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|1. Thought leadership
|1.  
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|Thought leadership
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|Short term outcomes
|Short term outcomes
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|2020 objective
|2020 objective
| Test out our theory of change in ways that both give momentum to other orgs taking concrete action on trustworthy AI and establish Mozilla as a credible thought leader.  
| Test out our theory of change in ways that both give momentum to other orgs taking concrete action on trustworthy AI and establish Mozilla as a credible thought leader.  
|+
|2020 key results
|Publish a white paper and landscape analysis that elaborate our theory of change and show who is working on key elements (H1)
X# people and organizations map their work against the landscape analysis and offer feedback on theory of change
25 collaborations with partners working on concrete projects that align with short term outcomes in the theory of change
|+
|Activities
| White paper analysis 0.9 produced in collaboration with MoCo, disseminated to key stakeholders and feedback gathered through individual and group sessions
Draft landscape analysis of trustworthy AI field (host org landscape analysis feeds in)
Develop process to identify, monitor and nurture collaborations
Pursue Partnership on AI project participation with staff & fellows
Connect fellows and staff to IEEE projects
Pursue collaborations to translate AI principles into guidelines for consumer orgs
Support implementation of Trustworthy AI in digital cities coalition, including Amsterdam
Partner with existing & alumni fellows to facilitate mapping inputs and feedback
Develop effective tool to display and provide feedback on Theory of Change
Develop conference strategy and other comms to support feedback on ToC
Translate landscape into analysis for collateral to share with current & prospective donors
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Data stewardship
|+
 
|2.
Short term outcomes
|Data stewardship
|+
|Short term outcomes
(1 - 3 years)
(1 - 3 years)
 
| More foundational trustworthy AI technologies emerge as building blocks for developers (e.g. data trusts, edge data, data commons).
 
|+
 
|Narrative
More foundational trustworthy AI technologies emerge as building blocks for developers (e.g. data trusts, edge data, data commons).
|In the era of machine learning, who controls our data and what they do with is a big deal. It determines not only what is possible with AI but also who knows what, who can innovate, who makes money, what decisions get made. Right now, the biggest pools of data sit with the tech platforms and other companies that underpin our digital lives. What if this wasn’t the case? What if large pools of data were stewarded in a way that would benefit and protect the people who created the data in the first place? Or that would collectively benefit the general public? Emerging ideas like data trusts, data cooperatives and data commons aim to do exactly this: to shift the power dynamic around data.  
 
Narrative
 
In the era of machine learning, who controls our data and what they do with is a big deal. It determines not only what is possible with AI but also who knows what, who can innovate, who makes money, what decisions get made. Right now, the biggest pools of data sit with the tech platforms and other companies that underpin our digital lives. What if this wasn’t the case? What if large pools of data were stewarded in a way that would benefit and protect the people who created the data in the first place? Or that would collectively benefit the general public? Emerging ideas like data trusts, data cooperatives and data commons aim to do exactly this: to shift the power dynamic around data.  


In 2020, Mozilla and its partners will explore whether data stewardship models like these have the potential to accelerate the growth of trustworthy AI, offering everyone from developers to policy makers a new set of tools to use in their work. In the immediate term, Mozilla’s role in this work will be to a) provide an overview of trends and opportunities and b) to connect and fund people working on innovations in this space. These innovations may include laws, contracts, software, services and business models that put data stewardship concepts into concrete action. Over the longer term, Mozilla could enter into the business of being a data steward itself, helping members of the public collectively manage their relationships with platforms and others who use their data.
In 2020, Mozilla and its partners will explore whether data stewardship models like these have the potential to accelerate the growth of trustworthy AI, offering everyone from developers to policy makers a new set of tools to use in their work. In the immediate term, Mozilla’s role in this work will be to a) provide an overview of trends and opportunities and b) to connect and fund people working on innovations in this space. These innovations may include laws, contracts, software, services and business models that put data stewardship concepts into concrete action. Over the longer term, Mozilla could enter into the business of being a data steward itself, helping members of the public collectively manage their relationships with platforms and others who use their data.
|+
|2020 objective
| Increase the number of data stewardship innovations that can accelerate the growth of trustworthy AI.
|+
|}


 
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2020
|+
objective
|3.  
Increase the number of data stewardship innovations that can accelerate the growth of trustworthy AI.
|Consumer Power
 
|+
2020
|Short term outcomes
key results
 
$3 million raised to support bold, multi-year, cross movement initiatives on data stewardship as an indicator of growing philanthropic support in this area.
10 awards or fellowships for prototypes or other concrete exploration re: data stewardship.
50% increased interest in data stewardship projects from developers & investors (survey).
 
