马克·戈尔斯基 译/陈栋 Mark Gorski
Over 700 million people use wearable technology like smartwatches， fitness bands and medical devices. These consumers create extremely valuable data from their daily lives—sleeping， working， sweating and everything in between. Consumers currently pay companies huge sums of money for access to technology as part of an industry， and every time consumers use wearable devices， theyre giving away their personal data for free. Ironically， companies then use this data to create more products they sell back to consumers， and the cycle repeats.
However， instead of paying for smart devices and allowing manufacturers free， full access to their information， what if they paid consumers instead？ A new asset class is emerging—human health data—that is generating significant value for companies by fueling the health analytics they provide， with consumers largely unaware their data is becoming a capital asset1 in high demand. And this archaic2 model for value creation is about to be flipped on its head3.
Welcome to the Human Data Economy， where consumers will soon be able to monetize4 their health information and take control over how， where and when their data is used. Similar to influencers like the YouTube and TikTok stars of today， an entirely new group of content creators—data creators—will emerge. Data creators， which can be anyone from professional athletes to casual consumers， will generate Human Data from wearable devices and other systems and choose to voluntarily share their information with interested parties.
The market for Human Data that can power systems to better understand our bodies， provide personalized treatments and predict future health outcomes is immense. In health care alone， the analytics market is expected to reach over $67 billion by 2025， while the telehealth market is expected to reach over $559 billion and the health care insurance market $4 trillion by 2027. Growth is largely driven by user-generated health data， thus creating significant opportunities for data creators to monetize their information.
Although artificial intelligence and statistical-based tools are in the early days of powering a Human Data-centered economy， they are rapidly advancing. Machine learning models are being developed in order to collect data from multiple sources to learn about individuals and help improve their health. New AI-based techniques are demonstrating the potential to generate insights based on users activities， physiology5， genetic profile， genomics6， blood， sweat and tears7 （pun intended） that will predict future health risks and outcomes， including heart disease and stroke. For these tools to develop further， quality data is essential. It is improving fast， as higher-sampling sensors can provide better and more granular8 data in every area of users lives—sleep， fitness， you name it.
However， we arent quite there yet. For starters， many sensors （like your smartwatch） have only proved their effectiveness in limited environments （e.g.， sleeping） while falling short in both accuracy and repeatability9 for other activities （e.g.， high-activity workouts）. Collecting large datasets is also challenging. Data creators often do not provide their full profile information， nor do they maintain the regimen10 of documenting their daily lives. This lack of contextual information leads to incomplete datasets. Companies also oftentimes eschew data-sharing， which leads to silos of know-ledge and prevents important advances in research and discovery.
But were getting there. To continue this evolution， analytics systems need good， categorized data—and lots of it—which is why a monetization-based access model could explode industry growth. Enabling data creators to provide companies with access to their personal data in exchange for compensation can allow companies to request exactly what data theyre looking for and from whom. This should expedite the collection of the right data in the right quantities to make products and research better targeted and more valuable. Companies could also demand a higher degree of data quality and eliminate “garbage-in， garbage-out11” scenarios often caused by the misuse of wearable tech by casual users. Human Data could also become more widely available to organizations that can unlock its value.
Research published by BMC12 Public Health found that a majority of consumers are willing to wear digital devices and share their data if theyre given financial incentives， including with their health insurers. We have recently experienced this in sports， and in medicine， volunteers are already provided financial incentives for participation in clinical trials and other research.
While explicit consent and control over information distribution should alleviate many privacy concerns， thoughtful approaches are needed to overcome existing challenges. These include obtaining ethically sourced data （e.g.， from known， consenting sources without modification）， preventing unauthorized data sharing or use， transitioning current wearable systems to enable customer data access， and current health data regulations. These barriers will necessitate clear， legally supported rules of engagement between technology organizations， regulators and data creators in order to develop consumer confidence， enable further transparency and build trust.
In the emerging Human Data Economy， sensor technologies and other products should improve as access to data increases. Users who are unable to afford wearables may have them provided at no cost. New types of revenue models and businesses will emerge， including data agents who can help manage and monetize your data. Technol-ogies that can broker， track， and enforce data sharing agreements between data creators， technologies and acquirers will become the next unicorns.
This all suggests that were reaching a tipping point13 where the value of data created from wearables is exceeding the value of the wearables themselves. It will continue to accelerate as data creators use their newly controllable assets to enrich their social environment by sharing their generated content. By widening the availability of Human Data and broadening the appeal of its use—from livestreaming biometric data in workout classes to viewing sponsored， on-screen stress levels of reality show contestants—todays consumers will become tomorrows data creators with rights to control， share and monetize their information. Concurrently， this data will advance our collective understanding of the human body while fostering more transparency and creating an entirely new economic proposition.
Welcome to the Human Data Economy.
