Ensuring compliance with international data protection standards for privacy and data security is a crucial but complex task, often requiring substantial legal expertise. This paper introduces LegiLM, a novel legal language model specifically tailored for consulting on data or information compliance. LegiLM leverages a pre-trained GDPR Fines dataset and has been fine-tuned to automatically assess whether particular actions or events breach data security and privacy regulations. By incorporating a specialized dataset that includes global data protection laws, meticulously annotated policy documents, and relevant privacy policies, LegiLM is optimized for addressing data compliance challenges. The model integrates advanced legal reasoning methods and information retrieval enhancements to enhance accuracy and reliability in practical legal consulting scenarios. Our evaluation using a custom benchmark dataset demonstrates that LegiLM excels in detecting data regulation breaches, offering sound legal justifications, and recommending necessary compliance modifications, setting a new benchmark for AI-driven legal compliance solutions. Our resources are publicly available at https://github.com/DAOLegalAI/LegiLM

Since its implementation in May 2018, the General Data Protection Regulation (GDPR) has prompted businesses to revisit and revise their data handling practices to ensure compliance. The privacy policy, which serves as the primary means of informing users about their privacy rights and the data practices of companies, has been significantly updated by numerous businesses post-GDPR implementation. However, many privacy policies remain packed with technical jargon, lengthy explanations, and vague descriptions of data practices and user rights. This makes it a challenging task for users and regulatory authorities to manually verify the GDPR compliance of these privacy policies. In this study, we aim to address the challenge of compliance analysis between GDPR (Article 13) and privacy policies for 5G networks. We manually collected privacy policies from almost 70 different 5G MNOs, and we utilized an automated BERT-based model for classification. We show that an encouraging 51$\%$ of companies demonstrate a strong adherence to GDPR. In addition, we present the first study that provides current empirical evidence on the readability of privacy policies for 5G network. we adopted readability analysis toolset that incorporates various established readability metrics. The findings empirically show that the readability of the majority of current privacy policies remains a significant challenge. Hence, 5G providers need to invest considerable effort into revising these documents to enhance both their utility and the overall user experience.

Oracle's digital assistant is now available in Microsoft Teams, the cloud hosting and services provider announced today. Oracle's AI assistant got several other updates today, including the ability to interact via voice commands, enterprise-grade security for voice recordings, and the ability to respond to more complex voice commands. The news was announced today at Oracle's OpenWorld conference in San Francisco. As part of the Microsoft Teams integration, Microsoft Teams and Office 365 users will be able to access Oracle enterprise bots from the Microsoft Teams App Store. "For enterprise customers, what we're enabling [them] to do now is they can easily try to use Microsoft Teams to collaborate with their employees and colleagues and so forth with Microsoft Teams," Oracle VP of AI and digital assistant Suhas Uliyar told VentureBeat in a phone interview.

Oracle's digital assistant is now available in Microsoft Teams, the cloud hosting and services provider announced today. Oracle's AI assistant got several other updates today, including the ability to interact via voice commands, enterprise-grade security for voice recordings, and the ability to respond to more complex voice commands. The news was announced today at Oracle's OpenWorld conference in San Francisco. As part of the Microsoft Teams integration, Microsoft Teams and Office 365 users will be able to access Oracle enterprise bots from the Microsoft Teams App Store. "For enterprise customers, what we're enabling to do now is [that] they can easily try to use Microsoft Teams to collaborate with their employees and colleagues and so forth with Microsoft Teams," Oracle VP of AI and digital assistant Suhas Uliyar told VentureBeat in a phone interview.

The rapid progress in artificial intelligence, smart devices, and smart cities promises to revolutionise the way we work, live, and connect. However, recent scandals surrounding the handling of user data have prompted a wave of privacy concerns. The smarter a city gets, the more it can keep tabs on our every move. Likewise, with connected home devices and digital assistants picking up our daily activities and queries, the potential for privacy breaches are endless. Europe's pioneering General Data Privacy Regulation (GDPR) is one of several attempts by governments to mitigate widespread shortfalls in customer data protection, for both companies and governments. Other countries, and even US states like California, have followed.

Privacy advocates have placed an unfair stigma on machine learning. Despite what you may have heard through the mass media, ML is not some fiendish tool for invading people's privacy. Regardless, now that European Union's General Data Protection Regulation has taken effect, there's an even stronger scrutiny of ML applications in target marketing, customer engagement, experience optimization and other use cases that touch personally identifiable information, or PII. But in fact, ML is becoming a key element in how organizations manage compliance with GDPR and other privacy mandates. The core of ML's role in GDPR compliance is in its use as a tool for discovering, organizing, curating and controlling enterprise PII assets across complex, distributed application environments.

A lot has been said, and much has been discussed about the upcoming effects of GDPR – like how the organization is collecting the data and in what other ways they are making use of the data, and many more discussions are ongoing. Amongst these, all machine learning has become a key player and has gained traction amongst prominent role across organizations, and a key question is emerging and mystifying amongst regulators, researchers and lawyers alike; How will the GDPR impact on machine learning applications? If you are actively living on this planet, then I am pretty sure that you must have heard about the Facebook and Cambridge Analytica Scandal and Mark's statement on Facebook is making in response to European Union's GDPR – General Data Protection Regulation. If you do not belong to Europe, then you would have heard the statement from U.S. Senator Brain Schatz that all the technology partners, as well as platforms, will adopt the EU approach for data protection. GDPR is indeed a big deal, and since it has become a law in the European Union, it has undeniably improved the data protection for EU citizens and the people around the world.

What a huge advance it is that the financial sector now has robots to relieve the ever-growing pressure of regulation. Almost everyone handling or processing personal data now faces vastly increased compliance requirements once the European Union's General Data Protection Regulation (GDPR) comes into force in May. The new rules cover the personally identifiable data of any European Union or British citizen and are very prescriptive, with penalties for infringement that could amount to four per cent of global revenue. Small wonder, then, that Fortune 500 organisations are reported to have spent $7.8 billion on GDPR so far. For the financial sector the challenges of GDPR come on top of the plethora of Know Your Customer (KYC) and Anti-Money Laundering regulations.

The basis of GDPR is the privacy of data for citizens and consumers of EU countries and the methods needed to track and enforce GDPR will need to have intelligent methods to process the large amount of data that will need to be sorted to identify GDPR compliance or non-compliance. According to Dr. Shane Archiquette, CTO – Global Communications, Media & Entertainment, Global Markets and Technology Architecture, AI-assisted auditing will most likely be the method used to look for patterns across multiple disparate datasets that businesses will need to produce and process. In addition, AI will provide a composable method to machine-learn new areas that are identified by GDPR legal precedence as new cases are opened and closed. According to a recent report, European Union Institute researchers created AI-enabled software to scrutinize the privacy policies of 14 major technology companies for violations of the new GDPR. They found that 1/3 rd of the clauses contained "insufficient information," with 11% of the policies' sentences using "unclear language."

Unless you've been hiding under a rock, you've probably heard of the Cambridge Analytica Scandal and Mark Zuckerberg's statements about the worldwide changes Facebook is making in response to European Union's General Data Protection Regulation (GDPR). If your business is not yet in Europe, you may be taken aback by the statement from U.S. Senator Brian Schatz that "all tech platforms ought to adopt the EU approach to (data protection)." This, despite the fact that 45% of U.S. citizens think that there is already "too much" government regulation of business and industry. So yes, GDPR is a big deal indeed. When it became the law in European Union on May 25, 2018, it improved data protection for EU citizens dealing with companies not only in Europe but all around the world.