Contract Management Machine Learning

  contract management machine learning: Innovative and Agile Contracting for Digital Transformation and Industry 4.0 Shalan, Mohammad Ali, Algarni, Mohammed Ayedh, 2020-12-18 Digital transformation is reshaping the business arena as new, successful digital business models are increasing agility and presenting better ways to handle business than the traditional alternatives. Industry 4.0 affects everything in our daily lives and is blurring the line between the physical, the biological, and the digital. This created an environment where technology and humans are so closely integrated that it is impacting every activity within the organizations. Specifically, contracting processes and procedures are challenged to align with the new business dynamics as traditional contracts are no longer fitting today's agile and continuously changing environments. Businesses are required to facilitate faster, more secure, soft, and real-time transactions while protecting stakeholders’ rights and obligations. This includes agile contracts which are dynamically handling scope changes, smart contracts that can automate rule-based functions, friction-less contracts that can facilitate different activities, and opportunity contracts that looks toward the future. Innovative and Agile Contracting for Digital Transformation and Industry 4.0 analyzes the consequences, benefits, and possible scenarios of contract transformation under the pressure of new technologies and business dynamics in modern times. The chapters cover the problems, issues, complications, strategies, governance, and risks related to the development and enforcement of digital transformation contracting practices. While highlighting topics in the area of digital transformation and contracting such as artificial intelligence, digital business, emerging technologies, and blockchain, this book is ideally intended for business, engineering, and technology practitioners and policy makers, along with practitioners, stakeholders, researchers, academicians, and students interested in understanding the scope, complexity, and importance of innovative contracts and agile contracting.
  contract management machine learning: Contracting and Contract Law in the Age of Artificial Intelligence Martin Ebers, Cristina Poncibò, Mimi Zou, 2022-06-30 This book provides original, diverse, and timely insights into the nature, scope, and implications of Artificial Intelligence (AI), especially machine learning and natural language processing, in relation to contracting practices and contract law. The chapters feature unique, critical, and in-depth analysis of a range of topical issues, including how the use of AI in contracting affects key principles of contract law (from formation to remedies), the implications for autonomy, consent, and information asymmetries in contracting, and how AI is shaping contracting practices and the laws relating to specific types of contracts and sectors. The contributors represent an interdisciplinary team of lawyers, computer scientists, economists, political scientists, and linguists from academia, legal practice, policy, and the technology sector. The chapters not only engage with salient theories from different disciplines, but also examine current and potential real-world applications and implications of AI in contracting and explore feasible legal, policy, and technological responses to address the challenges presented by AI in this field. The book covers major common and civil law jurisdictions, including the EU, Italy, Germany, UK, US, and China. It should be read by anyone interested in the complex and fast-evolving relationship between AI, contract law, and related areas of law such as business, commercial, consumer, competition, and data protection laws.
  contract management machine learning: Contract Management Alain Brunet, Franck César, 2021-07-30 This book presents the latest findings relating to behavioral economics and the digital tools applied to contract management. There has been a decisive change in the role of contracts in the past decade, with contracts being transformed from purely legal necessities designed to protect against worst-case scenarios into tools for optimizing ongoing and mutually profitable business relationships with customers. There is an increasing emphasis on tight contracts, where time-risk and additional costs are passed on to the prime contractor, who may suffer heavy penalties in the event of non-performance. Contracts shape the behavior of the parties involved and as such have a major impact on project success. The contract manager’s goals are to protect the interests of the company and its shareholders by minimizing the company’s financial and contractual liabilities and to maximize its profitability while ensuring end-user satisfaction. The contract is usually written before the design is fully developed, and there is often a mismatch between contractual specifications and what the customer actually wants. Good contract management entails preserving the rights of the contractor by ensuring all parties respect their contractual obligations; providing advice to the project managers and engineering team; preparing profitable amendments to contracts or change requests; maintaining good record-keeping in the event that claims arise; filing notices when necessary; and guiding the project to a profitable conclusion. Like the ancient Chinese game of Go, moves made early in the game (notification of events) can shape the nature of a potential conflict one hundred moves later (arbitration threat). Contract management can also smooth the relationship between partners, allowing well-balanced “don’t-trade-a-dollar-for-a-penny” contracts to be managed through an established process rather than as sporadic events (we cannot claim to be in control of our business if we are not in control of the contracts on which it depends). Managing a contract with a mix of incomplete manuals, fragmented information, and poor planning can drive companies to “reinvent the wheel.” Contract management promotes a three-phase sequence to streamline information flows across the contract lifecycle, from the bid phase to performance, project closeout, and final payments.
