The final aspect of AI Literacy is interconnectedness. This means understanding how the development and use of Generative AI is complex. This complexity is much more pronounced than that of other Education Technologies because Generative AI is a general-purpose technology that touches all facets of society. Generative AI is entangled in larger institutional, social, political, and cultural structures, all of which impact individual perceptions and use of Generative AI tools as well as legislation, policy, and emerging practice. Because of this, AI Literacy requires the ability to understand the multiple factors that might be influencing Generative AI at both the micro and macro level.

Examples of larger complexities impacting Generative AI development include:

• The geopolitics of AI, including restrictions on the export of AI technologies and the impact on supply chains of key components to develop AI infrastructure, which impacts who is able to develop AI technologies (https://www.forbes.com/sites/bernardmarr/2024/09/18/the-geopolitics-of-ai/ )

• The regulation of AI tools, including discussion around setting global and national standards for AI development (https://iapp.org/resources/article/global-ai-legislation-tracker/ )

• The risks and potential for a small number of companies to hold control over foundation models of AI (https://www.economic-policy.org/79th-economic-policy-panel/ai-monopolies/ )

• The potential and perceived impact on labour markets and jobs skills for the future because of increasing AI capabilities (https://www.weforum.org/stories/2025/01/future-of-jobs-report-2025-jobs-of-the-future-and-the-skills-you-need-to-get-them/ )