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Illinois State’s ‘End of the World’ Class Puts AI on Trial

Nic Reeve7 min read
Illinois State’s ‘End of the World’ Class Puts AI on Trial
Students Confront AI Ethics in Illinois State’s ‘End of the World’ Classroom

In a seminar room at Illinois State University (ISU), an apocalyptic thought experiment is helping students grapple with one of the most disruptive technologies of their lifetimes: artificial intelligence. Framed as “feminism at the end of the world,” the class invites students to imagine futures shaped by climate crisis, economic collapse, and runaway automation—and then ask what justice, care, and responsibility look like when AI is woven into every aspect of life.

The course, titled WGS 391/491: Feminism at the End of the World, is taught by Dr. Jacklyn Weier in Illinois State’s Women’s, Gender, and Sexuality Studies program. Using speculative fiction, feminist theory, and contemporary reporting on AI, Weier’s students interrogate who benefits from emerging technologies and who is left more vulnerable when those tools are deployed in unequal societies.

‘End of the World’ as a Lens on AI

Rather than treating AI as a neutral tool, the course positions it as a technology emerging in an already crisis-ridden world. Students consider scenarios in which climate disasters, pandemics, or authoritarian politics intersect with increasingly powerful AI systems. That apocalyptic framing, Weier explains in the Illinois State University News feature, is less about doomsday spectacle and more about clarity: it allows students to see existing inequalities—and the potential amplification of those inequalities—without the distractions of business-as-usual.

Class discussions draw on questions such as: Who designs AI systems, and whose values are embedded in them? Which communities are most exposed when automated decision-making is used in policing, immigration, or social services? How might feminist and queer perspectives offer alternative models for building or governing AI, especially in times of crisis?

Students are encouraged to treat AI not only as a technical system but as a social infrastructure: something that redistributes power, labor, and risk. That perspective resonates with broader concerns raised by scholars and civil-society groups about bias in algorithms, surveillance capitalism, and the concentration of AI capabilities in a small number of corporations.

Illinois State’s Wider Debate Over AI in the Classroom

The apocalyptic classroom arrives amid a campus-wide—and statewide—reckoning over how AI should be used in education. Illinois State has devoted increasing resources to helping faculty and students navigate generative AI tools like ChatGPT, Gemini, and Copilot, and to clarifying when such tools enhance learning and when they undermine it.

In 2025, the university’s Office of the Cross Endowed Chair in the Scholarship of Teaching and Learning launched a grant program inviting faculty to study how generative AI is used or resisted in courses, and what that means for student learning, assessment, and equity. Those projects are structured around a central question: how is AI being integrated into higher education, and with what consequences for teaching and learning at ISU?

Illinois State’s professional development arm has since published guidance for instructors on generative AI in the classroom. That guidance emphasizes transparency and critical engagement: instructors are urged to state clearly in their syllabi when AI use is permitted, explain why particular assignments prohibit AI, and design assessments that prioritize process, reflection, and local or experiential knowledge.

Faculty workshops encourage instructors to have students critique AI-generated content, practice fact-checking, and reflect on where AI’s limitations become visible—especially when it comes to hallucinations, bias, and context. The goal is not to ban AI outright but to turn it into an object of analysis and a prompt for metacognition, much like what happens in Weier’s apocalyptic classroom.

State Policy: AI Can Assist, But Not Replace, Human Teachers

The conversations at Illinois State unfold against a backdrop of new laws in Illinois that specifically address AI in education. Recent legislation requires community colleges to ensure that courses are taught by qualified human faculty and explicitly prohibits using AI systems as the sole source of instruction in place of an instructor. At the same time, the law clarifies that faculty are allowed to use AI as a teaching tool—whether for generating practice problems, simulating scenarios, or tailoring feedback.

Another measure directs the Illinois State Board of Education to develop statewide guidance on AI in K–12 settings. That guidance must explain how AI works, offer examples of instructional uses, address data privacy and security, and highlight the risk of unintended bias baked into AI products. It also calls on educators to explicitly teach responsible and ethical AI use, preparing students to evaluate automated systems rather than accept them uncritically.

Illinois education officials have since released public-facing guidance that echoes those themes, stressing that AI should support, not supplant, human relationships in teaching and learning. The documents encourage schools to balance innovation with vigilance, especially when it comes to student data and the potential for algorithmic discrimination.

