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The Rise of the Bots: Are AI Responses Skewing Software Surveys?

December 22, 2025 by BBG News

Figure 1.Illustrative Pattern Detection Pattern recognition reveals underlying structure, where repeating motifs - akin to $x_i$ within a defined space - emerge from complex data and suggest inherent organizational principles.

A new study examines how the increasing use of artificial intelligence to complete online surveys is impacting the reliability of data in empirical software engineering research.

Categories Science

The Human Face of AI: Does Likeness Build Trust?

December 22, 2025 by BBG News

The study demonstrates that design choices evoking human likeness in artificial intelligence significantly influence perceptions of anthropomorphism, as evidenced by coefficient estimates from Ordinary Least Squares regressions across ten Likert-scale measures; further analysis of the “humanlike” item reveals consistent effects across sampled countries, suggesting a broadly applicable relationship between design and perceived human qualities.

New research reveals that designing artificial intelligence to appear more human increases perceptions of personhood, but doesn’t guarantee greater user trust across different cultures.

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Beyond Interviews: How AI is Deepening Our Understanding of Aging

December 22, 2025 by BBG News

A new wave of research is combining the richness of qualitative data with the power of computational methods to reveal more nuanced insights into the experiences of older adults.

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Giving Robots a Voice – and Hands

December 22, 2025 by BBG News

The quadrupedal robot maintains dynamic stability while simultaneously expressing generated co-speech gestures, demonstrating a convergence of locomotion and communicative action within a single embodied system.

New research demonstrates an end-to-end system enabling humanoid robots to express themselves with natural, synchronized gestures alongside spoken language.

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Beyond the Algorithm: How Students Really Trust AI Learning Tools

December 22, 2025 by BBG News

New research reveals that student acceptance of AI-powered learning assistants isn’t just about technical accuracy, but deeply rooted in psychological factors.

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Cooperative Robots: Smarter Scheduling for Human-Robot Teams

December 22, 2025 by BBG News

A mobile manipulator confronts the inherent complexity of task sequencing, necessitating a strategic evaluation of station visitation order and precise base positioning to optimize operational efficiency-a problem framed not as solvable, but as a continuous negotiation with inevitable logistical compromises.

New research details a simulation framework for optimizing the movements and task order of mobile robots working alongside humans, boosting efficiency and safety.

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The Logic of Intelligence: Building AI with Competitive Coding

December 22, 2025 by BBG News

A new framework proposes that artificial intelligence can be advanced by framing concept formation as a search for stable, communicable representations achieved through competitive optimization of information structures.

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The Human Spark in AI Collaboration

December 22, 2025 by BBG News

New research reveals how people and language models co-create, demonstrating that human creativity remains central even as AI adapts to our emotional cues.

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Busy Signals: How Robots Can Get Your Attention (and Your Order Right)

December 22, 2025 by BBG News

Following an initial gesture of deference-a slight bow-the robot subtly reorients a cup towards the user, enacting a nuanced communication of service intention through spatial positioning.

New research explores how service robots can effectively communicate with customers who are already occupied, improving both order accuracy and the overall user experience.

Categories Science

When AI Systems Collide: Navigating the Risks of Complex Interactions

December 22, 2025 by BBG News

The study elucidates a landscape of artificial intelligence approaches, demonstrating how diverse methodologies-ranging from symbolic reasoning to connectionist systems and Bayesian networks-each represent a distinct paradigm in the pursuit of intelligent computation, with their efficacy often determined by the inherent structure of the problem being addressed and the available computational resources, as formalized by the no-free-lunch theorem: $f(x) = \sum_{i=1}^{n} w_i \phi_i(x)$, where $w_i$ are weights and $\phi_i(x)$ are feature functions.

As artificial intelligence becomes increasingly interwoven into critical infrastructure, understanding the potential for systemic failures arising from interactions between multiple AI agents is paramount.

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