使用智能手表、健康手環和医疗设备等可穿戴技术产品的人超过7亿。这些用户在日常生活中创造出极具价值的数据——不管是睡觉、工作、出汗，还是干其他事的时候。作为产业的一部分，现在用户使用技术产品需向企业支付高昂的费用，而且用户每次使用可穿戴设备，都在免费贡献自己的个人数据。讽刺的是，企业之后又用这些数据创造出更多的产品卖给用户，如此循环往复。
但是，如果是制造商付钱给用户，而不是用户花钱购买智能设备并允许制造商免费访问他们的全部信息，那会怎么样？一种新的资产品类正在浮现，即健康数据，它能提升企业的健康分析服务，给企业创造巨大价值，而大多数用户并未意识到自己的数据正在成为一项紧俏的资本资产。这种陈旧的价值生产模式即将发生翻天覆地的变化。
欢迎来到人类数据经济时代。在这里，用户即将能用自己的健康信息赚钱，并有权决定自己的数据在哪、何时以及怎样被使用。类似于如今优兔和抖音国际版等平台的网红，一类全新的内容生产群体——数据创作者——将应运而生。从专业运动员到普通用户，数据创作者可以是其中任何人。他们将通过可穿戴设备和其他系统生产数据，并自愿选择将自己的数据分享给感兴趣的人。
人类数据市场需求巨大，它可以驱动各种系统更好地了解我们的身体，提供个性化治疗并预测未来健康结果。单就卫生保健而言，分析市场预计到2025年将超过670亿美元，而到2027年，远程医疗市场预计将超过5590亿美元，医疗保险市场预计将超过4万亿美元。增长主要由用户生产的健康数据驱动，这就为数据创作者将自身信息变现创造大量机会。
虽然人工智能和以统计学为基础的工具在驱动人类数据经济方面处于初期阶段，但它们在快速发展。机器学习模型正在研发当中，以便收集各方数据来研究个体，并帮助改善其健康。新的人工智能技术正展现出潜力，能基于用户的活动、生理机能、基因图谱、基因状况、血汗和泪水（一语双关）形成分析，从而预测包括心脏病和中风在内的未来健康风险和结果。这些工具要想取得进一步发展，优质数据必不可少。这方面的进步很快，因为采样率更高的传感器可以在用户生活的各个领域提供更好的、颗粒度更细的数据——睡眠、健康度，随便你说。
不过我们还没完全走到那一步。首先，许多传感器（譬如智能手表）只在有限环境（譬如睡眠）中证明了有效性，而在进行其他活动（如高强度运动）时，其精确度和重复性会大打折扣。收集大量数据集也是一大挑战。数据创作者通常不会提供全部的个人资料信息，也不会保持记录日常生活的习惯。这种情境信息的缺失导致数据集的不完整。企业之间通常也不会数据共享，导致知识封闭，阻碍了研究发现的重大进步。
但我们正在向前迈进。要让这一发展持续，分析系统需要大量分门别类的优质数据——这也是为何货币化的数据访问模式可以使行业实现爆炸式增长。如果让数据创作者能够向企业提供个人数据的访问权限换取报酬，就可以精准地从想要的人那里获取想要的数据。这将加速收集合适体量的合适数据，从而使产品和研究更有针对性、更具价值。企业也可以对数据质量提出更高的要求，消除马虎的用户错误使用可穿戴技术产品导致的“无用输入无用输出”常见情况。能够解锁人类数据价值的组织也将更容易获得这种数据。
《BMC公共卫生杂志》发表的研究论文发现，大部分用户在得到金钱激励后愿意使用电子设备并分享其数据，分享对象包括他们的健康保险公司。近来我们已经在体育、医疗领域有过这样的经验——临床试验和其他研究在招募志愿者时便会提供金钱激励。
虽然征求明确同意和控制信息传播可以消除许多隐私问题，我们仍需要深思熟虑的手段来克服已有的挑战。这些挑战包括：从合乎道德的来源获取数据（譬如从征得许可的已知来源获取且不加修改）、防止未经授权而分享或使用数据、转换当前的可穿戴系统以实现客户数据访问，以及现行的健康数据法规约束。这些障碍的存在使得技术机构、监管部门和数据创作者之间必须制定明确的、受法律支持的关联规则，以建立用户信心、进一步提高透明度并建立信任。
在新兴的人类数据经济中，传感器技术和其他产品应当随着数据访问的增加而改进。买不起可穿戴设备的用户或将免费获得这些设备。新的创收模式和业务类型将会出现，包括帮助打理数据并将其变现的数据代理商。能够在数据创作者、技术和需求方之间协调、跟踪和执行数据共享协议的科技公司将成为下一批独角兽。
这一切都表明我们将要到达一个临界点，即可穿戴设备产生的数据价值将超过可穿戴设备本身。随着数据创作者不断分享其生成的内容，用这一新型可控资产来丰富自己的社交环境，这一临界点将会加速到来。通过拓展人类数据的可及性并扩大其用途吸引力——从直播健身课程中的生物特征数据，到在屏幕上收看用受赞助的可穿戴设备展示的真人秀选手压力水平——今天的用户将成为明天的数据创作者，他们有权控制、分享和变现自己的信息。同时，这些数据将促进我们对人体的共同理解，提高透明度并创造出一个全新的经济命题。
欢迎来到人类数据经济时代。
（译者为“《英语世界》杯”翻译大赛获奖者）
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