This book broaches the newly crafted concept of algorithmic dictatorship that draws on a plethora of human biases that creep into the algorithm and feeds into an automated decision that comes to the expense of citizens´ lives, freedoms, health, property, fair lending, and credit scoring. This book sheds a keen light on the slew of reasons in view of which artificial intelligence should be both interpretable and controllable, as opposed to merely explainable. The reason for that is straightforward: the skewed data baked into the bigoted algorithms—machine biases—spawns harrowing effects with which criminal justice has been grappling for a long-haul/drawn-out. Tallyingly, and perhaps unsurprisingly, law enforcement evinces biases that run along both gender and race lines. No surprise springs from the fact that computer-generated algorithms that propel predictive policing are often flagged as tools whereby racial discrimination abounds. It should not therefore be pegged as flabbergasting that this sort of shady algorithmic governance is a byproduct of a grueling algorithmic dictatorship that is shaping up to crumble the foundations of Rule of Law upon which stands modern societies. This is one of the key takeaways of this book. Disturbingly enough, brain–computer interfaces are poised to be converted into shady tools to collate/gauge thoughts, emotions, sentiments, and crime-related information that would be otherwise inaccessible to the governments’, rogue nations’, or unscrupulous actors’ prying eyes. Much to our dismay, an eerily dystopian world is unfolding before our very eyes. This is the gist of transhumanism—a byproduct of convolutional neural networks that revolve around deep learning genetic algorithms—that will overhaul the current legal landscape beyond recognition. This book charts the path ahead as to draw set-in-stone boundaries to prevent jurisdictions from careening into the chaos of genetic plutocracy that should be wished away.

This book broaches the newly crafted concept of algorithmic dictatorship that draws on a plethora of human biases that creep into the algorithm and feeds into an automated decision that comes to the expense of citizens´ lives, freedoms, health, property, fair lending, and credit scoring. This book sheds a keen light on the slew of reasons in view of which artificial intelligence should be both interpretable and controllable, as opposed to merely explainable. The reason for that is straightforward: the skewed data baked into the bigoted algorithms—machine biases—spawns harrowing effects with which criminal justice has been grappling for a long-haul/drawn-out. Tallyingly, and perhaps unsurprisingly, law enforcement evinces biases that run along both gender and race lines. No surprise springs from the fact that computer-generated algorithms that propel predictive policing are often flagged as tools whereby racial discrimination abounds. It should not therefore be pegged as flabbergasting that this sort of shady algorithmic governance is a byproduct of a grueling algorithmic dictatorship that is shaping up to crumble the foundations of Rule of Law upon which stands modern societies. This is one of the key takeaways of this book. Disturbingly enough, brain–computer interfaces are poised to be converted into shady tools to collate/gauge thoughts, emotions, sentiments, and crime-related information that would be otherwise inaccessible to the governments’, rogue nations’, or unscrupulous actors’ prying eyes. Much to our dismay, an eerily dystopian world is unfolding before our very eyes. This is the gist of transhumanism—a byproduct of convolutional neural networks that revolve around deep learning genetic algorithms—that will overhaul the current legal landscape beyond recognition. This book charts the path ahead as to draw set-in-stone boundaries to prevent jurisdictions from careening into the chaos of genetic plutocracy that should be wished away.

This book broaches the newly crafted concept of algorithmic dictatorship that draws on a plethora of human biases that creep into the algorithm and feeds into an automated decision that comes to the expense of citizens´ lives, freedoms, health, property, fair lending, and credit scoring. This book sheds a keen light on the slew of reasons in view of which artificial intelligence should be both interpretable and controllable, as opposed to merely explainable. The reason for that is straightforward: the skewed data baked into the bigoted algorithms—machine biases—spawns harrowing effects with which criminal justice has been grappling for a long-haul/drawn-out. Tallyingly, and perhaps unsurprisingly, law enforcement evinces biases that run along both gender and race lines. No surprise springs from the fact that computer-generated algorithms that propel predictive policing are often flagged as tools whereby racial discrimination abounds. It should not therefore be pegged as flabbergasting that this sort of shady algorithmic governance is a byproduct of a grueling algorithmic dictatorship that is shaping up to crumble the foundations of Rule of Law upon which stands modern societies. This is one of the key takeaways of this book. Disturbingly enough, brain–computer interfaces are poised to be converted into shady tools to collate/gauge thoughts, emotions, sentiments, and crime-related information that would be otherwise inaccessible to the governments’, rogue nations’, or unscrupulous actors’ prying eyes. Much to our dismay, an eerily dystopian world is unfolding before our very eyes. This is the gist of transhumanism—a byproduct of convolutional neural networks that revolve around deep learning genetic algorithms—that will overhaul the current legal landscape beyond recognition. This book charts the path ahead as to draw set-in-stone boundaries to prevent jurisdictions from careening into the chaos of genetic plutocracy that should be wished away.