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Georgia Institute of Technology: It’s Just Distributed Computing – Rethinking AI Governance

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Summary of https://www.sciencedirect.com/science/article/pii/S030859612500014X

Argues that the current approach to governing "AI" is misguided. It posits that what we call "AI" is not a singular, novel technology, but rather a diverse set of machine-learning applications that have evolved within a broader digital ecosystem over decades.

The author introduces a framework centered on the digital ecosystem, composed of computing devices, networks, data, and software, to analyze AI's governance. Instead of attempting to regulate "AI" generically, the author suggests focusing on specific problems arising from individual machine learning applications.

The author critiques several proposed AI governance strategies, including moratoria, compute control, and cloud regulation, revealing that most of these proposed strategies are really about controlling all components of the digital ecosystem, and not AI specifically.

By shifting the focus to specific applications and their impacts, the paper advocates for more decentralized and effective policy solutions.

Here are five important takeaways:

  • AI is not a single technology but a diverse set of machine learning applications enabled by distributed computing. It is not new, but an evolution of computing capabilities.
  • The digital ecosystem, comprised of computing devices, networks, data, and software, is essential for understanding AI. AI applications depend on all four elements of this ecosystem.
  • Many policy concerns associated with AI, such as misinformation, bias, and fraud, mirror those that arose with the growth of the Internet.
  • Attempts to regulate AI often lead to proposals for systemic control of the entire digital ecosystem, which can be unrealistic, disproportionate, or authoritarian.
  • A more effective approach to governance involves focusing on specific problems caused by individual machine learning applications rather than trying to regulate "AI" as a whole.
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