Cover Image for ED + AI #14: What Counts as Their Own Work?
Cover Image for ED + AI #14: What Counts as Their Own Work?
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ED + AI #14: What Counts as Their Own Work?

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The first big assignments are coming back. Underneath every AI rule is one question nobody has settled.

ED + AI is spending an evening on authorship: what students are asked to produce, how we judge it, and what happens when we get it wrong.


Assessment is where this gets real.

Every AI policy in every school is, underneath, a claim about authorship. What counts as a student's own thinking. What counts as help. Where the tool stops and the person starts.

That line was blurry before any of this, and most of us have been drawing it under time pressure, one assignment at a time.

October is when it stops being theoretical. Work is coming back. Somebody is going to look at a paragraph and feel unsure. Somebody is going to be accused and be innocent. Somebody is going to hand in something genuinely their own that a detector does not believe.

So let us think about it together before the next round.

Bring an assignment you are proud of. Bring one you are no longer sure about. Bring the rubric you rewrote. Bring the moment you had to make a judgment call about a student and are still turning over.


The questions on the table:

  • Where is the line between a tool and a ghostwriter, and can we describe it to a fourteen-year-old?

  • What does a good assignment look like when AI is simply assumed?

  • How do you assess thinking rather than output?

  • What do we owe a student we suspect, and what do we owe one we accused wrongly?

  • Who gets believed by default, and who does not?

  • What have students told you about how they actually use it, when nobody was grading them?

  • What is worth protecting in an assessment even when it costs time?

We will talk about this without pretending detection is solved or that the answer is to give up and let the machine write everything.


What to expect

  • Open conversation around real education and AI questions

  • Space to share tools, workflows, prompts, projects, and experiments

  • Honest talk about consent, equity, workload, assessment, creativity, and student agency

  • Small-group discussion so everyone actually gets to talk

  • A practical community vibe: more kitchen table than conference stage


Who ED + AI is

ED + AI is a monthly AI and education gathering hosted with big love by Ethọ́s Lab × BC + AI.

We are here to weave practical tools with ethical guardrails so classrooms, after-school programs, community labs, and learning spaces can adapt without losing the human core: relationships, curiosity, confidence, care, and agency.


Who belongs

Educators (K to 12 and post-secondary), students, parents and caregivers, youth-program leads, librarians, mentors, researchers, artists, designers, EdTech builders, and all curious neighbours welcome.

If you see learning as public infrastructure and teaching as a creative act, you are home.


Big love to Ethọ́s Lab

Ethọ́s Lab is a youth-powered innovation studio centring Black futures and community imagination. Their space, leadership, and care make ED + AI possible. Thank you for holding the centre and keeping the vibe welcoming and bold.


Who BC + AI is

BC + AI is a grassroots nonprofit network of educators, technologists, artists, researchers, founders, and community builders shaping a uniquely BC approach to AI rooted in accessibility, community, and ethical design.

We host meetups, special interest groups, office hours, and community projects for people who want AI development to stay local, useful, accountable, and human.


Schedule

6:30: Doors open 7:00: We start, right on time 8:00: Formal wrap, mingling and conversation 8:30: Doors close

Ring the doorbell at Ethọ́s Lab for entry.

Questions or want to get involved? anthonia@ethoslab.ca or kk@bc-ai.ca.

We look forward to learning and unlearning together.

Location
Ethọ́s Lab
177 E 3rd Ave, Vancouver, BC V5T 1C7, Canada
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BC + AI Events