An ‘Apocalyptic’ Syllabus Meets Real-World Tech

Within this rapidly shifting policy and technological landscape, ISU’s “end of the world” class serves as a kind of laboratory. Students might read feminist science fiction that imagines AI governing resource distribution after climate collapse, and then compare those visions with real-world deployments of predictive analytics in disaster response or public assistance programs.

Assignments invite students to bring news coverage, corporate marketing, and government documents into conversation with theoretical texts. For example, a student might juxtapose a tech company’s promise to use AI for equitable healthcare with reports of biased diagnostic algorithms, or analyze how AI-enhanced policing could change under conditions of social unrest or environmental migration.

By situating AI in imagined end-times, Weier’s course asks students to strip away the sheen of inevitability that often accompanies innovation narratives. If AI is introduced into a fragile or unjust world, she asks, what safeguards and alternative designs would be needed to prevent it from reinforcing existing hierarchies—or making crises worse?

Feminism, Care, and the Future of Work

The feminist framing of the course pushes students to pay particular attention to care work, reproductive labor, and the often-invisible human effort that underlies technological systems. Discussion topics include:

  • How AI may reshape care professions, from nursing to education, and what happens when emotional labor is automated or monitored.
  • Who performs the ghost work of data labeling, content moderation, and user support that keeps AI systems running.
  • How automation might intersect with gender, race, and class in future labor markets, especially under crisis conditions.
  • What a more just AI ecosystem would require in terms of labor protections, democratic oversight, and alternative ownership models.

Students are encouraged to imagine AI futures in which care, reciprocity, and mutual aid are central design principles rather than afterthoughts. In some projects, that means sketching out hypothetical policies for community-run data trusts or workers’ cooperatives overseeing AI tools in essential services.

AI Education Beyond One Classroom

Illinois State is also building technical capacity around AI. The university has promoted AI-focused professional development sessions for faculty, including workshops on demystifying AI for teaching and learning and on designing assignments that cannot easily be outsourced to generative tools.

In 2026, ISU highlighted a new “AI + Robotics” initiative that introduces pre-service STEM educators to so-called physical AI—systems embedded in robots and other devices. The project, supported by an internal innovation grant, aims to help future teachers understand both the capabilities and limits of AI, and to translate abstract concepts into hands-on classroom activities.

Another Illinois State faculty member, Dr. Elahe Javadi from the School of Information Technology, was selected for the inaugural cohort of NSF NAIRR AI Education Fellows. That national role positions ISU at the intersection of AI research and education policy, and underscores the university’s effort to engage with AI not only as an object of critique but as a field in which its faculty and students can lead.

Questioning the Future, Not Just the Tools

The apocalyptic classroom at Illinois State shows how humanities and social science courses can complement technical and policy efforts around AI. By combining speculative scenarios with rigorous critique, students learn to move beyond questions like “Is AI good or bad?” and toward more specific, grounded inquiries: Which AI, deployed where, under whose control, and with what safeguards?

For Weier’s students, the end of the world is less a prophecy than a lens—a way to see clearly the stakes of technological change and the kinds of futures they are willing to build or resist. In that sense, Illinois State’s experiment in apocalyptic pedagogy offers a model for universities everywhere: treat AI not only as a tool to be mastered, but as a system whose power must be scrutinized, contested, and, where possible, redirected toward more just worlds.

