Question

Data governance involves the supervision, monitoring, and control of an organization’s data assets. Its main concerns are data quality, appropriateness, and cost effectiveness of the controls. It is difficult because organizations typically have a lot of old data, which is of unknown quality. Imagine that you must collect and assess the quality and appropriateness of data held by a large, multinational organization. What steps you would take? Include how you would address network, security, and ethical considerations when deciding what data to collect from the company. Explain the kinds of support you’ll need and how you will obtain resources and cooperation. This is not a job you can do on your own!

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Answer 1

From my perspective, we believe that any organizational conversation about big data ethics should relate to four basic principles that can lead to the establishment of big data norms:

1. Privacy is not dead; it is just another word for information rules. Private does not always mean secret. Ensuring privacy of data is a matter of defining and enforcing information rules and not just rules about data collection, but about data use and retention. People should have the ability to manage the flow of their private information across massive, third-party analytical systems.

2. Shared private information can still remain confidential. It is not realistic to think of information as secret or shared, completely public or completely private. For many reasons, some of them quite good, data is shared or generated by design with services we trust through address books, pictures, GPS, cell tower, and Wi-Fi location tracking of our cell phones. But just because we share and generate information, it does not follow that anything goes, whether we are talking medical data, financial data, address book data, location data, reading data, or anything else.

3. Big data requires transparency. Big data is powerful when secondary uses of data sets produce new predictions and inferences. Of course, this leads to data being a business, with people such as data brokers, collecting massive amounts of data about us, often without our knowledge or consent, and shared in ways that we do not want or expect. For big data to work in ethical terms, the data owners, or the people whose data we are handling, need to have transparent viewsof how our data is being used, or sold.

4. Big Data can compromise identity. Privacy protections are not enough anymore. Big data analytics can compromise identity by allowing institutional surveillance to moderate and even determine who we are before we make up our own minds. We need to begin to think about the kind of big data predictions and inferences that we will allow, and the ones that we should not.

Explain the kinds of support you’ll need and how you will obtain resources and cooperation.

There is a great deal of work to do in translating these principles into laws and rules that will result in ethical handling of Big Data. And there is certainly more principles we need to develop as we build more powerful tech tools. But anyone involved in handling big data should have a voice in the ethical discussion about the way we exploit Big Data. Developers and database administrators are on the front lines of the whole issue. The law is a powerful element of Big Data Ethics, but it is far from able to handle the many use cases and nuanced scenarios that arise. Organizational principles, institutional statements of ethics, self-policing, and other forms of ethical guidance must be exploited. Technology itself can help provide an important element of the ethical mix as well. This could take the form of intelligent data use trackers that can tell us how our data is being used and let us make the decision about whether or not we want our data used in analysis that takes place beyond our spheres of awareness and control. We also need clear default rules for what kinds of processing of personal data is allowed, and what kinds of decisions based upon this data are acceptable when they affect the lives of people. But the important point is this, we need a big data ethics, and software developers need to be at the center of these critical ethical discussions. Big data ethics, as we argue in real life scenarios, are for everyone.