Harnessing big data to 'better regulate' on-line decision-making

Previous regulatory models for the online environment have been designed with a foundation and premise that users are fictional Homo Economicus – beings capable of optimizing all available information into order to make sound decisions. Sometime these decisions will be rational and predictable. However, on other occasions users will make irrational, yet predictable mistakes; other times those errors will be unpredictably irrational. To overcome these shortcomings in rational economist models, behavioural economists like Daniel Kahneman, Amos Tversky and Richard Thaler and lawyers like Cass Sunstein have advocated using lessons from psychology to help people make better decisions. By deploying 'choice’ architecture to overcome less than rational decisions, Homo Sapiens can be 'nudged' to making better choices. Building from this foundation, our paper inquires what role big data may play in developing better regulation. For example, can insights from big data help to overcome erroneous assumptions that regulators may make about the way users rationally behave in online environments? What potential is there for harnessing ‘big data’ to provide insights into user behaviour? Can big data be used as an additional tool by lawmakers to improve regulatory settlements?