A "robot" lawyer powered by artificial intelligence was set to be the first of its kind to help a defendant fight a traffic ticket in court next month. But the experiment has been scrapped after "State Bar prosecutors" threatened the man behind the company that created the chatbot with prison time. Joshua Browder, CEO of DoNotPay, on Wednesday tweeted that his company "is postponing our court case and sticking to consumer rights." Bad news: after receiving threats from State Bar prosecutors, it seems likely they will put me in jail for 6 months if I follow through with bringing a robot lawyer into a physical courtroom. Browder also said he will not be sending the company's robot lawyer to court.
A "robot" lawyer powered by artificial intelligence will be the first of its kind to help a defendant fight a traffic ticket in court next month. Joshua Browder, CEO of DoNotPay, said the company's AI-creation runs on a smartphone, listens to court arguments and formulates responses for the defendant. The AI lawyer tells the defendant what to say in real-time, through headphones. The artificial intelligence firm has already used AI-generated form letters and chatbots to help people secure refunds for in-flight Wifi that didn't work, as well as to lower bills and dispute parking tickets, among other issues, according to Browder. All told the company has relied on these AI templates to win more than 2 million customer service disputes and court cases on behalf of individuals against institutions and organizations, he added.
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AI is undergoing a paradigm shift with the rise of models (e.g., BERT, DALL-E, GPT-3) that are trained on broad data at scale and are adaptable to a wide range of downstream tasks. We call these models foundation models to underscore their critically central yet incomplete character. This report provides a thorough account of the opportunities and risks of foundation models, ranging from their capabilities (e.g., language, vision, robotics, reasoning, human interaction) and technical principles(e.g., model architectures, training procedures, data, systems, security, evaluation, theory) to their applications (e.g., law, healthcare, education) and societal impact (e.g., inequity, misuse, economic and environmental impact, legal and ethical considerations). Though foundation models are based on standard deep learning and transfer learning, their scale results in new emergent capabilities,and their effectiveness across so many tasks incentivizes homogenization. Homogenization provides powerful leverage but demands caution, as the defects of the foundation model are inherited by all the adapted models downstream. Despite the impending widespread deployment of foundation models, we currently lack a clear understanding of how they work, when they fail, and what they are even capable of due to their emergent properties. To tackle these questions, we believe much of the critical research on foundation models will require deep interdisciplinary collaboration commensurate with their fundamentally sociotechnical nature.
There is mounting public concern over the influence that AI based systems has in our society. Coalitions in all sectors are acting worldwide to resist hamful applications of AI. From indigenous people addressing the lack of reliable data, to smart city stakeholders, to students protesting the academic relationships with sex trafficker and MIT donor Jeffery Epstein, the questionable ethics and values of those heavily investing in and profiting from AI are under global scrutiny. There are biased, wrongful, and disturbing assumptions embedded in AI algorithms that could get locked in without intervention. Our best human judgment is needed to contain AI's harmful impact. Perhaps one of the greatest contributions of AI will be to make us ultimately understand how important human wisdom truly is in life on earth.
This book discusses the necessity and perhaps urgency for the regulation of algorithms on which new technologies rely; technologies that have the potential to re-shape human societies. From commerce and farming to medical care and education, it is difficult to find any aspect of our lives that will not be affected by these emerging technologies. At the same time, artificial intelligence, deep learning, machine learning, cognitive computing, blockchain, virtual reality and augmented reality, belong to the fields most likely to affect law and, in particular, administrative law. The book examines universally applicable patterns in administrative decisions and judicial rulings. First, similarities and divergence in behavior among the different cases are identified by analyzing parameters ranging from geographical location and administrative decisions to judicial reasoning and legal basis. As it turns out, in several of the cases presented, sources of general law, such as competition or labor law, are invoked as a legal basis, due to the lack of current specialized legislation. This book also investigates the role and significance of national and indeed supranational regulatory bodies for advanced algorithms and considers ENISA, an EU agency that focuses on network and information security, as an interesting candidate for a European regulator of advanced algorithms. Lastly, it discusses the involvement of representative institutions in algorithmic regulation.
When Arnold Schwarzenegger's "Terminator" character said "I'll be back," this probably wasn't what he had in mind. The actor and former governor of California is suing a robotics company for $10 million, after the business decided to use his name and likeness. Schwarzenegger's lawsuit against the tech startup, called Promobot, alleges that the robot lookalike... "diminishes his hard-earned and well-deserved reputation as a major motion picture star," according to TMZ. The robot isn't just meant to look like Schwarzenegger, it also has his name. Promobot advertises the creation on its site as a "companion robot," one of several that emulates the appearance of world-famous celebrities.
The creator of the hugely popular video game Fortnite has urged a judge to throw out a lawsuit by the rapper 2 Milly, who claims a viral dance move he created was used in the game without his consent. According to defence lawyers for Epic Games, the musician's dance moves are not subject to copyright laws because "no one can own a dance step." The lawsuit centres around the'Swipe It' dance emote that can be obtained as a reward in the online Battle Royale game. Plaintiff Terrence Milly, who goes by the name 2 Milly, argues that the dance move is based on a choreography he created in 2014 called the Milly Rock. Epic Games' lawyers claimed in the motion to the Californian Judge that "individual dance steps and simple dance routines are not protected by copyright," though copyright experts believe there is a strong counter argument to this claim.
RAVN Systems, leading experts in Artificial Intelligence, Search and Knowledge Management solutions, announced today the launch of a RAVN ACE powered Robot for LPP (Legal Professional Privilege) review, allowing clients to automate the review of determining if material is subject to LPP. The LPP Robot uses state of the art AI (Artificial Intelligence) techniques to automatically read through vast document collections, such as case material in litigation, as well as other document types, to determine whether individual items are subject to LPP. The accuracy levels achieved by the Robot making these determinations now surpass traditional manual efforts and is several orders of magnitude faster. The solution exploits supervised iterative Machine Learning models inside the RAVN ACE (Applied Cognitive Engine) platform, meaning the Robot will become more accurate over time. It is a technological leap from legacy predictive coding methods that sometimes are used today.