AI and the Future: Key Questions

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The US elections serve as a strong signal for the future of AI. Key dynamics to monitor for both national and global impact include:

1.    Oversight of dual-use consumer and defense technology: Will there be stricter oversight of consumer tech companies that supply the defense sector, and will legislation mandate a clear separation between consumer and defense divisions? 

This issue carries global implications, particularly as many foreign governments view compliance with the US CLOUD Act as a critical national defense and security decision. Major US tech corporations increasingly operate as military contractors or suppliers: hyperscalers such as Amazon, Microsoft, Alphabet (Google), and Oracle (notably through the Joint Warfighting Cloud Capability, or JWCC), alongside platforms such as Palantir, SpaceX, Nvidia, OpenAI, Anthropic, and Meta (via Llama). 

Furthermore, consumer tech firms regularly acquire defense-oriented capabilities. 

Should companies be permitted to transfer data harvested from consumer operations directly into defense workflows?

Moreover, should defense-focused technology companies be tracked through dedicated stock exchanges or specialized indices to enforce tailored disclosure standards? While this could improve transparency for investors, it raises the question: which agency would regulate it?

2.    Subsidization and expansion: Much of current AI growth relies on heavy subsidies (such as tax breaks for data centers, subsidized energy, and preferential loan rates) alongside layered investment structures. 

Does this state support encourage global tech firms to pursue more aggressive or predatory expansion strategies in international markets (free accounts for data collection in emerging markets or for students), especially given their presence across more than 100 countries through subsidiaries and joint ventures?

3.    Trade restrictions and AI sovereignty: Will geopolitical friction produce a more strategic, transparent framework for export and import embargoes? 

Furthermore, will the concept of individual "AI sovereignty" morph into "AI blocs"—alliances organized around shared supply chains rather than geographic proximity or traditional defense treaties?

4.    Algorithmic governance and multilateralism: Will there be greater legal oversight, mandatory auditing, and systemic algorithmic transparency? 

Could AI governance serve as the catalyst that revives multilateral diplomacy?

5.    Labor market stability: Despite unprecedented profitability, tech giants have introduced substantial volatility into domestic and international labor markets. How will this ripple effect evolve? 

Will workers secure stronger protections for their livelihoods and an improved quality of life? Will labor markets transition away from the precarious gig economy toward more stable employment, acknowledging the substantial portion of our lives spent at work? Could we see a renewed emphasis on organizational culture and human-centered workplace expertise?

6.    Public vs. private balance in public-interest sectors: In sectors heavily dependent on public funding—such as education, healthcare, and civil governance—will authority rebalance from private vendors back to public institutions? 

While legacy systems require modernization, a genuinely human-centric model does not deploy AI merely for its own sake; it adopts a care-centric approach where the human problem remains paramount. Does this require a return to empathetic design-thinking methodologies to contextualize data, rather than deploying complex analytics without understanding the root problem?

7.    Intellectual property and global standards: Will intellectual property frameworks be re-evaluated? While copyright terms are typically longer compared to patents, their legal application to AI training data remains contested.

 Can the World Intellectual Property Organization (WIPO) establish unified global standards, or will AI IP governance default to a fragmented web of bilateral agreements?