Here's a curious question: Imagine it is the year 2023 and self-driving cars are finally navigating our city streets. For the first time one of them has hit and killed a pedestrian, with huge media coverage. A high-profile lawsuit is likely, but what laws should apply? Today, we get an answer of sorts thanks to the work of John Kingston at the University of Brighton in the UK, who maps out the landscape in this incipient legal field. His analysis raises some important issues that the automotive, computing, and legal worlds should be wrestling with in earnest, if they are not already.

Artificial intelligence is going to make legal work faster and more efficient, but it needs help from lawyers and legal professionals to do so. As a Research Director in Thomson Reuters Research and Development group, I work firsthand with technologies like machine learning, natural language processing and artificial intelligence (AI). Since we work on creating solutions for customers, I also meet many intelligent and experienced legal professionals. I'm often asked whether the technologies we work on – particularly AI – are going to send these professionals to the same part of history books as milkmen and stenographers. To allay any remaining concern, expanding on that short answer may be helpful.

Building an operating system for data is the foundation needed for any industry today. These could range from a health care organization crafting a strategy to comply with General Data Protection Regulation (GDPR) and Health Insurance Portability and Accountability Act (HIPAA) policies, to an airline using artificial intelligence (AI) to pinpoint maintenance issues sooner and get passengers to their destinations on time. As we move further into the new year, companies may need to harness greater amounts of their data for competition and innovation. This will not only help to solve the challenges surrounding dark data and upcoming data regulations but will also open the door to uncovering new ways to innovate with data and AI. As more organizations take hold of their data with cloud technology, we can expect these five trends to continue to change the way we view the potential of cloud and AI in 2018.

I have written a few times about the unusual nature of robocar accidents. Recently I was discussing this with a former student who is doing some research on the area. As a first step, she began looking at lists of all the reasons that humans cause accidents. This led me, though to the following declaration that goes against most early intuitions. Every human accident teaches us something about the way people have accidents.

Critics, however, see it as an effort to blunt outside regulation by cities, states or the federal government, and they question if tech companies are best suited to shape the rules of the road. For the corporations, the algorithms will be proprietary tools to assess your loan-worthiness, your job application, and your risk of stroke. Many balk at the costs of developing systems that not only learn to make decisions, but that also explain those decisions to outsiders. When New York City proposed a law in August requiring that companies publish source code for algorithms used by city agencies, tech firms pushed back, saying they needed to protect proprietary algorithms. The city passed a scaled-back version in December without the source-code requirement.

Does GDPR require Machine Learning algorithms to explain their output? Probably not, but experts disagree and there is enough ambiguity to keep lawyers busy. Starting May 25, the European Union will require algorithms to explain their output, making deep learning illegal.--

A business runs on diligence, passion, and creativity -- but it also needs a whole lot of legal help. Regardless of your industry, your startup needs legal assistance to ensure its growth remains safe and secure. You need lawyers to help you with incorporation and IP creation. You also need lawyers to help you write contracts for clients and staff. However, what you don't need is lawyers' prohibitive fees, which can cost your startup hundreds of thousands of dollars -- even millions -- in just the first few years.

Have you ever booked a flight or hotel and then noticed that the prices drop after you've shelled out? A computerised legal tool has expanded its offerings in a bid to help travellers recuperate losses like this on holiday bookings. DoNotPay - masterminded by Stanford University tech whizz Joshua Browder - uses a'robot lawyer' to find legal loopholes and negotiate cheaper prices or re-book reservations for customers if prices lower after they've paid. DoNotPay - masterminded by Stanford University tech whizz Joshua Browder - uses a'robot lawyer' to find legal loopholes and negotiate cheaper prices or re-book travel reservations for customers if prices lower after they've paid Once a customer signs up, the sophisticated bot automatically looks for all the travel confirmations in the user's email inbox and checks for fluctuations in price about 17,000 times a day until the departure date. If the flight or hotel price drops, DoNotPay claims it would bag the better deal and make the vendor refund the difference.

In the latest breakthrough claim for artificial intelligence in law, a firm today announced what it says is the first successful test of predictive coding for document review in a full High Court trial. International firm Berwin Leighton Paisner (BLP) said it had achieved a successful outcome after a 12-day hearing in David Brown v BCA Trading Limited, in which relevant document were identified with predictive coding. Predictive coding is a machine-learning technique, which involves identifying documents with an algorithm which learns by iteration, dramatically cutting the cost of e-disclosure. In May 2016 BLP obtained a court order overruling the opposing party's opposition to the technology in the case. BLP was representing BCA Marketplace in an unfair prejudice claim brought by a minority shareholder in a business BCA had acquired.

When it comes to artificial intelligence, a lot of attention has been focused on issues of privacy and economics – what happens if AI makes human workers obsolete. Now, a new report from the non-profit Environmental Law Institute highlights the potential environmental impacts of AI-driven technologies, from autonomous cars to smart thermostats. Lead author Dave Rejeski says that whether those impacts are positive or negative will depend on how the technology is built and used, and the time to start thinking about that is now. The PyeongChang Olympics are likely to be remembered for the joint Korean team, wind delays, and robots. South Korea is taking advantage of the international spotlight to show off its leadership in robotics, with eleven different types of robots – eighty five, in all – in action at the Olympics.