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Research on the economics of AI safety investment
webCredibility Rating
3/5
Good(3)Good quality. Reputable source with community review or editorial standards, but less rigorous than peer-reviewed venues.
Rating inherited from publication venue: ResearchGate
An early (2012) economics-focused thesis on AI safety investment gaps; useful for understanding the economic and policy framing of AI safety, though predates many modern alignment concerns and may have limited empirical grounding given its speculative forward-looking nature.
Metadata
Importance: 38/100working paperanalysis
Summary
This thesis examines AI safety investment through market failure theory, identifying how public goods characteristics, information asymmetries, coordination problems, and limited liability frameworks create structural underinvestment in AI safety. It evaluates policy interventions including direct funding, tax incentives, and regulatory frameworks, proposing institutional arrangements to support long-term safety investment.
Key Points
- •AI safety exhibits public good properties, externalities, and information asymmetries that cause markets to systematically underinvest in safety measures.
- •Competitive dynamics, knowledge spillovers, and coordination failures create structural barriers to safety investment even when socially optimal.
- •Policy options assessed include direct funding mechanisms, prize competitions, public-private partnerships, and regulatory frameworks balancing innovation with precaution.
- •Case studies from early ML applications (automated trading, recommendation systems, autonomous vehicles) illustrate how market failures manifest in practice.
- •Draws parallels with nuclear safety and biotechnology governance to situate AI safety within established economic frameworks for transformative technology governance.
Cited by 1 page
| Page | Type | Quality |
|---|---|---|
| Governance-Focused Worldview | Concept | 67.0 |
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ThesisPDF Available
# Economics of AI Safety Investment: Market Failures and Policy Responses
- February 2012
DOI: [10.13140/RG.2.2.36724.26240](https://doi.org/10.13140/RG.2.2.36724.26240)
Authors:
[](https://www.researchgate.net/profile/Uchechukwu-Ajuzieogu)
[Uchechukwu Ajuzieogu](https://www.researchgate.net/profile/Uchechukwu-Ajuzieogu)
- [University of Nigeria](https://www.researchgate.net/institution/University-of-Nigeria2)
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## Abstract
This publication examines the complex economic dimensions of artificial intelligence safety investment through the lens of market failure theory and explores potential policy responses to address identified inefficiencies. As artificial intelligence technologies advance beyond narrow applications toward more general capabilities, questions regarding safety measures and their economic underpinnings become increasingly salient. This work, situated in the technological landscape of 2012, provides a forward-looking analysis of the economic challenges that may constrain optimal investment in AI safety research and implementation.
The first chapter establishes a theoretical framework for conceptualizing AI safety as an economic problem, identifying characteristics such as public good provisioning, information asymmetries, and externalities that create market inefficiencies. Drawing parallels with established domains such as nuclear safety and biotechnology governance, we demonstrate how AI safety presents both familiar and novel economic challenges that warrant systematic analysis.
Chapter two provides a detailed examination of specific market failures impeding adequate investment in AI safety measures. We analyze how coordination problems, competitive dynamics, knowledge spillovers, and limited liability frameworks create structural barriers to safety investment, even when such investment would be socially optimal. Through cas
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