Litigation

In the future, is it conceivable that a firm would be charged with legal malpractice if they didn't use artificial intelligence (AI)? Today, artificial intelligence offers a solution to solve or at least make the access-to-justice issue better and completely transform our traditional legal system. Here's what you need to know about how AI, big data, and online courts will change the legal system. When I sat down in conversation with Richard Susskind, OBE, the world's most-cited author on the future of legal services, to discuss the future of law and lawyers, it became apparent just how much change the legal system will face over the next decade thanks to innovation brought about by artificial intelligence and big data. In Richard's book The Future of Law, published in 1996, he predicted that in the future, lawyers and clients would communicate via email.

Nearly a decade after co-founding Cyberjustice Laboratory, a unique hub that analyses the impact of technologies on justice while developing concrete technological tools that are adapted to the reality of justice systems, Karim Benyekhlef and Fabien Gélinas have set their sights on artificial intelligence. The Autonomy through Cyberjustice Technologies (ACT), the latest brainchild of the Cyberjustice Laboratory, is the largest international multidisciplinary research initiative that seeks to leverage artificial intelligence to increase access to justice while providing justice stakeholders with a roadmap to help them develop technology that is better adapted to justice. "The main objective behind the initiative is to ensure that individuals know their rights, understand their legal situation regarding their problems and improve access to justice – and AI may help accomplish those goals," said Benyekhlef, the head of Cyberjustice Laboratory and a law professor at the Université de Montréal. "There's a good chance that our reflections and work on areas such as privacy, data management, data governance could easily be used in other realms such as in public administration. But we must be careful. We cannot play the sorcerer's apprentice. These are tools that are not yet mature. There's work to be done."

Inspired by "predictive coding" - a theory in neuroscience, we develop a bi-directional and dynamic neural network with local recurrent processing, namely predictive coding network (PCN). Unlike feedforward-only convolutional neural networks, PCN includes both feedback connections, which carry top-down predictions, and feedforward connections, which carry bottom-up errors of prediction. Feedback and feedforward connections enable adjacent layers to interact locally and recurrently to refine representations towards minimization of layer-wise prediction errors. When unfolded over time, the recurrent processing gives rise to an increasingly deeper hierarchy of non-linear transformation, allowing a shallow network to dynamically extend itself into an arbitrarily deep network. Despite notably fewer layers and parameters, PCN achieves competitive performance compared to classical and state-of-the-art models.

Google is at CES this week touting all the different partners it has to bring the personal Assistant to speakers, smart displays, phones and the like. One partner is popping mad - wireless speaker pioneer Sonos. The Santa Barbara, California maker of speakers that can be added to home systems for improved sound without that last-century accessory, speaker wire, filed two complaints against Google Tuesday, and called for an immediate cease-and-desist order. If granted, it would mean Google would have to stop selling the Google and Nest Home speakers, Pixel phones and laptops. That was the cease-and-desist request sought by Sonos in a complaint filed with the International Trade Commission, along with a separate patent violation lawsuit in federal court in California.

Based on our interactions and the results of this study, we expect to see organizations not only adopt AI – but scale it across their enterprises, by building/developing their own AI, or putting ready-made AI applications to work. For example, according to the survey, 40% of respondents currently deploying AI said they are developing proof-of-concepts for specific AI-based or AI-assisted projects, and 40% are using pre-built AI applications, such as chatbots and virtual agents. I see the excitement building with clients every day. Consider just a couple of recent examples. Legal software developer LegalMation has leveraged IBM Watson and our natural language processing technology to help attorneys automate some of the most mundane litigation tasks, speeding, for example, the written discovery process from multiple hours to a few minutes.

Security cameras made by the Chinese tech company Xiaomi are being shut out by Google after evidence of a serious security flaw. According to Android Police, Google revoked Xiaomi's ability to integrate with its Home app or Google Assistant after some devices started to mysteriously stream video feed from strangers' cameras. The decision comes just a day after one Reddit user demonstrated the concerning flaw in a video. Pictures posted by a Reddit user show how other users' cameras mysteriously showed up in a feed being streamed to a Google Hub smart display. The video feeds ranged from random interiors of homes and potentially businesses.

Sonasoft delivers value-added AI–driven solutions targeting larger enterprises. We combine deep expertise in Data Engineering, Big Data Analytics and AI consulting. All of this is underpinned by NuGene, the world's first autonomous cognitive AI platform. Sonasoft is a publicly traded company since 2014. Your data is your most valuable resource.

As more businesses realize the benefits of artificial intelligence (AI) in their daily operations, the demand for use cases will increase and drive the AI market. The leaps forward in AI will continue, as we see this young technology blossom into wider and more advanced uses. In 2020, companies will keep an eye on proven AI use cases that can help their businesses--they should speed ROI and minimize risk. Look for 2020 to be a year of AI expansion into businesses and out of the proof-of-concept labs. Here are seven leading use-case trends I see for AI in 2020.

Artificial Intelligence (A.I.) is changing the landscape of the practice of law. From e-Discovery to A.I. contract software, A.I. is impacting legal practices. A.I. is now capable of a more involved role in litigation, such as: Some law firms have been slow to adapt to the advantages that A.I. brings. The fear that they are replacing the work of attorneys is unfounded. A.I. helps reduce the amount of tedious and redundant work once done by those in the legal field.

What is the law but a series of algorithms? Codified instructions proscribing dos and don'ts--ifs and thens. Sounds a lot like computer programming, right? The legal system, on the other hand, is not as straightforward as coding. Just consider the complicated state of justice today, whether it be problems stemming from backlogged courts, overburdened public defenders, and swathes of defendants disproportionately accused of crimes.