value thresholds to identify super-partners. We explore the characteristics of super-partners and the added value of a long-term commitment, which provides quantitative insights into the effect on scientific collaboration associated with close collaboration.

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FeaturedFrontiersOpinion

Looking Backwards to See Ahead: The Case of Expert Systems Development in Libraries

During the current moment, as generative AI dominates our thinking, both for its extraordinary performance and serious flaws, a new direction is needed. The way forward may involve looking backward. The addressing the deficiencies of generative AI would benefit from reviewing, and incorporating, some of the lessons from expert system development during the late 20th century.

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FeaturedTranslation

A New Critical Lens to Examine Factors Influencing Differences in Global Scholarly Communication Experiences

If scholars’ research outputs are high quality and add to knowledge in a field of scientific study, why should their geographical location or any aspect of their identity matter? Evidence demonstrates that cognitive and ideological differences are beneficial to research. Unfortunately, experience and the literature show differences between scholars’ geographical locations or their identities and their ability to obtain, produce, and distribute research outputs. The disparities can be described by focusing on geopolitical positions, such as low- and middle-income countries compared to high-income countries, or differences can be examined through a racial or ethnic lens, or any number of ways we identify individuals or groups of people.

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