We will be releasing a white paper, early in the new year, challenging the view that consent and personal control of one's data by data subjects is a thing of the past—it is not. In fact, in the wake of Edward Snowden's revelations, we are witnessing the opposite: a resurgence of interest in strengthening personal privacy.
There is no question that the field of Big Data and data analytics is growing exponentially, which in turn is leading to new challenges with respect to data privacy. At the same time, there are strong solutions that have been proposed and which are being deployed in Big Data analytics contexts. That these solutions are not widely used yet only means that we need to double our efforts to transition best practices rather than abandon ship. One solution involves the application of strong de-identification measures at the earliest opportunity to remove the harm of having personal identities linked with the data, thereby enabling extensive data analytics to be performed on non-personally identifying data. This can be done at the point of collection or the first use of the collected data. Other solutions may also be pursued in the form of encrypting personal identifiers, or aggregating datasets.
To suggest that Big Data’s entry into the world of personal data must inevitably lead to the obliteration of Fair Information Practices, which form the basis of virtually all privacy laws around the world and, which will be further strengthened in the forthcoming EU Data Protection Regulation, is sadly misguided. Yes, Big Data will lead to invaluable findings, but this need not happen at the expense of privacy. Privacy by Design rejects such dated zero-sum thinking in favour of doubly-enabling positive-sum solutions.
We must also not overlook public sentiment. To argue that the public would readily accept taking away all control of their personal information and giving it to private sector companies and to the government would be a colossal misread of the public`s views. There is no evidence that legislators and the public are prepared today to cast aside their existing privacy interests. In fact, there is growing intolerance of data breaches and privacy infractions (with specific reference to unacceptable Big Data pursuits). We need changes that will increase public trust—erosion of personal control will most likely not be one of them.
Applying the appropriate tools and methods, given the context of data collection and use, makes ultimate sense. This means that we need to have a tool box consisting of many tools. Controls at the point of collection, and controls at the point of use may be suitable at different times, and for different reasons. Both are valuable measures, but shrinking the toolbox limits the capacity of privacy professionals to address complex data analytics situations.
Our paper will argue that privacy does not impede innovation—quite the contrary, it breeds innovation and creativity! New methods will be discovered whereby the value derived from Big Data and data analytics will be achieved with privacy embedded directly into the design process. Privacy by ReDesign may also be used on existing datasets to de-identify personal identifiers before submitting the data for use in analytics.
In our upcoming paper, we will point to recent developments that are serving to strengthen Fair Information Practices and privacy interests. Not only through the Snowden revelations but also as a result of other developments such as the growth of the Personal Data Ecosystem, the determinations of the European Parliament LIBE Committee, forthcoming EU Data Protection Regulation—all of this will strengthen the resolve and pursuit of Fair Information Practices, not the reverse. Never before have so many demanded that their right to privacy, and in turn their freedoms, be respected.
There is no question that the field of Big Data and data analytics is growing exponentially, which in turn is leading to new challenges with respect to data privacy. At the same time, there are strong solutions that have been proposed and which are being deployed in Big Data analytics contexts. That these solutions are not widely used yet only means that we need to double our efforts to transition best practices rather than abandon ship. One solution involves the application of strong de-identification measures at the earliest opportunity to remove the harm of having personal identities linked with the data, thereby enabling extensive data analytics to be performed on non-personally identifying data. This can be done at the point of collection or the first use of the collected data. Other solutions may also be pursued in the form of encrypting personal identifiers, or aggregating datasets.
To suggest that Big Data’s entry into the world of personal data must inevitably lead to the obliteration of Fair Information Practices, which form the basis of virtually all privacy laws around the world and, which will be further strengthened in the forthcoming EU Data Protection Regulation, is sadly misguided. Yes, Big Data will lead to invaluable findings, but this need not happen at the expense of privacy. Privacy by Design rejects such dated zero-sum thinking in favour of doubly-enabling positive-sum solutions.
We must also not overlook public sentiment. To argue that the public would readily accept taking away all control of their personal information and giving it to private sector companies and to the government would be a colossal misread of the public`s views. There is no evidence that legislators and the public are prepared today to cast aside their existing privacy interests. In fact, there is growing intolerance of data breaches and privacy infractions (with specific reference to unacceptable Big Data pursuits). We need changes that will increase public trust—erosion of personal control will most likely not be one of them.
Applying the appropriate tools and methods, given the context of data collection and use, makes ultimate sense. This means that we need to have a tool box consisting of many tools. Controls at the point of collection, and controls at the point of use may be suitable at different times, and for different reasons. Both are valuable measures, but shrinking the toolbox limits the capacity of privacy professionals to address complex data analytics situations.
Our paper will argue that privacy does not impede innovation—quite the contrary, it breeds innovation and creativity! New methods will be discovered whereby the value derived from Big Data and data analytics will be achieved with privacy embedded directly into the design process. Privacy by ReDesign may also be used on existing datasets to de-identify personal identifiers before submitting the data for use in analytics.
In our upcoming paper, we will point to recent developments that are serving to strengthen Fair Information Practices and privacy interests. Not only through the Snowden revelations but also as a result of other developments such as the growth of the Personal Data Ecosystem, the determinations of the European Parliament LIBE Committee, forthcoming EU Data Protection Regulation—all of this will strengthen the resolve and pursuit of Fair Information Practices, not the reverse. Never before have so many demanded that their right to privacy, and in turn their freedoms, be respected.
