前沿資訊/
數聯惠法平臺最新推出欄目，以世界各行業先進報刊、精英雜誌作為原文引用來源，在法律、財經、金融與科技的交叉領域進行檢索，篩選收集行業的前沿資訊，最終翻譯整合進行專題推送，共同了解大數據時代、科技時代、人工智慧時代的行業發展新動向。
【前沿資訊002】本期內容來自《SSRN工作文件》和《哈佛商業評論》共計三篇前沿資訊文章，分別與Data Pollution（數據汙染）、AI（人工智慧）、Lifelong learning（終身學習）有關。
01/ Data Pollution
數據汙染
SSRN Working Paper, June 2018Omri Ben-Shahar
Digital information is the fuel of the new economy. But like the old economy's carbon fuel, it also pollutes. Harmful "data emissions" are leaked into the digital ecosystem, disrupting social institutions and public interests. This article develops a novel framework- data pollution-to rethink the harms the data economy creates and the way they have to be regulated. It argues that social intervention should focus on the external harms from collection and misuse of personal data. The article challenges the hegemony of the prevailing view-that the harm from digital data enterprise is to the privacy of the people whose information is used. It claims that a central problem has been largely ignored: how the information individuals give affects others, and how it undermines and degrade public goods and interests. The data pollution metaphor offers a novel perspective why existing regulatory tools-torts, contracts, and disclosure law-are ineffective, mirroring their historical futility in curbing the external social harms from environmental pollution. The data pollution framework also opens up a rich roadmap for new regulatory devices-an environmental law for data protection-that focus on controlling these external effects. The article examines whether the general tools society has long used to control industrial pollution-production restrictions, carbon tax, and emissions liability-could be adapted to govern data pollution.
數字信息是新經濟的能源。但就像舊經濟的碳燃料一樣，它也可能造成汙染。有害的「數據排放」被洩露到數字生態系統中，擾亂了社會結構和公共利益。本文開發了一個新的框架——數據汙染，來重新思考數據經濟帶來的危害以及數據經濟的監管方式。本文認為，社會幹預應集中在收集和濫用個人數據的外部危害。這篇文章挑戰了主流觀點的霸權——數字數據企業的危害是其信息使用者的隱私，表明了在一個核心問題的被忽視了: 個人提供的信息如何影響他人，以及它如何破壞和降低了公共產品與利益。數據汙染隱喻提供了一個新的視角，為什麼現有的監管工具——侵權，合同和披露法都是無效的，反映了他們在遏制外部社會危害環境汙染方面的歷史無用性。 數據汙染框架還為新的監管設備開闢了豐富的路線圖—— 一種用於數據保護的環境法，專注於控制這些外部影響。 本文探討了是否社會長期以來用於控制工業汙染生產限制、碳稅和排放責任的一般工具也可以適用於管理數據汙染。
02/ How Marketers Can Start Integrating AI in Their Work
營銷人員如何開始將AI運用到他們的工作中
Harvard Business Review, May 29, 2018Dan Rosenberg
Artificial Intelligence (AI) holds great promise for making marketing more intelligent, efficient, consumer-friendly, and, ultimately, more effective. Smart marketers are developing, partnering to build, or integrating AI into their tech stacks to get better at what they do. To get started leveraging AI in your marketing efforts, it’s important to first confirm your policies regarding the handling of consumer data, transparency, and control. Consumers should be able to interact with connected devices — from web browsers to mobile phones to voice assistants — knowing that their data is being used in transparent ways, in a manner consistent with their preferences and expectations. Then, make sure that your data is actionable, for example by using a unique, common identifier for individual consumers across all of your company’s various channels and touchpoints. What's more, be sure to choose the right AI partner. Be sure to choose a partner that has true AI, not simply rules-based decisioning, which is impossible to scale for the volume of data and combinations of interactions that marketers are managing today. In addition, be sure to choose partners with real experience addressing your particular use cases and working with your existing technology partners. Finally, as with any vendor relationship, be sure to check on your partner’s ethical and philopshical approach to AI, as this is still an emerging technology that demands thoughtful guardrails to produce effective results in a responsible manner.
人工智慧（AI）有望使營銷更加智能，高效和實現消費者友好，並讓營銷最終更有效。聰明的營銷人員正在開發、合作建立或將AI集成到他們的技術堆棧中，以便更好地完成他們的工作。要在營銷工作中開始利用AI，首先要確認有關處理消費者數據的透明度和控制他們的政策，這一點非常重要。消費者需要能夠與連接的設備進行從網絡瀏覽器到行動電話再到語音助理交互，知道他們的數據以透明的方式使用，並且符合他們的偏好和期望。然後是確保數據可操作，例如，為公司的各種渠道和接觸點中的個人消費者使用唯一的公共標識符。更重要的是，一定要選擇合適的AI合作夥伴：一定要選擇具有真正AI的合作夥伴，而不僅僅是基於規則的決策，因為這對於營銷人員今天管理的數據量和交互組合是無法實現的。此外，務必選擇具有實際經驗的合作夥伴，以解決特定用例並與現有的技術合作夥伴合作。最後，與任何供應商的關係一樣，一定要檢查合作夥伴對AI的道德和哲學方法，因為這仍然是一種新興技術，需要周到的護欄並以負責任的方式產生使結果有效。
03/Automation Will Make Lifelong Learning a Necessary Part of Work
自動化將使終身學習成為必要的工作
Harvard Business Review, May 24, 2018Jacques Bughin, Susan Lund and Eric Hazan
McKinsey researchers analyzed the skill requirements for individual work activities in more than 800 occupations to examine the number of hours that the workforce spends on 25 core skills today. They then estimated the extent to which these skill requirements could change by 2030, as automation and artificial technologies are deployed in the workplace, and backed up their findings with a detailed survey of more than 3,000 business leaders in seven countries, who largely confirmed the quantitative findings. The findings highlight the major challenge confronting workforces, economies, and the well-being of society. Among other priorities, they show the urgency of putting in place large-scale retraining initiatives for a majority of workers who will be affected by automation—initiatives that are sorely lacking today. To give a sense of magnitude: more than one in three workers may need to adapt their skills』 mix by 2030, and lifelong learning of new skills will be essential for all.
麥肯錫的研究人員為了檢查勞動力今天花費在25種核心技能上的小時數，分析了800多種職業中個人工作活動的技能要求。他們接著估計了因為工作場所部署了自動化和人工技術，到2030年這些技能要求可以在多大程度上改變，並通過對七個國家等3000多名商業領袖的詳細調查來支持他們的調查結果。發現，調查結果突出了勞動力、經濟和社會福祉面臨的主要挑戰。除其他優先事項外，它們還顯示了為大多數受到自動化措施影響的工人實施大規模再培訓計劃的緊迫性。給人帶來的警示是：到2030年，超過三分之一的工人可能需要調整他們的技能組合，因此終身學習新技能對所有人來說都是必不可少的。