My little sister's use of ChatGPT for homework is heartbreaking

Homework, flipped classrooms, and in‑class work

• Many argue that traditional homework is now pointless if LLMs can do it; suggest moving most or all graded work into the classroom on paper or locked devices.
• Flipped classroom ideas (lectures at home, practice in class) are debated: some find them effective and more equitable; others say video engagement is poor and many students won’t watch.
• Several expect a long‑term shift toward heavy weighting of in‑class exams, essays, and oral work, with homework mainly for practice, not grading.

LLMs, cheating, and institutional response

• Widespread AI use for homework is seen as a continuation of longstanding cheating (copying from classmates, WhatsApp, Encarta, parents).
• Some say if “everyone cheats” it becomes the school/university’s problem; institutions have strong incentives not to confront it and “you can’t fail them all.”
• Others see this as an existential threat to assessment: if AI output is indistinguishable from student work, the assignment design is broken.

Parents, home environment, and childhood

• A recurring theme: where are the parents? Many blame disengaged or overwhelmed caregivers who outsource both learning and screen use.
• Counterpoint: many parents lack time, education, or tech understanding to supervise AI use; dual‑income and stressed households are common.
• There is concern about very young kids with unsupervised internet/phone access and age‑inappropriate content; some see this as a broader tech/attention crisis.

Calculators, past panics, and what counts as “learning”

• Frequent comparison to calculators, slide rules, and Google: tools once seen as “cheating” became standard.
• Dissenters argue calculators offload arithmetic, but LLMs offload understanding, composition, and problem setup, not just mechanics.
• Debate over whether education should focus less on rote skills and more on analysis, problem‑solving, and tool‑use literacy.

AI as tool vs crutch

• Many distinguish “using AI to check, explain, or critique your own work” (seen as beneficial) from “having AI do the work to copy verbatim” (seen as self‑sabotage).
• Some parents/teachers already use LLMs as tutors, graders, or feedback givers, sometimes via prompts that explicitly forbid direct answers.
• Others worry LLMs encourage intellectual laziness, erode basic skills, and train students to trust authoritative‑sounding nonsense.

Broader societal and equity concerns

• Thread notes existing functional illiteracy rates and fears LLMs could mask or worsen them, though some hope AI and screen readers might also help.
• Several argue the real issue is structural: grades as competition for scarce slots, social mobility tied to credentials, and homework used to push responsibility onto families.
• Some see AI as another disruptive “force multiplier” that will reward two groups: those who wield it aggressively (“the quick”) and those with deep understanding to direct it (“the deep”).