  contract management machine learning: Modern Approaches in Machine Learning and Cognitive Science: A Walkthrough Vinit Kumar Gunjan, Jacek M. Zurada, 2021-04-26 This book provides a systematic and comprehensive overview of machine learning with cognitive science methods and technologies which have played an important role at the core of practical solutions for a wide scope of tasks between handheld apps, industrial process control, autonomous vehicles, environmental policies, life sciences, playing computer games, computational theory, and engineering development. The chapters in this book focus on readers interested in machine learning, cognitive and neuro-inspired computational systems – theories, mechanisms, and architecture, which underline human and animal behaviour, and their application to conscious and intelligent systems. In the current version, it focuses on the successful implementation and step-by-step explanation of practical applications of the domain. It also offers a wide range of inspiring and interesting cutting-edge contributions to applications of machine learning and cognitive science such as healthcare products, medical electronics, and gaming. Overall, this book provides valuable information on effective, cutting-edge techniques and approaches for students, researchers, practitioners, and academicians working in the field of AI, neural network, machine learning, and cognitive science. Furthermore, the purpose of this book is to address the interests of a broad spectrum of practitioners, students, and researchers, who are interested in applying machine learning and cognitive science methods in their respective domains.
  contract management machine learning: AI and Machine Learning Impacts in Intelligent Supply Chain Pandey, Binay Kumar, Kanike, Uday Kumar, George, A. Shaji, Pandey, Digvijay, 2024-01-29 Businesses are facing an unprecedented challenge - the urgent need to adapt and thrive in a world where intelligent factories and supply chains are the new norm. The digital transformation of supply chains is essential for staying competitive, but it is a complex journey fraught with uncertainties. How can organizations harness the power of emerging technologies like Artificial Intelligence (AI) and Machine Learning (ML) to increase profitability, cut supply chain costs, elevate customer service, and optimize their networks? The answers to these questions are crucial for business survival and success. AI and Machine Learning Impacts in Intelligent Supply Chain is a groundbreaking book that offers a comprehensive solution to the challenges posed by the Industry 4.0 revolution. This book is your indispensable guide to navigating the intricate world of supply chain digital transformation using innovative technologies. It provides real-world examples and insights that illustrate how AI and ML are the keys to solving complex supply chain problems, from inventory management to route optimization and beyond. Whether you are an academic scholar seeking to delve into the impact of AI and ML on supply chain management or a business leader striving to gain a competitive edge, this book is tailored to meet your needs.
  contract management machine learning: Utilization of AI Technology in Supply Chain Management Pandey, Digvijay, Pandey, Binay Kumar, Kanike, Uday Kumar, George, A. Shaji, Kaur, Prabjot, 2024-03-01 The surge in digital transformation and the integration of innovative technologies into manufacturing processes have given rise to a pressing issue in supply chain management. Businesses are in dire need of solutions to navigate this complexity and harness the true potential of intelligent supply chains. Utilization of AI Technology in Supply Chain Management is a comprehensive guide tailored for academic scholars seeking to unravel the mysteries of artificial intelligence (AI) and machine learning (ML) in the context of supply chain management. Amid the hype surrounding AI and ML, there exists a critical need to bridge the gap between human expertise and technological advancements. Utilization of AI Technology in Supply Chain Management addresses this necessity by delving into real-world instances where teams have successfully employed these innovative technologies to enhance supply chain performance, reduce inventory, and optimize routes. The adoption of AI and ML is not just a trend; it is the cornerstone of digital acceleration initiatives, making it imperative for scholars to understand and leverage these technologies effectively.
  contract management machine learning: AI For Lawyers Noah Waisberg, Alexander Hudek, 2021-02-03 Discover how artificial intelligence can improve how your organization practices law with this compelling resource from the creators of one of the world’s leading legal AI platforms. AI for Lawyers: How Artificial Intelligence is Adding Value, Amplifying Expertise, and Transforming Careers explains how artificial intelligence can be used to revolutionize your organization’s operations. Noah Waisberg and Dr. Alexander Hudek, a lawyer and a computer science Ph.D. who lead prominent legal AI business Kira Systems, have written an approachable and insightful book that will help you transform how your firm functions. AI for Lawyers explains how artificial intelligence can help your law firm: Win more business and find more clients Better meet and exceed client expectations Find hidden efficiencies Better manage and eliminate risk Increase associate and partner engagement Whether focusing on small or big law, AI for Lawyers is perfect for any lawyer who either feels uneasy about how AI might change law or is looking to capitalize on the evolving practice. With contributions from experts in the fields of e-Discovery, legal research, expert systems, and litigation analytics, it also belongs on the bookshelf of anyone who’s interested in the intersection of law and technology.
