Universities, schools, and navigating AI -
MIT committee report urges rethinking higher education amid artificial intelligence
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USC and UCLA launch new artificial intelligence degree programs
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MIT committee reports AI completes nearly all undergraduate written assignments
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University of Chicago prohibits artificial intelligence and devices in core courses
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USC and UCLA launch new artificial intelligence degree programs
USC and UCLA have launched two distinct new undergraduate programs to meet the soaring student and job market demands for artificial intelligence expertise. While both institutions are implementing these programs for the Fall 2026 academic year, they are taking fundamentally different approaches to AI education—USC focuses on technical model-building while UCLA emphasizes the intersection of AI with the humanities. [1]
The Two Different Approaches
| University | New Degree / Department | Primary Program Focus | Key Target Fields |
|---|---|---|---|
| USC | Bachelor of Science in Artificial Intelligence (BSAI) | Technical model-building, algorithmic architecture, and system design. | Robotics, drug discovery, agriculture, and AI engineering. |
| UCLA | Department of Digital Humanities (Bachelor's Degree) | Integrating AI and digital tools into social sciences and humanistic study. | Sociology, history, archaeology, and studies of race and gender. |
USC: Building the Next Generation of AI Engineers
- Curriculum Focus: Offered jointly by the USC Viterbi School of Engineering and the newly renamed USC Stevens School of Computing and Artificial Intelligence, this program trains students to build, design, and deploy AI technology from the ground up. [1, 2, 3]
- Interdisciplinary Tracks: The degree spans across computer science, electrical engineering, and systems engineering. [1]
- Cohort Size: The program is launching with a selective inaugural class of 30 undergraduate students. [1]
- Institutional Support: The launch aligns with a massive $200 million donation to USC's AI initiative and a recent campus-wide partnership providing students full access to OpenAI's GPT-5. [1, 2]
UCLA: Pioneering AI in the Humanities
- Curriculum Focus: Rather than focusing on raw code, UCLA has established the nation's first freestanding Department of Digital Humanities. [1]
- Societal Application: Students learn to use advanced AI systems, data analytics, and digital tools to explore cultural history, languages, literature, and art. [1]
- Critical Frameworks: The program emphasizes evaluating how AI influences society, with heavy coursework dedicated to identifying biases in algorithms. [1]
Ethics Across the Board
A unifying feature of both programs is a mandatory focus on ethics. Higher education institutions are grappling with fears of plagiarism and the erosion of critical thinking skills, leading both USC and UCLA to weave responsible development and algorithmic accountability directly into their graduation requirements. [1]
Would you like more details on the specific course requirements for the USC AI major, or are you interested in learning about similar AI degree tracks at other California universities like Stanford and UC San Diego?
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MIT committee reports AI completes nearly all undergraduate written assignments
In August 2026, MIT’s Ad Hoc Committee on AI Use released a groundbreaking report warning that artificial intelligence can now credibly complete almost any written assignment in its undergraduate curriculum. Co-chaired by professors Eric Klopfer and Samuel Madden, the report found that AI easily handles everything from traditional essays to complex math proofs and coding assignments. [1, 2, 3]
MIT President Sally Kornbluth called the findings a "watershed for MIT—and for all of higher education," prompting an immediate, sweeping re-evaluation of how universities measure student learning. [1, 2]
Key Findings & Recommendations
The report outlines massive structural and cultural shifts required to maintain academic integrity and relevance: [1, 2]
- Move Away from AI Detectors: The committee explicitly discouraged relying on AI-detection software. They noted these tools frequently trigger false positives, particularly for neurodivergent students and non-native English speakers. [1]
- Overhaul Course Assessments: The university is urged to pivot toward alternative testing methods that AI cannot replicate. Recommended shifts include oral exams, hands-on portfolios, and in-person conversations where students must defend work done outside the classroom. [1, 2]
- Mandate Class-by-Class AI Policies: Rather than a blanket university ban, every single course must implement a clear policy. Syllabi must state exactly when AI is mandatory, allowed for critique, or entirely prohibited (such as requiring raw first drafts or basic algorithm coding without help). [1, 2]
- Accelerate Curriculum Approval: Current university governance requires a multi-committee, year-long review process to change a course. The report stresses that departments must be allowed to bypass this to make rapid curriculum alterations on a regular basis, or MIT risks being left behind. [1]
- Focus on the Physical Campus: Ironically, the surge in digital automation means a renewed focus on face-to-face community. The committee requested more physical campus spaces to foster human study groups, office hours, and collaborative research. [1, 2]
Examples of the "AI-Aware" Classroom
Instead of avoiding AI, MIT’s Teaching and Learning Lab is already designing ways to embed the technology directly into lessons so it cannot be used as a shortcut: [1]
- Language Courses: Students create a manual translation, pull an AI version, and write a critical analysis comparing the structural choices. [1]
- Data Visualization: Assignments challenge students to generate a project using AI and another using manual instructor guidance, explicitly revealing the blind spots and errors where the model fails. [1]
- Lab Science: AI can handle the post-experiment data analysis, but students must physically conduct the experiments and verbally defend their interpretations to professors. [1]
If you would like to explore this topic further, let me know if you want to look into how other universities are adapting, the specifics of MIT's new grading policies, or the technical benchmarks used to evaluate AI's performance on college coursework
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University of Chicago prohibits artificial intelligence and devices in core courses
The University of Chicago has banned laptops, smartphones, tablets, wearable AI devices, and artificial intelligence tools from core introductory courses for the 2026–2027 academic year. This new "analog" policy is explicitly designed to cultivate fundamental human critical thinking skills and independent judgment before students learn to collaborate with machines. [1, 2, 3, 4]
Affected Core Curriculums
The policy targets foundational introductory sequences where students build core academic habits:
- Undergraduate Social Sciences (SOSC) Core: Students must read assignments on physical paper and complete all work without AI assistance. Classrooms are entirely "device-free". [1]
- Law School First-Year (1L) Core: Laptops, phones, and tablets are barred from all mandatory first-year classes. Furthermore, exams will return to a proctored, offline format. [1, 2, 3, 4]
Key Rules of the Ban
- Device-Free Classrooms: Cell phones, tablets, laptops, and smart wearables are completely restricted.
