As the bitter and dirty race for the American presidency draws to a close, it's time to highlight the only candidate who has put bioethics at the front and centre of his campaign. His program is pretty simple: to overcome death and ageing within 15 years. A Tranhshumanist Bill of Rights for "Human beings, sentient artificial intelligences, cyborgs, and other advanced sapient life forms" commits government to working for indefinite life spans, morphological freedom and an end to involuntary suffering and ageing. Some people have questioned the practicality of eliminating death, because of the resulting population explosion. However, Zoltan's response is that "mind-uploading will be here in 50 years, so people might actually remain alive but in machines, making population levels easy to deal with." He has a few other ideas as well, such as surrendering the job of being president to artificial intelligence.

When Tesla announced recently that it would make "full self-driving capability" available on new S and X models for a mere $3,000 extra, optimists hailed the development as a watershed moment for consumer technology. But embedded in the press release was a little-noted catch: While customers may use the self-driving feature to pick up friends or family members, "doing so for revenue purposes will only be permissible on the Tesla Network, details of which will be released next year." If you want to earn some extra money -- perhaps to help pay off your robot car's $75,000 price tag -- by selling rides to strangers, you won't be allowed to use Uber or Lyft. On its face, this demand may seem ridiculous. For over a century, buying a car meant that as soon as you left the lot, you could drive it wherever and however you liked as long as you obeyed traffic laws.

Let's face it: the pace of progress in artificial intelligence can sometimes seem unsettling. Terminator-style machines remain science fiction, but AI could have a huge impact on employment, introduce bias into algorithms, and contribute to the development of autonomous weapons. But perhaps the biggest looming threat may be making sure we understand how these increasingly complex systems work when they go awry. The latest evidence that even the experts are concerned about this is the creation of a new AI ethics research center at Carnegie Mellon University. The new center, called K&L Gates Endowment for Ethics and Computational Technologies, is funded with $10 million from K&L Gates, an international law firm based in Pittsburgh.

"Loving" is an unpretentious film about unassuming real people, but don't let that mislead you. Just as Richard and Mildred Loving ended up overturning the status quo and making American legal history, so this feature on their lives by writer-director Jeff Nichols turns out to be a film of quiet but quite significant strengths. Nichols, responsible for "Mud," "Take Shelter" and the underappreciated humanistic science fiction epic "Midnight Special," has gone in a different, more historical direction here. He's made an involving socially conscious drama about the interracial couple whose marriage, illegal in their home state of Virginia, led to the unanimous 1967 Supreme Court ruling that racist anti-miscegenation laws were unconstitutional. But "Loving" is hardly a legal drama rife with attorney strategies and courtroom scenes.

Let's face it: the pace of progress in artificial intelligence can sometimes seem unsettling. Terminator-style machines remain science fiction, but AI could have a huge impact on employment, introduce bias into algorithms, and contribute to the development of autonomous weapons. But perhaps the biggest looming threat may be making sure we understand how these increasingly complex systems work when they go awry. The latest evidence that even the experts are concerned is the creation of a new AI ethics research center at Carnegie Mellon University. The new center, called K&L Gates Endowment for Ethics and Computational Technologies, is funded with $10 million from K&L Gates, an international law firm based in Pittsburgh.

Technology (the invention of steel) changed lives during the Industrial revolution, but it wasn't until mass production of the automobile nearly 100 years later that lives changed that much again. That's nearly a century for everyone to get used to change, and for legislation to catch up… just think: child labor laws didn't pass until after the turn of the 20th century, well over 100 years past the start of the Industrial Revolution.

An artificial intelligence method developed by University College London computer scientists and associates has predicted the judicial decisions of the European Court of Human Rights (ECtHR) with 79% accuracy, according to a paper published Monday, Oct. 24 in PeerJ Computer Science. The method is the first to predict the outcomes of a major international court by automatically analyzing case text using a machine-learning algorithm.* "We don't see AI replacing judges or lawyers," said Nikolaos Aletras, who led the study at UCL Computer Science, "but we think they'd find it useful for rapidly identifying patterns in cases that lead to certain outcomes. It could also be a valuable tool for highlighting which cases are most likely to be violations of the European Convention on Human Rights." In developing the method, the team found that judgments by the ECtHR are highly correlated to non-legal (real-world) facts, rather than direct legal arguments, suggesting that judges of the Court are, in the jargon of legal theory, "realists" rather than "formalists."

For the study, published in PeerJ Computer Science, researchers set a machine-learning algorithm loose on 584 cases and found that the AI could learn to predict the rulings in those cases with a relatively high percentage of accuracy. But if you're getting really excited about working with computer-lawyer-physic software in the future, well, there are a few caveats. Those 584 cases were all from the European Court of Human Rights and the analysis was based on published judgments. The program was learning to guess outcomes in a narrow class of cases, after they had already been decided. Still, the research is interesting.

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Summary: Deep learning and Big Data are being adopted in law enforcement and criminal justice at an unprecedented rate. Does this scare you or make you feel safe? When you read the title, whether your mind immediately went for the upstairs "H" or the downstairs "H" probably says something about whether the new applications of Big Data in law enforcement let you sleep like a baby or keep you up at night. You might have thought your choice of "H" related to whether you've been on the receiving end of Big Data in law enforcement but the fact is that practically all of us have, and for those who haven't it won't take much longer to reach you. There is an absolute explosion in the use of Big Data and predictive analytics in our legal system today driven by the latest innovations in data science and by some obvious applications.