Key activities right now that map to Mozilla's AI work include:
Interview series with experts
We’re launching an additional series of interviews with global experts on machine decision making to strengthen our understanding in key areas. In particular, we’ll be reaching out to experts who work outside the NA/EU context to understand how AI is taking shape in Africa, South America and Asia so we can better understand how we might support work in those regions; those who are working on gender equity and inclusion in this space; as well as technical experts who can help us understand the source and opportunities to move towards the goal on a technological level.
We’ll draw insights from these interviews into this wiki, as well ask interviewees for recommendations of source material for our literature review (see below). If interested, check out the interview questions and list of interviewees. Feel free to suggest interviewees that have expertise in the areas outlined above by adding to the interview spreadsheet.
The timeframe for this work is January-April.
Many organizations and individuals have researched and published recommendations regarding AI and machine decision making. Our literature review seeks to uncover those and identify themes, as well as gaps in the current recommendations that may warrant further research by us.
The key questions the literature review seeks to answer are:
- What are the top ten challenges (and proposed solutions, with a focus on policy interventions, product standards and consumer behavior) that machine decision making poses to internet health (privacy & security, decentralization, web literacy, digital inclusion & openness)?
- What are the different terms being used to describe machine decision making and how are they being used?
- What are current legislative frameworks that are being proposed on this topic globally and what has the reception to those frameworks been?
- What ethical guidelines already exist in this area and what has the reception to those ideas been?
See the key documents section for access to the literature review overview and current source material.
The timeframe for this work is January-March.
Current & Planned 2019 Work on Machine Decision Making
This doc provides a platform for us to share and understand in greater depth how we’re already leveraging existing programs towards the impact goal, as well as how we’re stretching our programs and thinking into 2019, so we can begin talking about this work with the board, partners and the press. Feel free to check out this document.
The timeframe for this work is Jan-February.
Theory of Change
This work is focused on using the Theory of Change tool we’ve already developed for internet health to define a set of more specific, measurable long-term and short-term outcomes for our work on ‘better machine decision making.’
This work will be drawn from the insights and information generated from the interviews, literature review, and current work overview, as well as additional research if needed.
The process will include opportunities for staff learning and contribution. We are still developing the detailed Theory of Change development plan and will update staff, which will include staff learning and contribution components.
The goal is for the project to be completed by June and support H2 and 2020 action planning at All Hands. The timeframe for this work is Feb-June.