人工智能在社会创新中的应用探讨白皮书（上）
今天阳民经济学要阅读一份白皮书，标题是《人工智能在社会创新中的应用》。这份白皮书非常重要。
首先，我阅读前言：
随着人工智能逐渐成为推动经济发展的驱动力，确保其用于造福人类和社会变得至关重要。在这个由快速技术进步定义的时代，人工智能展现出巨大的变革潜力，标准化既带来了承诺，也带来了挑战。
It has become increasingly evident that AI is not merely a tool for innovation, but when deployed responsibly and effectively, can be a force for social innovation, improving equality, shaping society, and redefining the global landscape. At the 2024 annual meeting of the World Economic Forum in Davos, social innovators, the private sector, and technology organizations came together to launch the AI for Social Innovation initiative, hosted by the Skoll Foundation and the Global Alliance for Social Entrepreneurship.
This initiative aims to ensure that AI improves lives and accelerates impact, and social innovators play a pivotal role here. In this first report on the status quo of AI in the social innovation space, we lay the foundation to enable social innovators around the world to use AI for impact. We map out the sector and highlight concrete examples at the forefront of driving the deployment of AI for social impact. The pace at which the technology evolves is nothing short of astonishing, from machine learning...
Social innovators in AI have a profound impact on our lives, promising efficiency, optimization, and new avenues for problem-solving. This work is released.
The development of AI has outpaced some of the information presented here. However, within this wave of progress lies a critical divide: a disparity in access to technology between the Global North and South persists, reinforcing existing inequalities and hindering the potential of AI to truly benefit all of humanity.
所以，这个数字鸿沟需要有针对性的、有意识的倡议，以促进可及性、公平性和包容性。弥合这一差距需要跨部门的协作努力，特别是社会企业。这类组织处于盈利与公益的交汇点，并提议利用创新方法，通过发挥人工智能的力量，来应对社会和环境挑战。社会企业有潜力以革命性的方式，精准解决从医疗保健到教育等领域的问题。
因此，它们正在为一个未来铺平道路，在这个未来中，技术进步与联合国可持续发展目标保持一致，以创造一个更加公平、可持续和公正的世界。
然而，人工智能对社会影响的承诺不仅仅依赖于技术本身，它还需要社会创新者能够准确认识到这项技术如何放大其影响力，并为他们配备必要的知识、技能和资源，以有效地利用这项技术。培训项目、能力建设倡议和知识共享平台至关重要。此外，确保私营部门、技术组织和社会创新者之间的对话对于创造可扩展、可持续并能应对当今世界最紧迫挑战的解决方案至关重要。
作为一名社会创新者和联盟成员，在探索人工智能用于社会影响的复杂格局时，我们希望这份报告能作为一个指南，阐明正在塑造技术驱动社会创新未来的战略和最佳实践。我们共同努力，可以驾驭人工智能的力量，为子孙后代建设一个更具包容性、公平和可持续的世界。
执行摘要：基于对300多名社会创新者和90多项倡议的新数据分析，本报告重点介绍了人工智能在推动社会创新方面的关键机遇与挑战。这份报告借鉴了来自横跨50多个国家的300多名社会创新者以及构成“人工智能促进社会创新”生态系统的90项倡议的广泛数据集。分析揭示，高收入地区和低收入地区的人工智能应用几乎具有同等代表性，突显了人工智能解决多样化社会问题的普遍潜力。
报告发现，人工智能主要在三个领域做出重大贡献：
医疗保健：25%的社会创新者利用人工智能来提升医疗服务的可及性。
环境可持续性：20%的社会创新者应用人工智能来应对气候解决方案。
经济赋权：特别是在低收入国家，80%的倡议都扎根于此，人工智能正通过预测分析和精准农业等方式，在农业、气候适应科学和提高生产力等领域带来革命性的实践。因此，在本文中，我们应该知道有8%的倡议致力于减贫。
报告还强调，虽然高收入国家（特别是美国）存在强大的人工智能影响生态系统，但低收入和中等收入国家缺乏对社会创新者或本地化倡议的支持。因此，将人工智能整合到社会创新的旅程伴随着挑战，远不止于生态系统支持不足。其他挑战包括数据偏见、技能差距、人工智能系统的技术复杂性以及有效实施人工智能解决方案所需的巨大资源。此外，该领域存在明显的性别差距，仅有25%的人工智能驱动型社会创新由女性领导，而全球所有社会企业中女性领导的比例为50%，这反映了更广泛的技术行业趋势。
尽管存在这些挑战，人工智能在社会创新中的益处是深远的：其自动化能力正在释放资源，使人们能够专注于战略性的影响工作；实时数据处理和先进的数据分析实现了更智能、基于证据的决策；个性化能力则提升了社会干预措施的有效性。
对于技术领导者、投资者和私营部门而言，本报告是一份强有力的行动号召，通过优先考虑包容和负责任的人工智能实践，促进跨部门紧密合作，并解决现有挑战，来支持人工智能生态系统的开发和部署。只有这样，人工智能的全部潜力才能被释放出来，以推动积极的社会变革，确保全球社区取得可及且公平的进步。
引言：人工智能在社会创新中的潜力是巨大的，但其成功取决于能否应对数据偏见和隐私等挑战。AI can revolutionize the industry, enhance efficiency, and solve complex problems, but it can also pose significant risks in areas such as security and societal change. The potential impact of AI is vast, offering groundbreaking opportunities in skills, education, environmental protection, and more. AI can optimize processes, create entirely new solutions, personalize experiences, and predict outcomes. However, these advancements come with risks such as job displacement, privacy invasion, and the amplification of vulnerabilities in code. The ethical use of AI, data governance, and the development of inclusive technology are critical considerations to ensure that the benefits of AI are realized without exacerbating existing inequalities or creating new forms of exclusion.
