DeepMind has almost apologized. The NHS trust has mended its ways. Further arrangements — and there may be many-between the NHS and DeepMind will be carefully scrutinised to ensure that all necessary permissions have been asked of patients and all unnecessary data has been cleaned. There are lessons about informed patient consent to learn. But privacy is not the only angle in this case and not even the most important. Ms. Denham chose to concentrate the blame on the NHS trust, since under existing law it “controlled” the data and DeepMind merely “processed” it. But this distinction misses the point that it is processing and aggregation, not the mere possession of bits, that gives the data value.
DeepMind几乎已经道歉了。国民保健服务的信任已经改变了方式。NHS和DeepMind之间的进一步安排 —— 可能会有很多 —— 将被仔细审查，以确保所有必要的权限已被问及患者，并清除了所有不必要的数据。有关于知情患者同意学习的经验教训。但隐私并不是在这种情况下唯一的角度，甚至不是最重要的。Denham女士选择把责任归咎于NHS信任，因为根据现有的法律，它‘控制’了数据，而DeepMind只是‘处理’了数据，但是这种区别错过了它正在处理和聚合的观点，而不是仅仅拥有位，这给出了数据的价值。
Any fair-minded assessment of the dangers of the deal between Britain’s National Health Service (NHS) and DeepMind must start by acknowledging that both sides mean well. DeepMind is one of the leading artificial intelligence (AI) companies in the world. The potential of this work applied to healthcare is very great, but it could also lead to further concentration of power in the tech giants. It Is against that background that the information commissioner, Elizabeth Denham, has issued her damning verdict against the Royal Free hospital trust under the NHS, which handed over to DeepMind the records of 1.6 million patients In 2015 on the basis of a vague agreement which took far too little account of the patients’ rights and their expectations of privacy.
对英国国民健康服务（NHS）和DeepMind之间的交易的危险性进行公平的评估，必须首先承认双方的用意都是好的。DeepMind是全球领先的人工智能（AI）公司之一。这项工作应用于医疗领域的潜力非常大，但也可能导致科技巨头进一步集中力量。正是在这种背景下，信息专员伊丽莎白·德纳姆（Elizabeth Denham）对NHS下的皇家免费医院信托公司（Royal Free hospital trust）发出了有害的判决，该信件向DeepMind交付了160万患者的记录。根据一个模糊的协议对于患者的权利和对隐私的期望的描述太少了。
The great question is who should benefit from the analysis of all the data that our lives now generate. Privacy law builds on the concept of damage to an individual from identifiable knowledge about them. That misses the way the surveillance economy works. The data of an individual there gains its value only when it is compared with the data of countless millions more.
最重要的问题是，谁应该从分析我们现在生活的所有数据中受益。隐私法基于对个人的可识别知识的损害概念。这忽略了监视经济的运作方式。一个人的数据只有在与无数的数据相比较时才能获得其价值。
The use of privacy law to curb the tech giants in this instance feels slightly maladapted. This practice does not address the real worry. It is not enough to say that the algorithms DeepMind develops will benefit patients and save lives. What matters is that they will belong to a private monopoly which developed them using public resources. If software promises to save lives on the scale that dugs now can, big data may be expected to behave as a big pharm has done. We are still at the beginning of this revolution and small choices now may turn out to have gigantic consequences later. A long struggle will be needed to avoid a future of digital feudalism. Ms. Denham’s report is a welcome start.
在这种情况下，利用隐私法遏制科技巨头感觉有点不适应。这种做法没有解决真正的担心。仅仅说DeepMind算法的开发将使患者受益并挽救生命是不够的。重要的是，它们将属于利用公共资源发展起来的私人垄断。如果软件承诺在现在挖掘的规模上挽救生命，那么大数据可能会像一个大制药公司那样行事。我们还处于这场革命的开始阶段，现在的小选择可能会在后来产生巨大的后果。为了避免数字封建的未来，需要进行长期的斗争。德纳姆女士的报告是一个受欢迎的开始。
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