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The Path Forward

Mozilla's Theory of Change

Table of Contents

Introduction to the Theory of Change

1. Shifting Industry Norms

1.1 Best practices emerge in key areas of trustworthy AI, driving changes to industry norms.
1.2 Engineers, product managers, and designers with trustworthy AI training and experience are in high demand across industry.
1.3 Diverse stakeholders — including communities and people historically shut out of tech — are involved in the design of AI.
1.4 There is increased investment in and procurement of trustworthy AI products, services and technologies.

2. Building New Tech and Products

2.1 More foundational trustworthy AI technologies emerge as building blocks for developers.
2.2 Transparency is included as a feature in more AI enabled products, services, and technologies.
2.3 Entrepreneurs develop — and investors support — alternative business models for consumer tech.
2.4 The work of artists and journalists helps people understand, imagine, and critique what trustworthy AI looks like.

3. Generating Demand

3.1 Trustworthy AI products and services emerge that serve the needs of people and markets previously ignored.
3.2 Consumers are increasingly willing and able to choose products critically based on information regarding AI trustworthiness.
3.3 Citizens are increasingly willing and able to pressure and hold companies accountable for the trustworthiness of their AI.
3.4 A growing number of civil society actors are promoting trustworthy AI as a key part of their work.

4. Creating Regulations and Incentives

4.1 Governments develop the vision, skills, and capacities needed to effectively regulate AI, relying on both new and existing laws
4.2 Progress toward trustworthy AI is made through wider enforcement of existing laws like the GDPR.
4.3 Regulators have access to the data and expertise they need to scrutinize the trustworthiness of AI in consumer products and services.
4.4 Governments develop programs to invest in and incent trustworthy AI.
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Introduction to the Theory of Change