- No Digital Textbooks: Readings must be completed on paper to foster deeper focus.
- No AI Assistance: Assignments must be researched and drafted entirely independently.
- No Lecture Recordings: Audio or video recording of classroom discussions is prohibited.
- Enforced Attendance: Students must participate in person to protect the face-to-face Socratic dialogue. [1, 2, 3]
Allowed Exceptions
The university has outlined narrow exceptions to maintain operational and inclusive standards:
- Academic Accommodations: Approved technological aids remain allowed for students with documented disabilities.
- Designated Scribes: Instructors can assign specific students to use a device for collaborative class note-taking.
- In-Class Polling: Devices can be briefly authorized for specific interactive tech exercises. [1, 2]
The Strategy Behind the Change
University leaders explain that a policy merely dictating "ethical AI use" is no longer enforceable because generative tools are completely embedded in standard digital workflows. Rather than avoiding AI entirely, the university's overarching strategy—headlined by the law school as "Rethinking Legal Education in the AI Era"—is to teach students how to think with, without, and about AI. By mandating device-free core spaces, educators aim to eliminate screen distractions and combat the "de-skilling" effects of outsourcing critical analysis to software. [1, 2, 3, 4]
Would you like to explore how other universities are responding to AI, or see details on UChicago's advanced AI electives?
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MIT committee report urges rethinking higher education amid artificial intelligence
MIT Says AI Is Forcing A Rethink Of College Itself - Forbes
MIT, a leader in AI, is urging a fundamental re-evaluation of higher education in response to generative AI, moving beyond simple cheating debates. Its report recommends redesigned assessments, emphas
The MIT Ad Hoc Committee on AI Use in Teaching, Learning, and Research Training released a comprehensive report warning that artificial intelligence can now credibly complete almost any written undergraduate assignment, serving as a critical "watershed moment" for the entire higher education landscape. [1, 2, 3, 4, 5]
The report, detailed on the MIT news site and covered by The Washington Post, warns that relying on AI creates an "illusion of learning" by letting students bypass critical problem-solving steps. In response, MIT President Sally Kornbluth and the committee have called for deep, structural changes to how universities teach, test, and adapt. [1, 2, 3, 4]
Core Recommendations & Changes
- Overhaul student assessments: Replace standard take-home problem sets and papers with oral exams, live demonstrations, and project portfolios. [1, 2]
- Mandate clear syllabus guidelines: Require every class to explicitly state if students must use AI, may use it with restrictions, or must entirely avoid it for specific tasks. [1]
- Ban AI detection software: Discourage the use of "AI checkers" because they frequently trigger false positives for non-native English speakers and neurodivergent students. [1, 2]
- Enforce mutual disclosure: Require both students and instructors to fully disclose how and when they utilize AI in coursework and research. [1]
- Fast-track curriculum changes: Redesign administrative workflows so departments can rapidly alter classes to adapt to AI advances without multi-committee, year-long delays. [1, 2]
- Prioritize the "human" campus experience: Create more physical spaces for face-to-face engagement, interactive peer learning, and hands-on laboratory work. [1, 2]
- Monitor broader impacts: Track the environmental costs and resource equity issues of paid AI tools, ensuring that access disparities do not disadvantage students. [1, 2]
If you are interested, I can provide more details on how specific MIT courses are already integrating AI, outline the risks the report found regarding AI hallucinations in graduate research, or discuss how other universities are responding. Let me know what you would like to explore next
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