I enjoyed the definition of Big Data by Kitchin that seems to be the community standard in which Big Data is different from other data because of terms like volume, velocity, variety, exhaustive, resolute, indexical, relational, flexible, and scalable amongst others that the Wikipedia blog also included. To me Big Data is data that shares the above italicized traits in which traditional computer processors and memory can not compute. Non-traditional would require AI/ML computation to deal with the abundance, exhaustivity and variety, timeliness and dynamism, messiness and uncertainty, and high relationality that is Big Data. My question for this, does the concept of Big Data involuntarily mean the use of AI/ML with the Data acquired? I know Kitchin characterizes Big Data as opposed to Data by being generated continuously, seeking to be exhaustive and fine-grained in scope, and flexible and scalable in its production, in doing so does that mean that Big Data we know today really only emerged from innovations in AI/ML? I believe the answer is yes, but would like confirmation.

Furthermore, Big Data is a relatively new phenomenon under the above definition because it is a result of two enabling changes in society that Denning argued. First, the expansion of the internet into a billion computing devices i.e. the Internet of Things that enables access to vast amounts of data. Second, the digitization of almost everything resulting in an explosion of innovation of network-based big data applications and automation of cognitive tasks. As a result, the emergence of Big Data from societal change is spurring more societal change. “Revolutions in science have often been preceded by revolutions in measurement,” – Sinan Aral. Science is only one thing that Big Data has changed, Kitchin argues that Big Data will move scientific approaches to a data-driven science method blending aspects of abduction, induction, and deduction the “born from data” rather than theory method. In society, Big Data is spurring changes in social networks and content providers ability to attract and hold consumers attention in the digital economy (Huberman). In government, Big Data can be a tool to enable surveillance and monitoring at unprecedented levels (Johnson). In education, Big Data is enabling the creation of different methods of learning and instructions through creation of personalized paths based on data analytics on users’ interactions with existing educational courses (Opening Statemen). The applications of big data touches nearly every aspect of our society though are there certain parts of our society that like cloud computing should not utilize Big Data?

Big Data is important because data is viewed as a prized resource that can optimize efficiency and profits for organizations or enable surveillance and security by governments. This and the relative newness of this technology has lent to a wild west in terms of lack of regulations and limits in the collection of data, the encroachment on consumer’s privacy and security rights, and the lack of transparency in models. So, I will echo a similar question made in the closing statement of the ACM Ubiquity, do regulatory initiatives even have the support to confront the ethical challenges in Big Data?