Up until recently, any debate between proponents and opponents of High Frequency Trading would typically be represented by heated debates of high conviction on either side, with discussions rapidly deteriorating into ad hominem attacks and the producer screaming 'cut to commercial' to prevent fistfights. Luckily, all this is about to change. In a research paper by Reginald Smith of the Bouchet Franklin Institute in Rochester titled "Is high-frequency trading inducing changes in market microstructure and dynamics?" the author finds that he "can clearly demonstrate that HFT is having an increasingly large impact on the microstructure of equity trading dynamics. Traded value, and by extension trading volume, fluctuations are starting to show self-similarity at increasingly shorter timescales. Values which were once only present on the orders of several hours or days are now commonplace in the timescale of seconds or minutes. It is important that the trading algorithms of HFT traders, as well as those who seek to understand, improve, or regulate HFT realize that the overall structure of trading is influenced in a measurable manner by HFT and that Gaussian noise models of short term trading volume fluctuations likely are increasingly inapplicable." In other words, the author finds ample evidence that during the past decade (on the NASDAQ) and especially since the 2005 revision of Reg NMS (on the NYSE), stock trading increasingly demonstrates "self similar" fractal patterns, resulting in volatility surges, recursive feedback loops, and a market structure which is increasingly becoming a product of the actual trading mechanism. In the process, as demonstrated by a Hurst Exponent gravitating increasingly further away from 0.5 (i.e., Brown Noise territory), the Markov Process nature of stock trading is put under question, and thus the whole premise of an efficient market has to be reevaluated. Simply said: HFT has been shown to affect the fairness of trading.