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Abstract: Big data brings forth a number of exciting prospects and solutions - for example in healthcare, transport, and controversially state security - but legitimate concerns, both private and public, remain due to the amount of information collected. Through speed of development and smart marketing, apps) become in-vogue, and have the ability to capture vast amounts of user data short periods of time. This is aided by poor attention given to privacy policies, along with concepts like the third party doctrine in the US, causing those volunteering personal data to third parties to have 'no reasonable expectation of privacy'. After algorithms are applied, the data becomes valuable and can be sold to a wide variety of buyers. There are two issues here. Firstly, volume takes preference over accuracy, which when used by insurance and credit companies, or state bodies, there is a potential for discrimination. The second issue is that the above commercial uses may lead to a struggle between intellectual property and privacy rights, and this paper uses the adoption of big data in sports to show how legal precedent may inform social norms in this area. Another problematic field is state surveillance. Data collection en-masse by bodies like GCHQ and the NSA (a form of 'rear window ethics' where surveillance is ubiquitous) utilises bottom-up knowledge discovery. In other words, rather than agents testing hypotheses, these emerge from the information independently. The sheer volume of data collected has the potential to obscure the true hazards, thus actually threatening security. The push for backdoor encryption to increase surveillance data collection also does so by opening up vulnerabilities. As Bruce Schneier has pointed out, cyber-attackers currently have the advantage online, meaning that anything weakening defences should be avoided. This paper argues for a more targeted surveillance bearing in mind that as mass data collection continues, it becomes normalised and we are subject to a feedback loop whereby as long as attacks do not happen, it is assumed to be the answer. This is despite a distinct lack of transparency as to the true effects. The above issues are explored in turn in this paper, to demonstrate that implementation of big data strategies should not be taken lightly due to the threat of entrenching undesirable...