Ways Cooperatives Are Shaping the Future of AI

Artificial intelligence is often propelled by tech giants, which can create unequal outcomes: centralized control, limited transparency, and misalignment with public interests. Cooperatives—democratically governed, community-owned entities—offer an inclusive alternative. According to Scholz and Tortorici, AI cooperatives “won’t outspend Big Tech, but they could offer a more viable, inclusive path for AI aligned with public interest” (hbr.org). As Trebor Scholz and Stefano Tortorici (2025) note, “AI development is dominated by a handful of powerful firms, raising concerns about equity, accountability, and social harm.”

So, how can we ensure that AI benefits everyone, not just a select few? One promising answer lies in the cooperative model.

What Exactly Are Cooperatives?

Before we dive into AI, let’s understand what a cooperative is. Unlike traditional businesses that are owned by shareholders and primarily aim for profit, cooperatives are:

Member-Owned and Controlled: They are democratically governed by their members, who could be customers, employees, or producers. This means decisions are made collectively, often on a “one member, one vote” basis.

Values-Driven: Cooperatives operate on a set of ethical principles, including honesty, openness, social responsibility, and caring for others (International Cooperative Alliance, 1995). Their main goal is to meet the common economic, social, and cultural needs of their members, not just to maximize financial returns.

In essence, a cooperative is “an autonomous association of persons united voluntarily to meet their common economic, social, and cultural needs and aspirations through a jointly-owned and democratically-controlled enterprise” (International Cooperative Alliance, 1995, cited in ResearchGate, 2022).

Why Cooperatives are Crucial for AI’s Future

The cooperative model offers a powerful antidote to the centralized nature of current AI development. Here are five key ways cooperatives can shape a more equitable and beneficial AI future:

1. Democratizing Data Governance

AI systems thrive on data. Currently, large tech companies collect vast amounts of our personal data, often with limited transparency or control for the individual. This leads to “extractive data practices” (CDO Times, 2025).

Cooperatives can revolutionize this by creating data cooperatives. These are organizations where individuals pool their data while retaining control over how it’s used and collectively benefiting from its access. As the Ash Center (n.d.) highlights, “Data cooperatives offer an alternative to current extractive practices by aiming to shift the power from large corporations to the individual. They enable individuals to pool their data while retaining control over its use and collectively benefiting from its access.” This empowers end-users to decide who accesses their data, what data they can access, and for what purpose.

Example: Superset, a data trust, allows its members to contribute, govern, and be compensated for their data. It then negotiates with companies like Delphia on behalf of its members (Ash Center, n.d.). Another example is the Driver’s Seat Cooperative, which helps gig workers pool their data to optimize routes and boost their earnings (Ash Center, n.d.).

2. Bridging Research and Civil Society

Often, discussions and advancements in AI happen within academic institutions or corporate labs, far removed from the everyday concerns of ordinary people. Cooperatives can act as a crucial link, ensuring that AI development is “grounded in public needs, not elite institutions” (Scholz & Tortorici, 2025). By involving diverse community members, cooperatives can ensure AI technologies align with shared values and address real-world societal challenges.

3. Ensuring Ethical AI Development and Accountability

Concerns about AI’s ethical implications—such as bias, privacy, and job displacement—are growing. Cooperatives, with their inherent focus on social responsibility, are uniquely positioned to champion ethical AI. They can implement rigorous ethical guidelines and ensure that AI tools are compatible with their core principles of democratic control and serving communities (ResearchGate, 2022). This provides a built-in mechanism for “enforceable oversight, and an economic stake for community stakeholders” (Ash Center, n.d.).

4. Promoting Fair Distribution of AI Benefits

When a few companies control AI, the economic benefits tend to concentrate at the top. Cooperatives, by their very nature, are designed for shared prosperity. They facilitate “collaboration, resource pooling, and collective decision-making” (Platform Cooperativism Consortium, 2023). This model ensures that the value created by AI—whether through data insights or new services—is distributed equitably among members, rather than solely enriching shareholders.

5. Providing Access to Resources and Expertise

Developing cutting-edge AI often requires “vast computational resources, massive proprietary datasets, deep pools of technical talent” (CDO Times, 2025), which are typically only available to large corporations. Cooperatives can overcome this barrier through “resource pooling” (Platform Cooperativism Consortium, 2023). This could involve creating shared AI infrastructure, like a “cooperative research-focused cloud, owned and operated by nonprofits, government, and universities” (Ash Center, n.d.), allowing smaller organizations and researchers to access the tools they need without a profit motive.

Recommendations for AI Adoption in a Cooperative Spirit

For organizations looking to adopt AI responsibly and contribute to a more equitable AI future, consider these recommendations:

Prioritize Data Governance and User Control: Implement clear, transparent policies for data collection, usage, and sharing. Empower individuals to understand and control their data within your AI systems.

Foster Transparency and Explainability: Strive for AI models that are understandable and whose decisions can be explained. Avoid “black box” solutions where the reasoning is opaque.

Engage Stakeholders Broadly: Involve a diverse group of stakeholders—employees, customers, community representatives, and even competitors—in the design, development, and deployment of AI. Their input is crucial for identifying potential biases and ensuring alignment with societal values.

Explore Collective Ownership Models: Investigate the possibility of forming or joining data cooperatives, AI development collectives, or platform cooperatives. This can provide shared resources, reduce individual risk, and ensure collective benefit.

Invest in Ethical AI Training: Educate your teams on responsible AI principles, including fairness, privacy, and accountability. Develop internal guidelines for identifying and mitigating algorithmic bias.

Advocate for Supportive Policies: Support policies and regulations that encourage cooperative AI models, data trusts, and public AI infrastructure. This creates a more level playing field for innovation that serves the public interest.

Conclusion

The future of AI doesn’t have to be dictated by a few powerful entities. By embracing the principles of cooperation—democratic control, shared ownership, and a focus on collective well-being—we can steer AI development towards a “viable, inclusive path… aligned with public interest” (Scholz & Tortorici, 2025). Adopting AI with a cooperative mindset is not just about technology; it’s about building a future where intelligence serves humanity, ethically and equitably.

References

Ash Center. (n.d.) Cooperative Paradigms for Artificial Intelligence. Available at: https://ash.harvard.edu/resources/cooperative-paradigms-for-artificial-intelligence/ (Accessed: 5 July 2025).

CDO Times. (2025) 5 Ways Cooperatives Can Shape the Future of AI – Harvard Business Review. Available at: https://cdotimes.com/2025/06/30/5-ways-cooperatives-can-shape-the-future-of-ai-harvard-business-review/ (Accessed: 5 July 2025).

International Cooperative Alliance (ICA). (1995) Statement on the Cooperative Identity. Manchester.

Platform Cooperativism Consortium. (2023) Cooperatives Should Embrace the Opportunities of AI. Available at: https://platform.coop/blog/cooperatives-should-embrace-the-opportunities-of-ai/ (Accessed: 5 July 2025).

ResearchGate. (2022) (PDF) Cooperatives and the Use of Artificial Intelligence: A Critical View. Available at: https://www.researchgate.net/publication/366609688_Cooperatives_and_the_Use_of_Artificial_Intelligence_A_Critical_View (Accessed: 5 July 2025).Scholz, T. & Tortorici, S. (2025) 5 Ways Cooperatives Can Shape the Future of AI. Harvard Business Review. Available at: https://hbsp.harvard.edu/product/H08SJT-PDF-ENG (Accessed: 5 July 2025