Readings and Links:
Introduction
AI is treated as an inevitable force, one upon which we have no control, both of its development and the way it defines our present and future. In “What Kind of World is AI Building?” Jeff de Kleijn and Antoine Fourmont-Fingal contest this inescapability, while cautioning that assuming we cannot participate in AI’s evolution turns perceived powerlessness into reality.
And this abdication is a problem, they insist, because it leaves a small number of companies in charge of what may be the most consequential technological development of this century. Absent public involvement, a handful of companies will decide the priorities that shape AI’s rollout. De Kleijn and Fourmont-Fingal suggest that the current monopolization of AI technologies creates three trends:
Scale. Companies are focused on amassing resources and increasing production to achieve efficiency and maximum profit. This insistence on scale erases the potential for a variety of ideas, trading specificity for uniformity.
Coherence over Intelligibility. Another result of the companies’ preferences for uniformity, AI is trained to provide surface-level summaries, stripped of ambiguity and variance. An inability to convey nuance should concern us, De Kleijn and Fourmont-Fingal insist, because our communities are composed of different voices, and we must be able to acknowledge and reconcile disagreement to coexist.
Massification and Atomization. De Kleijn and Fourmont-Fingal rely on scholars of totalitarianism such as Hannah Arendt to draw connections between the stripping of individuality and mass suppression. When people are discouraged from discovering their own morals and values and instead encouraged simply to comply with external directions, they become easier to control. If you are trained to obey orders rather than the dictates of your own conscience, you will be a cog in the machine—the controlled—and less likely to see the machine as a tool—which you can control.
In contrast to these trends dictated by a few monopolies, De Kleijn and Fourmont-Fingal offer another vision of AI’s future, one in which we voice our own opinions. If it will impact our lives, shouldn’t we all have a say in AI’s formation? They present democracy as the answer, enacted through decentralization of the powers determining AI, as well as civic technologies, which use technology to increase the public’s involvement in government actions. Further, they assert that AI training should occur within the context of a broader educational agenda, including ethics.
As you read De Kleijn and Fourmont-Fingal’s article, consider which priorities might control AI’s development other than the ones discussed here, and what would be needed in order to make those priorities a reality.
Preparing to Read the Selection
Other than the links, you will need a few other items to prepare adequately for a discussion of this reading:
- Print a copy of the reading.
- A pen or pencil to take notes on (literally) the reading. Some of you may have heard this described as text annotation.
- Effective text annotation includes: marking interesting portions of the reading you would like to think about further, underlining or circling words you need to look up to understand a passage, circling names or dates, marking passages you feel are important to the author’s point, and writing questions you have for the author in the margins of the page.
- Close reading and careful annotation will help you read more intently and deeply, gaining a level of understanding of material you will need in a college setting to confidently engage in a conversation with peers and faculty about a text.
- A separate piece of paper. Treat reading course materials as you would written correspondence, a written conversation.
- Write down questions you have for the author, your classmates, and your professor.
- You will be engaged in correspondence with others over this material. Your FYS instructor expects you to be prepared to share your ideas on this reading when you arrive on campus.
- To assist you in this effort, we include a series of questions to consider and respond to prior to reading, while you read, and after you read to focus attention, analysis, notes, and future conversation.
Before You Read Questions
- What are common ideas about AI that you have encountered?
- Investigate which companies are most heavily involved in AI technologies.
- How might AI impact your learning in college? How did it impact your learning in high school?
As You Read Questions
- What ideas about values, the environment, and civic participation—topics central to the missions of Catawba College’s Lilly Center for Vocation and Values, the Center for the Environment, and the North Carolina Center for Politics and Public Service—does the article touch upon?
- What skills do you think will be most important in an AI-driven world?
After You Read Questions
- Are there any common ideas about AI that this reading challenged or asked you to consider in new ways?
- We are often told that AI’s integration into our lives is inevitable. If instead we believe that we are in the driver’s seat, how might that change the future of AI?
- Should we be excited, worried, or both about AI’s role in society, and what kind of future do you want AI to help create?
Context and Sources for Review
What is AI? Basic AI Literacy and Distinguishing between Industry and Research
Artificial Intelligence (AI) has become a common term in today’s society, but for the average person it is a black-box term. You may have little understanding of what it is, the types of artificial intelligence models, what their functional purpose is, and how they work. This information is foundational to understanding the impact of our interaction with AI and to be informed citizens of its impact on our society. We seek to be literate in AI, whether you use it or not.
Types of AI: Often when referring to AI, people are talking about Generative AI; it is the most common. But when referring to Artificial Intelligence, it covers a field of mathematics and computer science that enables machines and technology to do tasks that would otherwise need human intelligence. Language matters when discussing AI models, by naming the function of the model's usage becomes clear, and it helps others understand the variety of artificial intelligence (See Artificial Intelligence Explained below).
AI Literacy, as defined by AILit Framework, a joint initiative of the European Commission (EC) and the Organization for Economic Cooperation and Development (OECD), is:
“The technical knowledge, durable skills, and future-ready attitudes required to thrive in a world influenced by AI. It enables learners to engage, create with, manage, and design AI, while critically evaluating its benefits, risks, and ethical implications.”
Industry versus Research: AI research and development in industry has often been ahead of academic research. Access to funding, lack of continuous oversite, and the question of “can we?” lead to more rapid expansion in technological innovation, all the while being constructed for the masses and financial gain. Academic research is subjected to rigorous standards of risk assessment, institutional oversight, and critical review of findings and innovation by peers in the field, which makes progress more time intensive. It is often circulated in academic spaces and less likely to be viewed by the masses (See “How the Tug-of-War Between Industry and Academia is Shaping AI Research” below for more).
Sources for Review
Educational Application, Interactions, and Implications
Technology integration in today’s classroom is nothing new, as the integration of digital tools in classrooms has evolved over the past 50 years; however, the rapid growth of AI poses additional implications and considerations. So, what effect does this have on learning? De Kleijn and Fourmont-Fingal (2025) state that AI produces coherent over intelligible results, suggesting that replacing humans as a tool for teaching and learning misses the mark by prioritizing polished, surface-level responses over deep understanding, critical thinking, and meaning-making. In doing so, AI could potentially obscure the learning process itself by reducing opportunities for struggle, questioning, and cognitive engagement, ultimately weakening students’ ability to construct knowledge, articulate reasoning, and develop independent thinking skills. On the other hand, when used intentionally, AI can serve as an invaluable tool providing quicker access to material and accessible entry points for complex content. Ultimately, educators and students must consider whether AI tools are being used to amplify thinking or replace it.
Sources for Review:
- Brookings Institute, A New Direction for Students in an AI Driven World: Prosper, Prepare, Protect
- Ethics, Data, and Decision-Making When Using Artificial Intelligence (AI) to Support Effective Instruction, Center for Innovation, Design, and Digital Learning
- AI Fluency for Students, Anthropic
- Resources for AI Literacy, NC Live
