Anita Sarma - Keynote: Effective Mentoring Strategies for an Inclusive Community | SciPy 2024

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Learn effective mentoring strategies for open source projects from Anita Sarma. Discover how to create inclusive communities, overcome barriers, and leverage AI tools to support contributors.

Key takeaways
  • Mentoring is essential for open source sustainability but faces key challenges around time constraints, communication barriers, and unacknowledged effort

  • Successful mentoring strategies include:

    • Setting clear expectations upfront
    • Using multiple communication channels (async, video, text)
    • Making documentation accessible and task-focused
    • Creating bite-sized, well-defined starter tasks
    • Allowing mentees to choose their tasks
    • Building psychological safety and peer support groups
  • Demographics and identity affect feeling of welcomeness:

    • 54% of non-binary/third gender contributors reported challenges
    • 34% of women and 33% of people with disabilities faced barriers
    • Cultural differences and language barriers create additional hurdles
  • Code reviews are valuable teaching opportunities but need:

    • Clear feedback with learning goals
    • Patience with newcomers
    • Recognition of time zone and language differences
    • Identification of appropriate task complexity
  • Formal vs informal mentoring:

    • Formal programs provide structure but may not create best connections
    • Informal mentoring often more effective for career growth
    • “Implicit mentoring” through day-to-day interactions valuable
    • Peer support groups critical for retention
  • Project sustainability requires:

    • Acknowledging and rewarding mentoring efforts
    • Creating welcoming environments for diverse contributors
    • Having enforceable codes of conduct
    • Supporting multiple paths to contribution
    • Planning for leadership succession
  • AI tools can potentially help with:

    • Documentation maintenance
    • Task complexity assessment
    • Communication improvements
    • But need careful consideration of fairness and bias