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Global South AI Safety Hackathon: Harare

lumaHosted on Luma

Fetched about 5 hours ago

Friday, June 19, 2026

to Sunday, June 21, 2026

•

2 days long

Artificial IntelligenceData ScienceSocial Impact

Event Type

in person

51

Participants

$1,000

Prize Pool

4

Est. Projects

Join the Harare hub for the Apart Global South AIS Hackathon! Develop context-appropriate solutions to policy and evaluations for the African AI risk response, focusing on policy or technical interventions against the AI harms most likely to manifest in African deployment contexts. Find collaborators to work on real research ideas. Get feedback from experts. Stand a chance to win $1000. ​Schedule: Friday 18:00 - Kick-off - Meet awesome, smart collaborators selected from our network. Saturday & Sunday 10:00-18:00 - Work on your project in teams or on your own; lunch is on us. Project submission deadline TBC. ​Project Ideas Here are some example projects you could work on. You can also come up with your own ideas - any project that addresses risks from AI in Africa is fair game! If you want to participate in the in-person event in Harare, you will need to register for this Luma event. You can participate remotely by registering on the Apart website.

Judge Accessibility

Organizer email available25/25
Student-run event15/15
Actively looking for judges25/25
Small event (120 participants)10/10
No corporate sponsors10/10
New or emerging organizer10/10
Public registration available5/5
Online format (judge from anywhere)10/10

Top signals

Organizer email available
Student-run event
Actively looking for judges

Organizers

Alex Johnson

alex@example.org

Jamie Rivera

jamie@example.org

Sam Chen

sam@example.org

Estimated Audience

Mostly Students
ExperienceStudent
OccupationStudents
Beginner Friendly
Women in Tech

Technical Focus

AI95%
Web80%
Mobile25%

Industries

Healthcare
Education
Climate

Technologies

Python
React
OpenAI

Why this estimate

  • • Hosted by a university
  • • Open to students
  • • MLH member event

Estimate inferred from event metadata, not actual attendee data.

Quality Score

Quality Score

72/100
High confidence
Organiser16/20
Event Maturity14/20
Sponsors18/25
Participants12/20
Operations12/15

Why this score

Strong organiser track record
Returning event
Well-sponsored

Missing data

Prize details
Code of conduct