 
 
Activities
 
 
 
Data trust lab + pilots: establish group with expertise in data trusts, as well as a fund to directly support data trust pilot projects.
Raise $1M by launching a titan donor ($250K+) campaign leveraging data stewardship
Pilot a model of hosting research fellows to dive deep on particular issues (i.e. data trusts)
Bring in overall product management and technical expertise
Support 4 current fellows working on projects related to new models for data stewardship
Launch a new fellowship program with 2 fellows to build voice libraries to grow the development of local innovation ecosystems for voice-enabled products and technologies
Public campaigns demonstrating concerns re: data ecosystem and promoting change
Support the design, implementation and analysis of surveys targeted to developers and investors to gather insight on appetite for data stewardship innovations.
 
Consumer Power
 
Short term outcomes
(1 - 3 years)
(1 - 3 years)
| Citizens are increasingly willing and able to pressure and hold companies accountable for the trustworthiness of their AI.
|+
|Narrative
|As AI-enabled technology becomes increasingly pervasive, we have a critical window in which to educate and more deeply engage people to advocate for trustworthy AI. In their role as consumers, people can illustrate the demand for trustworthy AI and its economic potential, accelerating action by developers, investors and policymakers. Younger adults (18-35 yrs) have disproportionate power to influence company behavior given their current and projected purchasing power. Mozilla’s current audience (given our existing measures) is predominantly older and we need to diversify our audience as we expand our reach. 


In 2020, we’ll increase awareness of trustworthy AI among key consumer audiences and then mobilize this cohort into deeper engagement on the issue. We’ll use pivotal moments (elections, holidays, etc.) among other tactics to show how AI impacts people and direct those who seek change a ‘hub’ for information, action and connection around ‘trustworthy AI’. We’ll focus our consumer mobilization on companies that produce AI-enabled consumer technologies widely available in the US/EU, including recommendation engines, targeting advertising and voice assistants. To deepen engagement, we’ll recruit people to gather evidence with us about the role and influence of algorithms.
|+
|2020 objective
| Mobilize an influential consumer audience using pivotal moments to pressure companies to make ‘consumer AI’ more trustworthy.
|+
|}


 
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Citizens are increasingly willing and able to pressure and hold companies accountable for the trustworthiness of their AI.
|+
 
|4.  
Narrative
|Movement building
 
|+
As AI-enabled technology becomes increasingly pervasive, we have a critical window in which to educate and more deeply engage people to advocate for trustworthy AI. In their role as consumers, people can illustrate the demand for trustworthy AI and its economic potential, accelerating action by developers, investors and policymakers. Younger adults (18-35 yrs) have disproportionate power to influence company behavior given their current and projected purchasing power. Mozilla’s current audience (given our existing measures) is predominantly older and we need to diversify our audience as we expand our reach. 
|Short term outcomes
 
In 2020, we’ll increase awareness of trustworthy AI among key consumer audiences and then mobilize this cohort into deeper engagement on the issue. We’ll use pivotal moments (elections, holidays, etc.) among other tactics to show how AI impacts people and direct those who seek change a ‘hub’ for information, action and connection around ‘trustworthy AI’. We’ll focus our consumer mobilization on companies that produce AI-enabled consumer technologies widely available in the US/EU, including recommendation engines, targeting advertising and voice assistants. To deepen engagement, we’ll recruit people to gather evidence with us about the role and influence of algorithms.
 
 
2020
objective
Mobilize an influential consumer audience using pivotal moments to pressure companies to make ‘consumer AI’ more trustworthy.
 
