MoFo Free-form Learning & EXploration (FLEX) about better machine decision making (AI)
MoFo FLEX is an org-wide learning journey. For this first iteration of MoFo FLEX, we’re focused on our better machine decision making (AI) theme.
- We’ve heard loud & clear that MoFo staff want (and need) to increase our own knowledge about better machine decision making (AI) to work on it effectively. Investment in ourselves is investment in this theme.
- The goal for MoFo FLEX is for staff and fellows to increase our understanding about this theme, in order to boost our confidence and ability to:
- Contribute to guiding the strategic direction of MoFo’s work in this space
- Talk about this part of MoFo’s work with external partners and stakeholders
- This is also an experiment to see if this approach effectively helps MoFos learn together.
- How it works:
- All staff and fellows are invited to lead a learning project or contribute to a learning project.
- In this iteration, a learning project is any initiative to help you (and possibly others) learn about better machine decision making (AI).
- You can pursue a learning project solo or with a group of any size. Projects can stretch all the way from now until June, be as short as an afternoon, or anywhere in between. Prototypes and experiments welcome - this is intentionally broad!
- Staff and fellows are encouraged to use working hours to contribute to MoFo FLEX projects. You’ll speak with your manager and agree on the amount of time you’ll be able to contribute together.
- 1 Key Dates
- 2 Where do I start?
- 3 I have an idea for a learning project
- 4 I want to contribute to a learning project
- 5 Active FLEX Projects
- 6 Who to contact
- Wednesday March 20 - MoFo FLEX launches! Call for learning project proposals opens: lead a learning project
- March 28 @ 9am PT | 12pm ET | 4 pm GMT | 5pm CET - Impact Goal office hours, feat. MoFo FLEX
- Friday April 5 - Call for learning project proposals closes
- Monday April 8 - Call for for contributors officially opens: contribute to a learning project
- Friday April 19 - All FLEX learning projects are up and running! We suggest contributors aim to join a project by this point, though you can still joinb after this date. Updates will be shared regularly here on the wiki and in Slack.
- June 17-21 - All Hands - FLEX projects may show up in skill shares and other ways!
- post-All Hands - we'll regroup and assess how the first iteration of FLEX went, and decide if/how to continue
Where do I start?
A great place to start is to consider what you want to learn about, and how you like to learn.
What do you want to learn about?
Anything related to the better machine decision making (AI) theme is fair game, though you're encouraged to tie your learning to ideas in the AI issue brief.
- Some projects may contribute more directly to MoFo-wide work, but this is not required.
- The primary goal is for staff & fellows to learn together, and to feel more ready to contribute to MoFo’s work in this space.
Topics you could explore include:
- What products use AI and how? Where is AI in your home? In your city?
- How is AI built?
- How does the public currently perceive AI?
- Who are key players in AI? (from technologists to activists to lawmakers)
- How does AI become biased? What impacts is this having?
- How are AI recommendation engines spreading misinformation? What are solutions?
- Who is responsible for making ‘ethical’ AI? What is ‘ethical’ anyway?
… and much more! Choose something you’re genuinely interested in understanding better. Check out the AI issue brief for more guidance and inspiration.
How do you want to learn?
- Start (or join) a book club
- Host an in-person ‘study group’ workshop (like the one Michelle and Jon hosted in Berlin)
- Experiment with building your own AI system (maybe take a class on Udemy, solo or with others)
- Write reflective blog posts about questions and ideas you’re exploring
- [insert your idea here]
Once you have an idea, propose it as a MoFo FLEX project!
Proposals don’t need to be fully baked -- general ideas are welcome, and we can help you work through the specifics.
- For example, if you want to host a book club but don’t know what you want to read yet (or want to get a group together first) -- send in the idea, and we can work out the details after. Learn more about how to propose a project.
I have an idea for a learning project
If you have an idea you want to pursue, you're ready to propose it as a MoFo FLEX project!
Here's what to do:
- Talk to your manager about your idea, and how much time you think you’ll need to make it happen. When you’ve agreed on the time commitment, you’re ready to --
- Submit your idea HERE by Friday April 5
- When you submit a proposal, it will go to both your manager and the MoFo FLEX team. We expect most proposals to be accepted!
- The proposal process is intended to help connect people who are interested in similar things, give the whole org a view of the learning that is happening, and to support you in working with you manager in making time during your workday. The FLEX team will have a look at your proposal, let you know if we have any questions or ideas, and confirm that you and your manager have agreed on your time commitment.
- Your project will then be added here, on the wiki, and officially be ready for contributors to join.
- Proposals don’t need to be fully baked.
- You can team up with others to co-lead projects - use the #ai-abcs Slack channel to share ideas and recruit partners.
- You can pursue a learning project solo or with a group of any size.
- Projects can stretch all the way from now until June, be as short as an afternoon, or anywhere in between.
- Prototypes and experiments welcome!
- If you don’t fully complete the project, it’s okay -- it’s your learning that counts, and there will be supports to help capture both what you learned and how we might improve these opportunities in the future.
I want to contribute to a learning project
Here's how to get involved:
- Browse projects here to find one you'd like to join. Feel free to reach out to the project leads with ideas or questions!
- Talk to your manager about the project you'd like to contribute to, and how much time you think you’d like to commit. When you’ve agreed on the time commitment, you’re ready to --
- Starting on April 8, you can join a project HERE. When you sign up as a contributor, the project lead, your manager and the MoFo FLEX team will be notified. The project lead will reach out about how to start contributing, and the MoFo FLEX team will add you as a contributor on the wiki.
You can also keep up with all learning projects through the better machine decision making (AI) wiki, #ai-abcs Slack channel, and monthly staff calls.
Active FLEX Projects
Below is the current list of projects that are taking place as part of the MoFo FLEX program. Each page shows if the project is currently looking for contirbutors.
The opportunity for staff to audit the course 'AI for Everyone' along side Sarah Watson.
Take a look at how AI/ML is part of "social listening" - complete research and/or a lit review of platforms and practices that are used to perform social listening and share/discuss the findings with others.
A group of Foundation staff will read the nonfiction book "Weapons of Math Destruction," at the pace of two chapters / week. At the end of each week, staff will add their thoughts to a Google Doc, where others can weigh in / start conversations. After finishing the book, the group will gather for a 40-minute discussion on Vidyo.
Creating a short, illustrated zines that introduces AI concepts and topics.
Would you like to host an in-person study group (one-off or recurring) to learn more about AI/ML with friends and colleagues? This is a group to support hosts and share tips & tricks for organizing study groups.
The project idea is to develop a set of curricula (suggested readings & questions) based on the challenges raised in the literature review–data privacy concerns, bias in training data, algorithms & behaviors, lack of accountability mechanisms, etc.
We are going to make low-fi and no-fi social, collaborative games that demonstrate how biased inputs lead machine learning products to discriminate against under-represented and wrongly-represented people. Inspirations include Werewolf, Inhuman Conditions, indie table-top role-playing games (TTRPGs), storytelling, matching games, and more.
Need to come up with an OKR? Use the MoFo OKR generator! We'll use MoFo's past and current OKRs as the training data. We may have to supplement with text from reports / meetings / etc.
Who to contact
Reach out to Zannah, Marc, or Sam