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RAND Perspective on AI Power Concentration and Governance Inequality
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A RAND Corporation policy perspective addressing how AI development intersects with power concentration and inequality, relevant to governance and coordination challenges in AI safety discussions. Full content unavailable for detailed analysis.
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Importance: 52/100organizational reportanalysis
Summary
This RAND Corporation perspective examines the dynamics of power concentration and inequality arising from advanced AI development, analyzing governance challenges and policy implications. It likely addresses how AI capabilities could exacerbate existing power imbalances and what institutional responses may be needed.
Key Points
- •Analyzes how advanced AI development may concentrate power among a small number of actors, raising governance concerns
- •Examines inequality dynamics created or amplified by differential access to AI capabilities
- •Considers policy frameworks and governance mechanisms to address power imbalances in AI deployment
- •Situates AI governance challenges within broader geopolitical and institutional contexts
Cited by 1 page
| Page | Type | Quality |
|---|---|---|
| AI-Driven Concentration of Power | Risk | 65.0 |
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The Rise of Generative AI and the Coming Era of Social Media Manipulation 3.0: Next-Generation Chinese Astroturfing and Coping with Ubiquitous AI | RAND
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The Wayback Machine - http://web.archive.org/web/20260228023012/https://www.rand.org/pubs/perspectives/PEA2679-1.html
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PE-A2679-1
The Rise of Generative AI and the Coming Era of Social Media Manipulation 3.0
Next-Generation Chinese Astroturfing and Coping with Ubiquitous AI
William Marcellino, Nathan Beauchamp-Mustafaga, Amanda Kerrigan, Lev Navarre Chao, Jackson Smith
Expert InsightsPublished Sep 7, 2023
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The world may remember 2022 as the year of generative artificial intelligence (AI): the year that large language models (LLMs), such as OpenAI's GPT-3, and text-to-image models, such as Stable Diffusion, marked a sea change in the potential for social media manipulation. LLMs that have been optimized for conversation (such as ChatGPT) can generate naturalistic, human-sounding text content at scale, while open-source text-to-image models can generate photorealistic images of anything (real or imagined) and
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