  contract management machine learning: Machine Learning for Algorithmic Trading Stefan Jansen, 2020-07-31 Leverage machine learning to design and back-test automated trading strategies for real-world markets using pandas, TA-Lib, scikit-learn, LightGBM, SpaCy, Gensim, TensorFlow 2, Zipline, backtrader, Alphalens, and pyfolio. Purchase of the print or Kindle book includes a free eBook in the PDF format. Key FeaturesDesign, train, and evaluate machine learning algorithms that underpin automated trading strategiesCreate a research and strategy development process to apply predictive modeling to trading decisionsLeverage NLP and deep learning to extract tradeable signals from market and alternative dataBook Description The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This revised and expanded second edition enables you to build and evaluate sophisticated supervised, unsupervised, and reinforcement learning models. This book introduces end-to-end machine learning for the trading workflow, from the idea and feature engineering to model optimization, strategy design, and backtesting. It illustrates this by using examples ranging from linear models and tree-based ensembles to deep-learning techniques from cutting edge research. This edition shows how to work with market, fundamental, and alternative data, such as tick data, minute and daily bars, SEC filings, earnings call transcripts, financial news, or satellite images to generate tradeable signals. It illustrates how to engineer financial features or alpha factors that enable an ML model to predict returns from price data for US and international stocks and ETFs. It also shows how to assess the signal content of new features using Alphalens and SHAP values and includes a new appendix with over one hundred alpha factor examples. By the end, you will be proficient in translating ML model predictions into a trading strategy that operates at daily or intraday horizons, and in evaluating its performance. What you will learnLeverage market, fundamental, and alternative text and image dataResearch and evaluate alpha factors using statistics, Alphalens, and SHAP valuesImplement machine learning techniques to solve investment and trading problemsBacktest and evaluate trading strategies based on machine learning using Zipline and BacktraderOptimize portfolio risk and performance analysis using pandas, NumPy, and pyfolioCreate a pairs trading strategy based on cointegration for US equities and ETFsTrain a gradient boosting model to predict intraday returns using AlgoSeek's high-quality trades and quotes dataWho this book is for If you are a data analyst, data scientist, Python developer, investment analyst, or portfolio manager interested in getting hands-on machine learning knowledge for trading, this book is for you. This book is for you if you want to learn how to extract value from a diverse set of data sources using machine learning to design your own systematic trading strategies. Some understanding of Python and machine learning techniques is required.
  contract management machine learning: Contract management in project management and service management - the CATS RVM® methodology Linda Tonkes, Richard Steketee, 2024-01-10 This book describes the CATS RVM methodology that proposes realization and verification management as a way to establish the relationship between contract management and project and service management. The CATS RVM methodology can be applied within public and private organizations, by and for clients and suppliers. Realization and verification management is the realization of the objectives intended with the contract. It does this by proactively realizing and verifying the performance stipulated in the contract during the execution phase of a contract, managing all risks associated with the performance, setting up all delivery processes, coordinating applicable delivery management processes between client and supplier, and preparing for these activities prior to the execution phase. CATS RVM offers a methodical approach to managing contracts in project and service management. It describes the basic principles, the roles, the points of attention for the realization and verification manager in the domains of delivery management and contract management, and the recommended way of working. In addition to a description of the methodology, this book also provides a description of the most common delivery management processes in both service and project management. The CATS RVM methodology is aligned with the best practice contract management methodology CATS CM as described in the book CATS CM® version 4: From working on contracts to contracts that work. However, it can be read completely independently. Where relevant, parts of CATS CM are also described in this book. This book is suitable for anyone involved with purchase and/or sales contracts in the provision of services, products or projects. This includes project managers, service managers, facility managers, those responsible for a technical service, and those responsible for the provision of HR services. This book also contains much useful information for those who work in adjacent domains such as contract management, procurement, sales, risk management, or compliance, and anyone who is responsible for contracts in a more tactical or strategic role.
  contract management machine learning: Valley of Genius Adam Fisher, 2014-11-04 This is the most important book on Silicon Valley I've read in two decades. It will take us all back to our roots in the counterculture, and will remind us of the true nature of the innovation process, before we tried to tame it with slogans and buzzwords. -- Po Bronson, #1 New York Times bestselling author of The Nudist on the Late Shift and Nurtureshock A candid, colorful, and comprehensive oral history that reveals the secrets of Silicon Valley -- from the origins of Apple and Atari to the present day clashes of Google and Facebook, and all the start-ups and disruptions that happened along the way. Rarely has one economy asserted itself as swiftly--and as aggressively--as the entity we now know as Silicon Valley. Built with a seemingly permanent culture of reinvention, Silicon Valley does not fight change; it embraces it, and now powers the American economy and global innovation. So how did this omnipotent and ever-morphing place come to be? It was not by planning. It was, like many an empire before it, part luck, part timing, and part ambition. And part pure, unbridled genius... Drawing on over two hundred in-depth interviews, Valley of Genius takes readers from the dawn of the personal computer and the internet, through the heyday of the web, up to the very moment when our current technological reality was invented. It interweaves accounts of invention and betrayal, overnight success and underground exploits, to tell the story of Silicon Valley like it has never been told before. Read it to discover the stories that Valley insiders tell each other: the tall tales that are all, improbably, true.