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AInews: Chicago Scholars Push Back on AI Apocalypse Fears While Urging Real-World Safeguards On September 14, 2026, Chicago television segment AInews reported that experts from the University of Chicago and Northwestern University argue fears that artificial intelligence will soon wipe out humanity are overstated, even as they call for tighter guardrails on real-world AI risks. What are Chicago AI experts actually saying about human extinction risks? Chicago computer scientists say current AI systems do not pose an imminent existential threat to humanity, but they stress that policymakers and engineers still need to address concrete dangers such as misuse, cyberattacks and economic disruption. Their message: dial down the apocalypse talk, and focus on practical safeguards. In the ABC7 Chicago report published on September 14, 2026, Hank Hoffmann, chair of the University of Chicago’s Computer Science Department, addressed popular fears that AI could soon destroy humanity. 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A 2025 review in an open‑access medical and risk journal concluded that the likelihood of human extinction from external threats such as asteroid impacts and supervolcanoes is “extremely low” based on available data, while the probability from human-generated dangers like nuclear war or environmental collapse is harder to quantify but clearly serious enough to justify prevention efforts. Chicago experts situate AI inside that larger map of threats: not the sole or dominant route to extinction today, but a force that could amplify other crises if left uncontrolled. What real dangers from AI systems are these scholars warning about? While rejecting near-term apocalypse scenarios, Chicago and Northwestern scholars are explicit about concrete threats: AI tools used for cyberattacks, disinformation, fraud and surveillance, and advanced models that can escalate existing risks such as biological weapons or financial instability. They argue these hazards demand policy and technical responses now. Diakopoulos has highlighted cybersecurity as an area where AI already increases risk. He cautioned that criminals can harness generative models to write malware or phishing campaigns at scale, making existing cybercrime more efficient. His lab’s work examines how different news outlets frame these risks, since media narratives influence which AI harms legislators treat as urgent. Northwestern’s Buffett Institute reported on September 10, 2026, that more than 100 AI and cybersecurity companies warned the U.S. federal government about emerging “dramatic” expansions in the scale and sophistication of AI-powered cyberattacks. The warning, issued in a joint letter, argued that increasingly powerful models could allow attackers to automate reconnaissance, exploit discovery and social engineering at a pace human teams cannot match. Signatories pressed for stronger regulatory standards for model access, auditing and secure deployment, focusing on practical controls rather than speculative extinction scenarios. Risk analysts in the broader AI safety community describe another pathway: AI acting as a “force multiplier” on other known threats. A 2026 analysis on catastrophic risk argued that the “single most probable path to civilizational collapse” is not a lone AI system deciding to attack humanity, but advanced models amplifying crises such as cyberwarfare, engineered pandemics or financial instability. That paper stresses cascades, where automation and optimization tools accelerate dangerous actions by humans—for instance, making it easier to design biological agents or coordinate attacks. The scenario aligns with Chicago experts’ emphasis on misuse and systemic impact over science-fiction narratives about self-directed machine hostility. How do Chicago experts view doom messaging by AI industry leaders? Chicago academics criticize the way some AI executives promote extinction narratives, arguing that “doom trolling” and dramatic talk of “p(doom)” can distort public priorities. They say alarmist messaging from companies that build these systems risks confusing voters and policymakers about which AI harms are most urgent. On PBS’s “Amanpour and Company,” computer science professor Cal Newport described what he calls “doom trolling” by large AI firms. Newport defined doom trolling as the “strange” pattern of AI companies trying to convince customers that their own products could lead to “massive devastation” down the line. He argued that this rhetoric is misleading and can overshadow more immediate problems related to labor, privacy and concentration of power. Fortune’s September 12, 2026 interview with OpenAI CEO Sam Altman showed how that messaging enters mainstream debate. Altman described the “probability of doom,” or “p(doom),” as a real concept discussed inside the AI community, even as he pressed for balanced regulation and continued model development. Altman’s comments reflected a split narrative: he acknowledges low-probability catastrophic risk while arguing that the technology’s benefits justify ongoing investment. Chicago analysts worry that repeated focus on p(doom) can crowd out attention to verifiable harms and measurable indicators such as job data, cyber incidents and bias audits. Outside Chicago, prominent researchers have also pushed back against extreme doom rhetoric. Meta AI pioneer Yann LeCun told Axios in May 2026 that predictions of 20% job loss from AI in the near term were “ridiculously stupid.” He said current systems are “nowhere near” replacing half of white‑collar work, and called the broader extinction narrative “extremely destructive” because it causes psychological harm. What steps are universities and policymakers taking in response to these concerns? Universities in Chicago are adjusting classroom rules, research agendas and public engagement strategies to keep AI’s risks manageable, while policymakers field warnings from industry and academia. The current focus is on governance, transparency and restraint in high-impact areas rather than on banning AI outright. The University of Chicago has begun reshaping how students use AI tools. An August 28, 2026 editorial described a new policy in the university’s social sciences core that aims to return many classes to an “analog experience.” Under this policy, students generally must read, write and analyze without using generative AI, while AI-assisted grading is tightly restricted. The editorial framed the move as a way to preserve critical thinking skills and reduce dependence on unverified machine outputs. On the research side, University of Chicago computer scientist Ben Zhao has been exploring adversarial uses of AI, such as training neural networks to generate fake restaurant reviews or discover “backdoors” that allow hackers to fool facial recognition systems and autonomous vehicles. In a December 2024 episode of the university’s “Big Brains” podcast, Zhao argued that computer scientists must “carefully scrutinize” new AI techniques and applications to expose flaws and improve protections. His work underpins the idea that developers should seek out vulnerabilities before malicious actors exploit them. Policy conversations extend beyond campus walls. The Buffett Institute’s September 2026 report on the AI–cybersecurity industry letter shows companies urging federal action on standards and oversight for advanced models. Risk scholars who study extinction pathways call for prevention strategies across nuclear security, pandemics and environmental protection, arguing that anthropogenic threats—including AI‑enhanced ones—require ongoing mitigation. How should the public interpret the gap between doom narratives and current evidence? The Chicago experts’ core message to the public is to treat AI as a powerful, double-edged tool rather than an inevitable extinction engine. They advise paying attention to documented harms and credible data, while avoiding paralyzing fear based on speculative future scenarios that today’s models cannot reach. The available evidence and expert views suggest a few practical takeaways. Current AI systems are not close to artificial general intelligence capable of autonomous global destruction, according to Hoffmann and Linna, who say multiple breakthroughs are still needed. Most documented harms involve misuse: cybercrime, fraud, disinformation, bias in decision systems and potential labor-market disruptions. Job-loss data to date does not show an AI-driven “bloodbath,” although displacement in specific roles remains a concern. Extinction risk research identifies other threats—nuclear war, pandemics, environmental collapse—as more immediately quantifiable, with AI possibly acting as an accelerator rather than the root cause. Experts advocate slower, more controlled deployment of frontier models, stronger security standards, and institutional rules that preserve human judgment in high-stakes domains such as education, finance and security. In short, Chicago’s AI scholars are trying to recalibrate the public conversation: less apocalyptic speculation, more evidence-led focus on the concrete ways advanced software can help and harm society today.

