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2,868 papers
Most teams believe AI requires tearing out legacy infrastructure. David Ohnstad explains why this myth costs companies weeks of debate and delayed shipping. Your existing SaaS foundation can support enterprise AI—here's how. Full article: https://davidohnstad.net/enterprise-ai-platform-replacement-myths/
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Explainable AI (XAI) has emerged as a critical area of research, driven by the need for trust and accountability in increasingly complex AI systems. However, many existing XAI techniques offer only superficial explanations, often failing to capture the underlying causal mechanisms driving AI decisions. This paper propo...
The findings indicate that the competencies of teachers for artificial intelligence should be viewed as a multidimensional basis for further research, improvement of teaching practice, and planning of professional development in the field of application of AI in education.
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Ethical implications are derived for the individual production of historical content with AI and for the role of distribution platforms, and the analytical limits of the case are discussed in order to open an empirical research agenda in this emerging field.
A methodological approach to the intellectualization of enterprise administration through the economics of managerial decision-making is substantiated, rather than by the number of AI tools implemented, by combining systems and institutional perspectives, decision theory under risk, stochastic optimization, and scenari...
Abstract Background Artificial intelligence (AI) has shown substantial potential in tuberculosis (TB). However, physicians’ distrust of “black-box” algorithms remains a major barrier to clinical adoption. Although explainable AI (XAI) has emerged to enhance transparency, limited evidence exists regarding TB physicians’...
SERVING TODAY’S SYSTEM NOW MEANS SERVING HUMANITY’S SELF-DESTRUCTION There was a time when the system needed human beings. It needed their labor, their attention, their imagination, their obedience, and their bodies. It needed workers to produce value, consumers to absorb it, soldiers to defend it, voters to legitimize...
Cybersecurity threat detection systems are increasingly reliant on Artificial Intelligence (AI) models, but these systems frequently operate as "black boxes," making it difficult for human analysts to understand *why* a particular activity is flagged as a threat. This paper proposes a novel Explainable AI (XAI) system...
This study develops machine learning models for early Polycystic Ovary Syndrome prediction using a structured clinical dataset with 42 features and 542 patient records and demonstrates that ensemble models can effectively capture non-linear feature interactions in clinical data.
Explainable AI (XAI) has emerged as a critical area of research, driven by the need for trust and accountability in increasingly complex AI systems. However, many existing XAI techniques offer only superficial explanations, often failing to capture the underlying causal mechanisms driving AI decisions. This paper propo...
A Blog post by Dharma-AI on Hugging Face
Research Manager Mike Walker reflects on a career spanning hacker culture, cybersecurity, and AI, sharing lessons about trust, teamwork, leadership, and why solving difficult problems requires curiosity, judgment, agility—and an understanding of the rules. The post Learn the rules: The hacker mindset appeared first on Microsoft Research.
GPT-Lab
· gpt-lab.eu
Nov 3, 2026
Is your company’s AI sovereign? A practical guide for CIOs on AI vendor lock-in, EU Data Act switching, cloud sovereignty, and testing your exit plan before you need it. The post Sovereignty Is the Option to Leave appeared first on GPT-Lab.
The MIT professors collaborated to identify the first AI-discovered antibiotic, a scientific breakthrough that is widely recognized as a milestone in AI-driven drug discovery.
Five MIT faculty members and two additional alumni are honored with fellowships to advance research on beneficial AI.
MIT professors Adam Berinsky and Chara Podimata discuss a new project to track how AI chatbots are responding to questions about the 2026 U.S. midterm elections.
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