Collective Action, Indigenous Wisdom & AI in Social Entrepreneurship

This article explores the evolving landscape of social entrepreneurship, emphasizing collective action, social movements, and indigenous wisdom. It also delves into the transformative role of Artificial Intelligence (AI) in social entrepreneurship, featuring insights from social entrepreneurs Pavia Chan and Bellabes Ben Creda.

The Evolution of Social Entrepreneurship

The traditional view of entrepreneurship often focuses on individual "heropreneurs" starting new ventures. However, this perspective is shifting towards a more collaborative and community-oriented approach. The problems facing the world are vast and complex, making individual solutions insufficient. Instead, the focus should be on collective action and joining existing movements.

Key Shifts in Thinking:

• Collective Action over Individualism: The idea that no single person can solve global problems. Instead, individuals should seek out others who care about the same issues, learn from their efforts, and find ways to contribute to collective solutions. This solidarity and shared effort, even if not immediately successful in achieving large-scale change, is a powerful way to make a difference.
• Social Movements: Social enterprises are increasingly viewed as integral parts of larger social movements. Understanding the movements a social enterprise belongs to can inform its decision-making, program design, and overall operations. For example, Havenly, a coffee shop supporting refugee and migrant women, operates at the intersection of women's movements, immigrant movements, and the solidarity economy, which shapes its leadership structure and long-term goals.
• Indigenous Wisdom: There's a growing recognition that true innovation might not always lie in new technologies or ideas, but in rediscovering ancient wisdom. Indigenous communities often possess profound knowledge about caring for each other and the planet, which has been lost in modern society. Engaging with indigenous leaders and learning from their practices, such as those seen in AANA Ventures supporting nature-based indigenous entrepreneurs, can offer sustainable and community-focused approaches to development.

AI and Social Entrepreneurship

AI is emerging as a powerful tool that can democratize entrepreneurship and accelerate social impact. While concerns about AI's negative repercussions (like global warming, data centers, and biases) are valid, there's a strong argument for social entrepreneurs to engage with AI to ensure its development and application serve the public good.

AI as an Enabler:

• Leveling the Playing Field: AI tools can empower entrepreneurs who might otherwise feel limited by a lack of technical skills or resources. It allows for rapid prototyping and testing of ideas, making it easier for individuals, including those from underrepresented groups or lower-income countries, to bring their visions to life.
• Accelerating Development: AI can significantly reduce the time and effort required for tasks like designing prototypes or implementing code. What once took weeks or months can now be done in minutes, allowing social entrepreneurs to iterate quickly and respond to feedback.
• Ethical AI Development: It's crucial for AI to be developed "by, with, and for" diverse voices, including those from the global south, women, and indigenous people. This proactive approach can prevent the repetition of past mistakes where new technologies exacerbated existing inequalities.

Case Study: Haven and AI for Health Equity

Pavia Chan's social enterprise, Haven, exemplifies how AI can be harnessed for social good. Haven aims to create a safe haven for patients and caregivers navigating chronic illness by connecting them with pharmaceutical resources they often don't know about or can't easily access.

• The Problem: Pharmaceutical companies invest heavily in patient resources, but patients often lack the bandwidth or technical know-how to utilize them.
• Haven's Solution: Haven's software, powered by AI, integrates with electronic health records. When a doctor prescribes medication, the software identifies eligible resources and can even automatically enroll patients.
• AI in Action (Hype Coding): Pavia used "hype coding" – leveraging AI platforms like Cursor and Claude – to build her Minimum Viable Product (MVP). This allowed her to rapidly prototype her vision without extensive coding knowledge. She could refine her ideas through conversations with the AI, and the AI would generate the necessary code, pushing changes to the platform in minutes.
• Stakeholder Engagement and Iteration: The MVP was then demonstrated to key stakeholders, including community hospitals, specialty care clinics, and pharmacists. This feedback was crucial. Initially, Haven was designed solely for patients and caregivers, but stakeholder input revealed a significant need for pharmacists and other healthcare professionals to use the platform. AI enabled rapid implementation of these changes.
• Pilot and Scaling: The next step involves an unpaid pilot with a small group of patients through a community health center. The results from this pilot will then be used to secure funding from venture capitalists to hire engineers, scale the platform, and conduct larger pilots in bigger health systems.
• AI Reinforces Human Interaction: A key takeaway from Haven's journey is that AI doesn't replace human interaction; it reinforces it. By automating technical tasks, AI frees up social entrepreneurs to focus on building relationships, gathering feedback, and responding to the needs of their communities.

The Fourth Wave of Public Spheres: AI-Driven Communication

Bellabes Ben Creda's startup, Public Spheres.org, addresses the transformation of public discourse through AI. Historically, public spheres have evolved through several stages:

1. Oral Tradition: The agora or town square, where communication was limited by sound travel.
2. Print: The advent of printing created the first mass publics, primarily a reading bourgeoisie.
3. Broadcast Media: Radio and television enabled truly mass publics, transcending literacy barriers.
4. Internet/Social Media: Facilitated "many-to-many" communication, where everyone can be a speaker and author.
5. AI-Driven Public Spheres: Bellabes hypothesizes that AI will usher in a fourth structural transformation, making intelligence ubiquitous and profoundly reshaping how societies debate and make decisions.

Public Spheres.org aims to define what healthy AI-driven public spheres should look like, rather than leaving it to chance or purely to Silicon Valley. The startup proposes seven guideposts for healthy conversation: civility, truth, shared arenas, common concerns, efficacy, equal opportunity, and pluralism. By using AI to diagnose existing public spheres against these guideposts, the goal is to identify what's going wrong and inform the development of more robust and democratic communication spaces. This involves using AI to capture and analyze public discourse, providing high-fidelity diagnostics across geographies and over time.