2020
key results
 
X# traffic to ‘trustworthy AI’ content on Mozilla channels (website, social media, YouTube, etc.).
X# new subscribers drawn from sources (partnerships, contextual advertising, etc.) oriented towards people ages 18-35.
25k people share information with us (stories, browsing data, etc.) in order to gather evidence about how AI currently works and what changes are needed
 
 
 
Activities
 
 
 
Commission computation art/creative media on trustworthy AI
Produce topical Privacy Not Included on voice-enabled technology
Apply trustworthy AI principles in voice-enabled consumer technology
Develop a “custom skill” for Alexa and Google Home that provides more detailed and accurate information from the company’s privacy policies
Deep dive on voice technology lifecycle and data (long form article or microsite)
Develop strategy across teams for 18-35 yo demographic
Build a series of browser extensions which collect data from users to build an evidence base of untrustworthy AI patterns on social media sites.
Convene working groups among fellows and host orgs Pilot/explore the utility of qualitative analysis on evidence gathered via campaigns, for deeper understanding of trends, learnings and impact (ongoing)
 
Movement building
 
Short term outcomes
(1 - 3 years)
(1 - 3 years)
 
| A growing number of civil society actors are promoting trustworthy AI as a key part of their work.
 
|+
 
|Narrative
A growing number of civil society actors are promoting trustworthy AI as a key part of their work.
|The internet health movement cannot succeed if it is siloed. Internet health and the likelihood of trustworthy AI increases as the need for both is prioritized by greater numbers of people. Internet growth rates in the global south measure over 10k% over the last decade. In Europe and North America where growth may now be slower, penetration rates hover around 90%. Regardless of region, digital platforms have become essential tools for 21st-century social movements.  
 
Narrative
The internet health movement cannot succeed if it is siloed. Internet health and the likelihood of trustworthy AI increases as the need for both is prioritized by greater numbers of people. Internet growth rates in the global south measure over 10k% over the last decade. In Europe and North America where growth may now be slower, penetration rates hover around 90%. Regardless of region, digital platforms have become essential tools for 21st-century social movements.  


Interdependence is geographically inherent to the internet and a tenet upon which the efficacy of social movements relies. Building models of engagement that value geographic and social interdependence; reaching users in the fastest growing regions; and engaging those users already self-organized for purpose-driven activity, increases the likelihood of internet health becoming a priority more broadly, thus ensuring our success.  
Interdependence is geographically inherent to the internet and a tenet upon which the efficacy of social movements relies. Building models of engagement that value geographic and social interdependence; reaching users in the fastest growing regions; and engaging those users already self-organized for purpose-driven activity, increases the likelihood of internet health becoming a priority more broadly, thus ensuring our success.  
   
   
In 2020 Mozilla will prioritize partnering with constituencies where we may deepen our understanding and action toward common cause. Diverse movements can originate from expanded geographies, particularly the global south and east; and per the theory of change, from human rights-, consumer rights- and those sectors historically excluded from the progression of Internet health or artificial intelligence. “Partnership” is a synchronous engagement for growth, learning, benefit, change. Partnering can include funding, training, resourcing, research collaboration, united campaigning, convening.
In 2020 Mozilla will prioritize partnering with constituencies where we may deepen our understanding and action toward common cause. Diverse movements can originate from expanded geographies, particularly the global south and east; and per the theory of change, from human rights-, consumer rights- and those sectors historically excluded from the progression of Internet health or artificial intelligence. “Partnership” is a synchronous engagement for growth, learning, benefit, change. Partnering can include funding, training, resourcing, research collaboration, united campaigning, convening.
 
|+
2020
|2020 objective
objective
| Partner with diverse movements to deepen intersections between their primary issues and internet health, including trustworthy AI, so that we increase shared purpose.
Partner with diverse movements to deepen intersections between their primary issues and internet health, including trustworthy AI, so that we increase shared purpose.
|+
 
|}
2020
key results
 
[X]# of partners with whom we (have both) published something that includes shared language (that integrates thinking about their issues and internet health).
75% of partners from these diverse movements report deepening intersection between their issues and internet health/AI.
4 new partnerships in the Global South report deepened intersection between their work and ours.
 
