Judgment prediction for legal cases has attracted much research efforts for its practice use, of which the ultimate goal is prison term prediction. While existing work merely predicts the total prison term, in reality a defendant is often charged with multiple crimes. In this paper, we argue that charge-based prison term prediction (CPTP) not only better fits realistic needs, but also makes the total prison term prediction more accurate and interpretable. We collect the first large-scale structured data for CPTP and evaluate several competitive baselines. Based on the observation that fine-grained feature selection is the key to achieving good performance, we propose the Deep Gating Network (DGN) for charge-specific feature selection and aggregation. Experiments show that DGN achieves the state-of-the-art performance.

Authentic AI is much more than just text analytics. NexLP's Story Engine leverages predictive coding, combined with next-generation Natural Language Processing, cognitive analytics and dataless classification to turn disparate, unstructured data into meaningful insight that can save time, money, and unnecessary risk. As the leader in legal and compliance AI, our breakthrough tools and technology use adaptive AI, behavioral analysis and AI Model Libraries to focus on the context around the data, not just what the words are saying.

Barrister and human rights advocate Fiona McLeod, who delivered the Solomon Lecture titled Accountability in the age of the artificial, said accountability was under threat in Australia and internationally. Ms McLeod called for a robust national integrity commission. "We have settled for a'trust us or vote us out' model of democracy and a veneer of transparency resulting in a piecemeal and un-strategic approach to accountability," she said. "For example, the federal government committed to bring in a Commonwealth integrity commission after its hand was forced by independents in the last Parliament. "The original preferred model of a closed hearings, with no power of the commission to initiate inquiries, appeared to me more like a benign hall monitor issuing'don't run' notices than a body capable of balancing competing public and private interests, of driving a culture of anti-corruption throughout government, private organisations and the community."

In 1951, Marvin Minsky asked an imaginary mouse to navigate an imaginary maze. Together with Dean Edmonds, Marvin carefully connected three hundred vacuum tubes together with an assembly of motors and light bulbs, applying ideas about the wiring of neurons in human and animal brains. Minsky and Edmonds watched the virtual mouse's progress on a bank of lights and offered rewards when it moved toward its goal. Through repeated tries, the mouse learned to escape the maze. When researchers coined the term "artificial intelligence" (AI) five years later, they hoped to prove in one summer that every feature of learning and intelligence could be conducted by a machine.

We aren't alone in trying to move responsible AI from discussion to action while the technology is still in its infancy. The European Commission High-Level Expert Group on Artificial Intelligence and Singapore Personal Data Protection Commission also have independent initiatives underway. And the Montreal Declaration for Responsible Development of Artificial Intelligence and various industry-led or regional ethical AI projects are also addressing the issue. These are additional resources for associations willing to use their influence to ignite broad stakeholder adoption. Through conferences and education, associations can offer safe forums for thoughtful debate and practical planning around the fundamental choices we make for responsible AI. Associations stand at a tipping point of AI disruption. Industry and government stakeholders are looking for sensible guideposts for responsible conduct. Will you help define, model, and adopt responsible AI?

The chief executive is headed to an artificial intelligence conference in Shanghai that kicks off on Thursday where he's set to face-off with Alibaba founder Jack Ma in what Bloomberg reports to be a "free-wheeling debate." "Conference-goers can look forward to featured speakers shedding light on the status quo of the industry and the potential impacts of artificial intelligence," a press release distributed by conference organizers says. Both leaders have been outspoken in their views on AI. Musk, who counts an AI company among his diverse portfolio of bets, has stressed the dangers of the nascent technology. "I'm really quite close, very close to the cutting edge in AI. It scares the hell out of me," Musk said at SXSW in 2018.

Recruiters beware and be prepared. New laws have recently come into effect policing the use of artificial intelligence (AI) in video interviewing. Here's how they could affect your recruiting efforts. Technology helps recruiters collect, organize and store enormous amounts of information about job applicants all over the world. Workflow automation, the cloud and search functionalities are just some examples of software that make recruiters' lives easier. But, artificial intelligence (AI) has long been a gray zone in HR, dangerously toeing the line between reality and an imperfect, artificial world.

Artificial Intelligence (AI) is an increasingly valuable tool for diagnostics and drug development and is being used to make medical devices more adaptive. However, the U.S. Supreme Court's 2014 decision in Alice has made it difficult to patent inventions involving AI, seeing as the court's derived test for Section 101 of the Patent Act prevents abstract ideas from being patented. Interestingly enough, the court's decision failed to define what an abstract idea is, resulting in Section 101 often being applied unevenly. Nimalka Wickramasekera, an Intellectual Property litigator and Los Angeles partner, discusses in BioWorld's article "Supreme Court's Alice Decision Leaves Drug, Device Firms in AI Wonderland" that Section 101 proves to be a big hurdle for evolving technology, and AI specifically, "since people are still wrapping their heads around what they're claiming as the invention." She added that she "wouldn't be surprised if every patent application based on AI has had at least one rejection at the USPTO…To get around the court's prohibition on patents for abstract ideas, AI inventors must go beyond the algorithm and its application in computing devices."

What is your view of the risks of facial recognition technology and its impact on civil liberties? There is a clear divergence of opinion in this area. The largest tensions, perhaps, sit between those who consider that this is a necessary exception to privacy, at least for law enforcement versus those who consider the technology sits far too far on the side of invasiveness, even where it will improve efficiencies and accuracies around law enforcement. That debate is stronger in certain countries. I envisage there will be continuing tensions – justification and/or legitimate interest will be important.

Reach out if you want to talk about digital & AI ethics in your organization-- Email: e-bruce@manydoors.net If you work for an organization that uses data--and just about all organizations do, or will before long--even if your job isn't specifically about data, your ability to make decisions using data, and decision about data, is becoming more and more important. An important subset of these decisions that involves everyone--decisionmakers, employees, and customers alike--falls under the general category of digital ethics, which can encompass how data is collected, stored, used, and shared. To illustrate, lets look at two examples of digital ethics in action, one surprisingly successful, and one disastrous. My friend Aaron Reich is basically the futurist in residence at Avanade, the global technology consulting firm. From the vantage point of his high level insight into many of their consulting projects, last year he called out a few examples where companies achieved remarkable improvement in ways that they can help their customers using data and artificial intelligence.