人工智能的影响：加强人工智能生态系统以促进社会创新（英）

AI for Impact: Strengthening AI Ecosystems for Social Innovation

Executive Summary

The transformative potential of artificial intelligence (AI) is widely recognized, with studies indicating that employees who deploy machine learning can achieve up to 30% in efficiency gains and that the technology has the potential to automate up to 70% of activities that consume employees' time. According to the IBM Global AI Adoption Index, 42% of companies have already deployed AI to improve efficiency in customer care, IT, and marketing sales functions, while an additional 40% are exploring its use within their enterprises. Despite these benefits, concerns about AI's environmental and societal impacts are growing, with some studies suggesting that over a third of employees fear losing their jobs due to AI.

Social innovators are at the forefront of demonstrating the positive impact of AI. They are uniquely positioned to deploy AI solutions tailored to community needs, especially for underrepresented communities, and to influence the future development of the technology toward positive outcomes. An earlier report highlighted how 300 social innovators have begun using AI capabilities like machine learning and predictive analytics to create impactful results, such as improving healthcare accessibility and enhancing educational outcomes in underserved communities.

To scale the adoption of AI for impact, social innovators rely on collaboration with tech companies, intermediaries, impact investors, and public-sector stakeholders. However, the report's analysis shows that only 31% of nearly 100 reviewed AI initiatives focus on positive impact. Among those that do, less than half provide direct financial resources.

Key Findings

1. Private-Sector Support: The private sector plays a critical role in supporting social innovators through technology access, mentoring, and networks.

   • Microsoft's Entrepreneurship for Positive Impact: Provides technology access, mentoring, and networks to empower social entrepreneurs.
   • EY Ripples: Extends EY teams' knowledge to provide professional services and skills development programs.

2. Intermediary Role: Intermediaries are essential in bridging the gap between tech organizations and social innovators.

   • Program Design and Facilitation: Program design, network and access facilitation, information exchange, training, and capacity building.
   • Engagement Mechanisms: Mechanisms to engage the ecosystem and other collaborators.

3. Challenges in Deployment: Despite the potential, challenges remain in deploying AI for impact.

   • Resource Allocation: Limited direct financial resources provided to social innovators.
   • Regulatory Considerations: Need for robust policy and regulatory frameworks to guide AI development and deployment.

4. Drivers of Success: Successful AI initiatives for social innovation often leverage:

   • Ethical Principles: Ethical guidelines and missions to serve.
   • Collaborative Efforts: Collective efforts to support and scale social innovations.

5. Policy and Regulatory Considerations: There is a need for policies and regulations that ensure AI is developed and deployed responsibly, focusing on inclusivity, ethics, and shared prosperity.

Conclusion

The initiative aims to harness the power of AI to create a just and prosperous society by supporting social innovators and scaling their impact. By fostering collaboration among tech companies, intermediaries, impact investors, and public-sector stakeholders, the ecosystem can better support the responsible and impactful deployment of AI. The goal is to ensure that AI serves underrepresented communities and unlocks its full potential for societal good.

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Image Credit: TechnoServe