Today we launched AI Now’s 2023 Landscape Report. In it, we put forth an actionable policy strategy to confront concentration of power in the tech industry.
— AI Now Institute (@AINowInstitute) April 11, 2023
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Quick Overview
This 103-page report articulates what the authors see as the critical need for policy creation around the use of artificial intelligence. There is a useful executive summary. The table of contents lists the following topics:
- ChatGPT and More: Large Scale AI Models Entrench Big Tech Power
- Toxic Competition
- Algorithmic Accountability: Moving Beyond Audits
- SPOTLIGHT: Data Minimization
- Algorithmic Management:
- SPOTLIGHT: Tech and Financial Capital
- AntiTrust
- Biometric Surveillance
- International "Digital Trade" Agreements
- US-China Arms Race: AI Policy as Industrial Policy
- SPOTLIGHT: The Climate Costs
In the two final chapters shown, there are useful timelines included (1) An AI Arms Race Timeline (page 93) and (2) Greenwashing Timeline (page 102).
From the Executive Summary
ChatGPT was unveiled during the last month of our time at the FTC, unleashing a wave of AI hype that shows no signs of letting up. This underscored the importance of addressing AI’s role and impact, not as a philosophical futurist exercise but as something that is being used to shape the world around us here and now. We urgently need to be learning from the “move fast and break things” era of Big Tech; we can’t allow companies to use our lives, livelihoods, and institutions as testing grounds for novel technological approaches, experimenting in the wild to our detriment. Happily, we do not need to draft policy from scratch: artificial intelligence, the companies that produce it, and the affordances required to develop these technologies already exist in a regulated space, and companies need to follow the laws already in effect. This provides a foundation, but we’ll need to construct new tools and approaches, built on what we already have.
Three Key Dimensions
The dominance of Big Tech in artificial intelligence plays out along three key dimensions:
1. The Data Advantage: Firms that have access to the widest and deepest swath of behavioral data insights through surveillance will have an edge in the creation of consumer AI products. This is reflected in the acquisition strategies adopted by tech companies, which have of late focused on expanding this data advantage. Tech companies have amassed a tremendous degree of economic power, which has enabled them to embed themselves as core infrastructure within a number of industries, from health to consumer goods to education to credit.
2. Computing Power Advantage: AI is fundamentally a data-driven enterprise that is heavily reliant on substantial computing power to train, tune, and deploy these models. This is expensive and runs up against material dependencies such as chips and the location of data centers that mean efficiencies of scale apply, as well as labor dependencies on a relatively small pool of highly skilled tech workers that can most efficiently use these resources. 12 Only a handful of companies actually run their own infrastructure – the cloud and compute resources foundational to building AI systems. What this means is that even though “AI startups” abound, they must be understood as barnacles on the hull of Big Tech – licensing server infrastructure, and as a rule competing with each other to be acquired by one or another Big Tech firm. We are already seeing these firms wield their control over necessary resources to throttle competition. For example, Microsoft recently began penalizing customers for developing potential competitors to GPT-4, threatening to restrict their access to Bing search data. 13
3. Geopolitical Advantage: AI systems (and the companies that produce them) are being recast not just as commercial products but foremost as strategic economic and security assets for the nation that need to be boosted by policy, and never restrained. The rhetoric around the US-China AI race has evolved from a sporadic talking point to an increasingly institutionalized stance (represented by collaborative initiatives between government, military, and Big Tech companies) that positions AI companies as crucial levers within this geopolitical fight. This narrative conflates the continued dominance of Big Tech as synonymous with US economic prowess, and ensures the continued accrual of resources and political capital to these companies
Four Strategic Priorities
Four strategic priorities emerge as particularly crucial for this moment:
1. Employ strategies that place the burden on companies to demonstrate that they are not doing harm, rather than on the public and regulators to continually investigate, identify, and find solutions for harms after they occur;
2. Break down silos across policy areas, so we’re better prepared to address where advancement of one policy agenda impacts others. Firms play this isolation to their advantage;
3. Identify when policy approaches get co-opted and hollowed out by industry, and pivot our strategies accordingly:
4. Move beyond a narrow focus on legislative and policy levers and embrace a broad-based theory of change.