Big data, ethics & regulation and the future
Michael Irene is a data and information governance practitioner based in London, United Kingdom. He is also a Fellow of Higher Education Academy, UK, and can be reached via email@example.com; twitter: @moshoke
March 15, 2021726 views0 comments
From all indications and numerous researches, businesses will rely heavily on the use of big data. Companies want to know their customers deeply. They want to suggest items to them and serve them better. Enter big data.
Richard Herschel and Virginia Miori, in their paper titled, Ethics and Big Data, argue that the use of big data raises fundamental issues in data privacy and at the same time gives companies the opportunity to make information. They further opine that businesses that would last in this age, need to learn how to be ethical about how they use big data.
If the future relies on collecting data on such a massive scale, how can we now embed ethics? What should the equation look like?
I believe a typical model for businesses should be simple. First, businesses must propound ethical solutions for their big data collection schemes. What do I mean here?
Big firms that must rapidly capture, analyse, and exploit information, must have defined policies that guide their processing of this data. At the minimum, the companies should remain transparent about how they use these data. A bank, for example, that wants to further process a particular data for the purpose of delivering certain types of services must have a scheme in place to inform their customers.
Brent Daniel Mittelstadt and Luciano Floridi in their paper, The Ethics of Big Data: Current and Foreseeable Issues in Biomedical Contexts, highlight other ethical approaches firms can use when collecting data. Informed consent is first on the list. Here, again, it asks whether the firms have a way to seek consent from individuals whose data they have in their possession.
Another approach is the idea of anonymising data. In some way, the anonymisation process requires that identifiers be removed, substituted, distorted, generalised or aggregated. By doing this, companies go further in protecting any personal information or sensitive personal information seeping out recklessly from their data processing schemas.
From experience, most IT stakeholders generally think that ethics would stifle the growth of innovation. But I would argue that reverse is the case. Once a company understands the importance of building robust information management systems within their company structures, they can quickly create products that can be trusted and free of any significant privacy issues.
A firm that pays attention to global data protection principles would understand how they marry ethics and big data together. The principles of minimisation, fairness and security are ethical concerns in the end-to-end lifecycle processing of big data.
Ethics, therefore, is the foundation on which businesses must leap. In today’s ever-evolving data ecosystem, it is evident that companies that wish to advance both structurally and improve profitability must ensure they look for the best approach to collect massive data for the business’ benefit and customers’ benefit.
As I write this article, I have Mathias Fischer’s book, Fintech Business Models: Applied Canvas Method and Analysis of Venture Capital Rounds, lying on my desk. It is a fantastic book that extrapolates the future of banking models and various radical business models that would shake the foundation of existing traditional business. In it, one notices that the future belongs to those businesses that can harness data to improve their services and the development of new products.
One caveat remains. Only those firms that can build an ethical foundation would benefit from this new future.