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Implementing AI represents a significant structural transformation for organizations, impacting decision-making and workflows. A control versus flexibility dilemma emerges as organizations strive to balance strict regulations with the need for innovative AI applications. While regulations are essential for accountability, excessive controls can hinder the adoption of AI in dynamic environments.
The study highlights three categories of tensions: values-related, implementation, and impact-related tensions that shape AI governance. Organizations must reconcile conflicting stakeholder views on AI priorities, such as efficiency versus social responsibility. Addressing these challenges requires transparent governance and interdisciplinary collaboration to ensure AI aligns with societal values.
• AI adoption presents challenges in balancing ethics and innovation.
• Organizational tensions influence AI governance and implementation.
AI ethics involves the moral implications of AI technologies and their societal impact.
Algorithmic discrimination refers to biases in AI systems that can lead to unfair treatment of certain groups.
The black box problem highlights the lack of transparency in AI decision-making processes, complicating accountability.
Isomorphic Labs, the AI drug discovery platform that was spun out of Google's DeepMind in 2021, has raised external capital for the first time. The $600
How to level up your teaching with AI. Discover how to use clones and GPTs in your classroom—personalized AI teaching is the future.
Trump's Third Term? AI already knows how this can be done. A study shows how OpenAI, Grok, DeepSeek & Google outline ways to dismantle U.S. democracy.
Sam Altman today revealed that OpenAI will release an open weight artificial intelligence model in the coming months. "We are excited to release a powerful new open-weight language model with reasoning in the coming months," Altman wrote on X.
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