2018年3月8-9日由约200名顶尖创业者、投资人和顾问组成,清均度摩纳哥大会.会议启动新特征Covington清洁公平对话,旨在捕捉和纪念摩纳哥聚会提供的独特思想领导机会。第一天,与会者分三次分组讨论查塔姆规则,由国际法律事务所伙伴主持Covington和BurlingLLP三大问题面对清洁技术部署和商业化

• AI和IoT-福利、风险和监管作用
• 可持续性-企业应优先实现什么目标? 正确的尺度是什么?
• 单靠市场驱动创新能拯救我们免受气候变化影响吗?

第二天,Covington团队在会议最后全体会议期间报告三大分组讨论的关键开销创新首都并乐于分享会议参与者过程所开发思想引导摘要

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AI和IoT-福利、风险和监管作用

• 人工智能和物联网的快速进化和扩散为几乎每一个行业带来巨大希望,实现巨变效率提高
• 同时这些技术带来大规模中断就业、隐私损失和人自由意志产生算法和机器决策的风险

由Covington公司伙伴主持赛门爱米斯会议与会者研究了这些提议并接着审议了两个问题:监管应站到哪里去?监管能有效管理风险而又不削弱收益吗?

福利类

人们普遍同意AI和物联网进化扩散有可能在几乎所有产业部门实现转化效率增益。 AI通过部署精密算法处理大量数据,已经改变了技术部门商业模式,机器学习自动化已经在工业其他领域大规模使用,流程革命化并实现显著效率增益。

A number of the presenting companies noted that artificial intelligence already plays a pivotal role in their businesses, with some utilizing the technology at the heart of their business model — one company uses its machine learning system to manage and optimize grid operations — and others use AI as a tool to enhance research and refine product development.  One participant flagged the fundamental change to supply chain dynamics and manufacturing processes with the emergence of the smart factory in the Industry 4.0 model, leading to increased efficiency, reduced costs and maximization of resources.  Mass-customisation of lower-cost goods manufactured to order in close proximity to the market bring reduced shipping costs and lead times.

风险类

常见的干扰技术 出现新风险与挑战

一位与会者指出对获取、控制及拥有保健领域个人数据的关切,重点是开发个性化精度药材;另一位与会者表示个人数据可如何被雇主或承保者使用以支付汽车或生活保值,但未经个人明确同意

一位与会者指出自动智能系统取代人控制汽车和其他机器和设备的安全和安保问题;在自主车辆方面,系统自觉判断错误并造成死亡时由谁负责事故处理?另一位与会者指出恶意攻击者干扰或坚持控制AI和IoT系统的风险,无论是工业规模或微级均想利用个人

AI和IoT对工作的威胁也得到了强调。 许多工作令员工代代相传几乎一夜之间都可能成为冗余,因为企业想采用技术提高效率和生产率并同时降低人工成本。 劳动力市场预计会经历自工业大革命以来未曾见的大规模变换,这将对财富不平等和潜在全球稳定产生影响。政府和决策者可能采取步骤保护工作,但对技术技师支持数字能力的需求将增加

作用调控

讨论侧重于两个关键问题:(a) 监管应步进何方和(b) 监管能有效管理风险而又不损益

The first observation was that against the backdrop of recent high profile data breaches and the imminent deadline for implementation of the EU's General Data Protection Regulation, regulation is appropriate and has an important role in managing the risks presented by AI and IoT.  Data privacy legislation has continually evolved since the emergence of the internet, adapting and reacting to the challenges associated with mass collection, use and storage of personal data to ensure privacy, security and transparency.  Privacy laws already apply to AI systems that process personal data, which means new systems need to be designed adhering to these standards where applicable.

一位与会者评论说,不应留待立法者确保风险得到充分立法处理。市场参与者,特别是大公司,也可以发挥作用,通过采纳反映关键道德原则的最佳做法守则,确保以负责任和公平实践为依托,据指出微软已制定了六大道德原则指导人工智能开发使用-AI系统应公平、可靠和安全、包容、透明并接受问责[1]

一位与会者指出,当前产品责任法将适用自主车辆风险问题,这意味着如果损失由车辆造成,发现该车辆有缺陷或不安全,则可能存在索赔问题。 这些法律有可能演进以澄清责任何在,制造商和保险公司将面向立法者制定控制无驱动车辆自主系统在特定情况下应如何操作而不是自主决策的标准

与会者指出,对AI和IoT标准和规则的通过需要全球一致协调,经济合作与发展组织等国际决策人需要制定普遍接受的标准。 发达国家间越来越激烈的武器竞赛开发成为AI和IoT的经济领先者,这将具有挑战性。

The final point tackled by the group was the need for employment laws to evolve to recognize the changes in employment practices that are likely to flow from the move to automated systems.  Current employment laws are based around the model of employers employing workers at specific worksites, whereas people are increasingly engaged through remote, part-time or project-based work.  As jobs are displaced through adoption of AI and IoT, new skilled roles will be created to develop, monitor and manage the new systems.  Governments will have an important role in ensuring that the education curriculum adapts to ensure students acquire the necessary skills required to support digital capabilities.

[1]微软2018年未来计算-人工智能及其社会作用.https://blogs.microsoft.com/uploads/2018/02/The-Future-Computed_2.8.18.pdf