Nic Reeve·
Harvard Adds AI Avatars to a $699 Founder Bootcamp
AI & Tech

Harvard Adds AI Avatars to a $699 Founder Bootcamp

Harvard Business School has put an artificial-intelligence twist on entrepreneurship training, rolling out a new eight-week startup bootcamp that pairs live instruction with AI-generated instructor avatars. The program, known as HBS Foundry, costs $699 and is designed to give aspiring founders more personalized feedback during pitch practice and simulated board meetings. According to reporting from TechCrunch, the course uses avatars built by AI video platform HeyGen to mimic instructors and respond during exercises such as practice pitches and boardroom scenarios. The weekly live sessions are still led by real teachers, but the AI avatars are intended to extend the feedback students receive between those classes. The idea reflects a broader push by business schools and online learning platforms to make startup education more scalable without losing the feel of individualized coaching. In this case, Harvard is trying to blend human-led teaching with digital replicas that can deliver critiques in a format similar to a live conversation. The bootcamp is part of Harvard Business School’s effort to reach founders beyond its traditional degree programs. HBS Foundry is aimed at entrepreneurs who want practical guidance on shaping and testing ideas, refining their pitches and preparing for investor-style questioning. By using AI avatars, the program attempts to offer more frequent and accessible feedback than a standard classroom model might allow. CryptoRank’s coverage highlighted the novelty of the setup, and the story quickly spread across tech and startup media because of the contrast between Harvard’s elite brand and the mass-market feel of a $699 online bootcamp. The price point is notably lower than the cost of many executive education offerings, which makes the course more accessible to early-stage founders and operators. The use of AI avatars also raises questions that are now common across education and corporate training: how well can synthetic instructors capture the nuance of a seasoned mentor, and where is the line between useful automation and imitation? In this program, the avatars are not replacing live faculty altogether, but they are taking on a role that traditionally depends on one-on-one human interaction. HeyGen, the company behind the avatars, has been positioning itself as a tool for AI-powered video creation and presentation workflows. In Harvard’s bootcamp, its technology is being used for a more specific purpose: simulating instructor feedback in a startup-training environment. That makes the course one of the more visible examples so far of generative AI moving from demo use cases into formal education. The broader significance lies in what Harvard is signaling about the future of teaching entrepreneurship. If AI avatars can reliably provide structured feedback on pitches, board meetings and founder communication, similar systems could be adopted by other schools, accelerators and corporate training programs. If they fall short, the experiment will still serve as a useful test of how far AI can go in roles that depend on judgment, tone and mentorship. For now, HBS Foundry stands out less as a replacement for professors than as a hybrid model that uses software to extend their reach. That combination of live instruction and AI-driven personalization is likely to draw attention from founders looking for practical training — and from educators watching how far the technology can be pushed.

Nic Reeve·