Foundation/AI/FLEX/Projects/MachineLearningGames: Difference between revisions

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== Overview ==
== Overview ==
'''Project Lead:''' Chad Sansing
'''Project Lead:''' Becca Ricks


'''Area of Focus:''' Focusing on how discrimination, a lack of openness and  transparency, and a lack of responsibility all contribute to discimination and negatively impact digital inclusion.
'''Area of Focus:''' Machine Decision Making (Impact Goal)


'''Knowledge Level Required:''' None / Any
'''Knowledge Level Required:''' Intermediate


'''This project is actively seeking contributors you can sign up to participate here.'''
'''This project is actively seeking contributors you can sign up to participate here.'''
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== Project Information ==
== Project Information ==
==== Project Description: ====
==== Project Description: ====
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 (https://robots.management/), indie table-top role-playing games (TTRPGs), storytelling, matching games, and more.
MoFo has an opportunity to educate itself and learn together about this year's impact goal, machine decision-making (AI). 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. The idea is that anyone from MoFo can self-organize into small discussion groups to talk about each topic.


==== Expected Outcomes: ====
==== Expected Outcomes ====
I want to learn how each part of machine learning functions & connects to the others from trainers & data sets, to general adversarial networks & generators & discriminators, to the products that use the machine learning & the people it affects.
The hope is that MoFo as an organization is able to develop a more in-depth knowledge about the challenges posed by AI that goes reacting to the news cycle. We should all be able to speak and work confidently around the impact goal.  


==== Help Required: ====
==== Help Required ====
Everyone should feel welcome to join, learn, & design games with us, & to help us prototype & publish games to share at All-Hands, MozFest, & beyond via CC licensing & .pdf distribution. Gamers, artists, storytellers, layout designers, editors et al.
Based on the challenge areas identified in the literature review, the hope is that contributors will volunteer to tackle a topic and develop out a suggested curriculum on that topic. These are suggestions–groups can diverge from the topics, too.


==== Required Time Commitments ====
==== Required Time Commitments ====
Gather contributors --> begin cadence of meetings, mini-design sprints --> prototype --> share at All-Hands --> submit to MozFest --> refine for MozFest --> play at MozFest --> publish betas before the end of 2019. The Project Lead will spend 2 hours working on the project and contributors would need to allow for 2 hours per week to fully get involved.
The project will take place over 1-2 months. The Project Lead will spend 1 hour working on the project per week and contributors would need to allow for 1 hour per week to fully get involved.


== Project Updates ==
== Project Updates ==
More to come...
More to come...

Revision as of 16:20, 27 March 2019

Machine Learning Games

MoFo FLEX 2019 - Project Proposal

Overview

Project Lead: Becca Ricks

Area of Focus: Machine Decision Making (Impact Goal)

Knowledge Level Required: Intermediate

This project is actively seeking contributors you can sign up to participate here.

Project Information

Project Description:

MoFo has an opportunity to educate itself and learn together about this year's impact goal, machine decision-making (AI). 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. The idea is that anyone from MoFo can self-organize into small discussion groups to talk about each topic.

Expected Outcomes

The hope is that MoFo as an organization is able to develop a more in-depth knowledge about the challenges posed by AI that goes reacting to the news cycle. We should all be able to speak and work confidently around the impact goal.

Help Required

Based on the challenge areas identified in the literature review, the hope is that contributors will volunteer to tackle a topic and develop out a suggested curriculum on that topic. These are suggestions–groups can diverge from the topics, too.

Required Time Commitments

The project will take place over 1-2 months. The Project Lead will spend 1 hour working on the project per week and contributors would need to allow for 1 hour per week to fully get involved.

Project Updates

More to come...