Big Data is producing increased powers of institutional awareness and power that require the development of Big Data Ethics. The Facebook acquisition of WhatsApp shows just how high the stakes can be as huge amounts of data is available.
The scale and ease with which data collection can all be done today changes the ethical framework of data analysis. Developers today can tap into remarkably varied and far-flung data sources.
Big Data revolution raises a bunch of ethical issues related to privacy, confidentiality, transparency and identity.
The problem is that people’s ability to reveal patterns and new knowledge from previously unexamined troves of data is moving faster than current legal and ethical guidelines can manage.
Big data capabilities risk abandoning these values for the sake of innovation and expediency.
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.
Ensuring privacy of data is a matter of defining and enforcing information rules 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.
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 users, often without our knowledge or consent. For big data to work in ethical terms, the data owners /social media companies need to have a transparent view of how user data is being used or sold.
There’s a great deal of work to do in translating these principles into laws and rules that will result in ethical handling of Big Data. Along with strict laws Organizational principles, institutional statements of ethics, self-policing, and other forms of ethical guidance are also needed.