 
 
Activities


 
{| class="wikitable sortable" cellpadding="3" width="100%"
 
|+
European digital rights funders network
|5.
Launch fellowship program of 5-10 fellows to support civil society orgs in the global south
|Org effectiveness
GIZ - Launch fellowship program and recruit and onboard 2 fellows to build voice libraries to grow the development of local innovation ecosystems for voice-enabled products
|+
Show up as experts and leaders on stages and in conversations in our network
|Short term outcomes
Map global events - feeding in fellowships and awards projects 
(1 - 3 years)
Create joint outreach strategy to policy influencers in Brussels
| A growing number of civil society actors are promoting trustworthy AI as a key part of their work.
Facilitate opportunities for publications with host orgs
|+
US 2020 Presidential election: disseminate talking points on the role of AI
|Narrative
Execute a public call for ideas in H1 that will feed into Internet Health Report content
|Over the last 5 years, MoFo has moved through a long period of growth and change. Through this change, we have built a solid set of programs focused on internet health and movement building, and have mapped out a vision for our work around trustworthy AI. As we follow through on this work, we need to build an increasingly high performing, effective organization with the supports and resources required to drive impact through these programs.  
 
Org effectiveness
 
 
Narrative
 
Over the last 5 years, MoFo has moved through a long period of growth and change. Through this change, we have built a solid set of programs focused on internet health and movement building, and have mapped out a vision for our work around trustworthy AI. As we follow through on this work, we need to build an increasingly high performing, effective organization with the supports and resources required to drive impact through these programs.  


We have strong foundations in place, but in many cases, we are still living with systems and models from a previous era. It is imperative that we understand the needs and shape of the Foundation now, and put updated approaches in place to confidently set us up to execute on our strategy for years to come. These include a long term funding model to ensure sustainability, new systems for gaining organizational insight and measuring performance, support for ensuring our people have the skills needed to excel in their roles and deliver on our goals, and a clear and transparent framework for decision-making.
We have strong foundations in place, but in many cases, we are still living with systems and models from a previous era. It is imperative that we understand the needs and shape of the Foundation now, and put updated approaches in place to confidently set us up to execute on our strategy for years to come. These include a long term funding model to ensure sustainability, new systems for gaining organizational insight and measuring performance, support for ensuring our people have the skills needed to excel in their roles and deliver on our goals, and a clear and transparent framework for decision-making.
 
|+
 
|2020 objective
2020
| Update our organizational models and capabilities so that our strategy and people can succeed, and our ambition can grow over multiple years.  
objective
|+  
Update our organizational models and capabilities so that our strategy and people can succeed, and our ambition can grow over multiple years.  
|}
 
2020
key results
 
70% overall favorable score for staff perception of organizational effectiveness.
A long-term funding model that matches our ambitions exists.
100% of staff strengthen skills (through PD) needed to accomplish our objectives.
 
 
 
Activities
 
 
 
 
 
Evaluate and redesign staff engagement survey, establish a “factor” for measuring organizational effectiveness
Optimize the cadence for annual planning and reporting to track impact and performance
Conduct org-wide debrief and analysis following key strategic planning and engagement moments
Evaluate contract/legal nimbleness (contract admin and process, approvals, bugzilla as a platform, risk tolerance, grant agreement templates, fluxx)
Audit all job descriptions
Develop and formalize the process of systematic monitoring of news and research relevant to internet health across a variety of topics to serve various stakeholders
Undertake sequencing of objectives/milestones over next 5 years
Ensure effective governance (effective board committees, advisory group)
Update and evaluate leadership team development and effectiveness (directors + execs)
Review CRM needs across the organization and evaluate effectiveness of Salesforce
Review investment portfolio management and investment policy
Develop and provide updated and more informative financial reporting by Department
Create a multi-year fundraising plan
Update case for support
Build out MoFo’s philanthropic strategy, creating grant cycles distinct from our funders
Refine professional development program (align to concrete work/projects/application of skills)


= Process =
= Process =
Swatson
196

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