The World Economic Forum AI Governance Alliance is a multi-stakeholder initiative at the forefront of helping businesses and policymakers navigate the operational, security, and regulatory implications of AI. The AI Governance Alliance’s approach spans four work streams:
Responsible application and transformation
Resilient governance
National AI ecosystem
Safe systems and technology
The Alliance engages with a variety of stakeholders, including C-suite executives, public sector officials, AI developers, and civil society participants, to ensure that the development and deployment of AI technology remains inclusive, sustainable, and human-centric. It draws on the expertise of its members, industry technology organizations, academia, and civil society to shape guidelines and recommendations for the application of AI by businesses.
In January 2024, the Alliance released an inaugural briefing paper series, including a framework to guide businesses in their adoption of AI. The papers include guidance for responsible transformation and a structured approach toward responsible implementation of AI. The papers feature insights from industry leaders like Ikera and Google, showcasing the transformative power of AI. As business leaders navigate the AI landscape and manage change within large organizations, social innovators are often adopting creative AI solutions in resource-constrained environments.
In this complex landscape, social innovators leveraging market-driven solutions to societal challenges serve as a crucial conduit for harnessing positive attributes of AI while mitigating its risks, ensuring that technological advancement contributes to sustainable societal progress. Social entrepreneurs and social innovators in public and private spaces are central actors in delivering on the impact potential of this new technology. They work with communities around the world, understanding their contexts and needs based on their unique positioning, and have a front-row seat to technology adoption, providing important insights into the AI roadmap.
This report highlights the current landscape of AI in social innovation, presenting prevalent opportunities and changes. It is the first in a series of reports, with later editions to include frameworks for successful adoption, practitioner needs, guidelines for responsible deployment, and opportunities to positively influence the overall AI technology roadmap going forward.
To understand the impact potential of AI in social innovation, it is important to contextualize the technology. In its various forms, AI has been a key driver and enabler for social innovation in the past. Social innovation operates at the intersection of business, social relations, societal impact, and technological innovation. The role of technology in social innovation has evolved over time. Some of the earliest examples of social innovation in the eighties and nineties explain the influence of social innovation on technology adoption, especially how increasingly networked societies have managed to accelerate the adoption of technological innovation.
More recent studies, however, show adverse trends while technology plays a large role in driving social innovation itself. Figure two summarizes a 2016 Cambridge study that classified social innovation literature from 1989 until 2013, tracing the evolution of the concept of social innovation over time. It shows a strong rise in the role of technology as a foundation for social innovation. The mobile phone, for example, has been incredibly transformative in driving social change, especially in lowand middle-income countries. Mobile money dates back to 2007 with the introduction of innovators like M-Pesa, which provided their own bank an opportunity to save money and complete financial transfer transactions, triggering a range of economic ripple effects across many regions.
Similarly, critical weather and market data is now sent via very short message services, enabling rural farmers to improve productivity and negotiate better pricing. In this context, the impact of AI as a groundbreaking technology has understandably garnered much attention as one of the world’s top emerging technologies. AI has witnessed rapid growth and global adoption over the years. One of the key reasons for its acceleration over the past 20 years has been the rapid development in AI capability, made possible by changes in the ecosystem of parallel technologies.
Accelerating development of AI capability supports human ability and performance. Big data, for example, with its sheer volume, velocity, and variety, requires greater and more efficient means of processing. Consequently, the innovation of graphic processing units and cloud computing enabled AI systems to process such big data, and now, dedicated processors for AI applications have drastically increased data processing rates. The evolution of these technologies can further be attributed to the connected global community, which has enabled open-source software to spread from developer to developer, reducing redundant tasks and invention, and allowing companies to collaborate on best practices.
As AI capability and performance have quickly moved beyond human ability, organizations seeking higher returns on investment are motivated to invest more in research and development, contributing to the quality and advancement of AI. That’s all for today. We will continue tomorrow. Thank you very much.