  contract management machine learning: Machine Learning and Cryptographic Solutions for Data Protection and Network Security Ruth, J. Anitha, Mahesh, Vijayalakshmi G. V., Visalakshi, P., Uma, R., Meenakshi, A., 2024-05-31 In the relentless battle against escalating cyber threats, data security faces a critical challenge – the need for innovative solutions to fortify encryption and decryption processes. The increasing frequency and complexity of cyber-attacks demand a dynamic approach, and this is where the intersection of cryptography and machine learning emerges as a powerful ally. As hackers become more adept at exploiting vulnerabilities, the book stands as a beacon of insight, addressing the urgent need to leverage machine learning techniques in cryptography. Machine Learning and Cryptographic Solutions for Data Protection and Network Security unveil the intricate relationship between data security and machine learning and provide a roadmap for implementing these cutting-edge techniques in the field. The book equips specialists, academics, and students in cryptography, machine learning, and network security with the tools to enhance encryption and decryption procedures by offering theoretical frameworks and the latest empirical research findings. Its pages unfold a narrative of collaboration and cross-pollination of ideas, showcasing how machine learning can be harnessed to sift through vast datasets, identify network weak points, and predict future cyber threats.
  contract management machine learning: Fun with Machine Learning Arockia Liborious, Dr. Rik Das, 2023-03-23 Learn how to use AutoML to leverage Machine Learning for solving business problems KEY FEATURES ● Get familiar with the common machine learning problems and understand how to solve them. ● Understand the importance of different types of data and how to work with them effectively. ● Learn how to use machine learning and AutoML tools to solve real-world problems. DESCRIPTION “Fun with Machine Learning” is an essential guide for anyone looking to learn about machine learning and how it can be used to make informed business decisions. The book covers the basics of machine learning, providing an overview of key concepts and terminology. To fully understand machine learning, it is important to have a basic understanding of statistics and mathematics. The book provides a simple introduction to these topics, making it easy for you to understand the core concepts. One of the key features of the book is its focus on AutoML tools. It introduces you to different AutoML tools and explains how to use them to simplify the data science processes. The book also shows how machine learning can be used to solve real-world business problems, such as predicting customer churn, detecting fraud, and optimizing marketing campaigns. By the end of the book, you will be able to transform raw data into actionable insights with machine learning. WHAT YOU WILL LEARN ● Get a clear understanding of what machine learning is and how it works. ● Learn how to perform regression analysis using Orange. ● Understand how to implement classification In machine learning. ● Get to know more about the clustering and association algorithms. ● Analyze, visualize, manipulate, and forecast time series data with Orange. WHO THIS BOOK IS FOR This book is for Machine Learning engineers, Machine Learning enthusiasts, Data Scientists, beginners, and students who are looking to implement machine learning techniques to solve real-life business problems. It is also a great resource for business leaders who are responsible for making data-driven decisions. TABLE OF CONTENTS 1. Significance of Machine Learning in Today’s Business 2. Know Your Data 3. Up and Running With Analytical Tools 4. Machine Learning in a Nutshell 5. Regression Analysis 6. Classification 7. Clustering and Association 8. Time Series Forecasting 9. Image Analysis 10. Tips and Tricks
  contract management machine learning: Digital Development of the European Union David Ramiro Troitiño, Tanel Kerikmäe, Ondrej Hamuľák, 2023-06-20 This edited volume analyses the digital development of the European Union, presenting an interdisciplinary perspective from the disciplines of political science, international relations, economics, and law. The contributions address the main areas where the EU can, and should act, for creating an efficient and protective digital space in Europe. The book highlights the responsibility of the European Union to work on the future of its digital development, looking for prosperity and defending the European conception of society. It explains how European values must be incorporated into the digital revolution and shows how the digital revolution of the EU will defend the Europeans from new threats. The book's comprehensive approach allows the reader to understand this process without in-depth knowledge of the specific discipline. Therefore, it is a must-read for everybody interested in a better understanding of digital development, European Union policy, and the future of Europe.
  contract management machine learning: Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance El Bachir Boukherouaa, Mr. Ghiath Shabsigh, Khaled AlAjmi, Jose Deodoro, Aquiles Farias, Ebru S Iskender, Mr. Alin T Mirestean, Rangachary Ravikumar, 2021-10-22 This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.
  contract management machine learning: Artificial Intelligence in Business Management Teik Toe Teoh, Yu Jin Goh, 2023-11-26 Artificial intelligence (AI) is rapidly gaining significance in the business world. With more and more organizations adopt AI technologies, there is a growing demand for business leaders, managers, and practitioners who can harness AI’s potential to improve operations, increase efficiency, and drive innovation. This book aims to help management professionals exploit the predictive powers of AI and demonstrate to AI practitioners how to apply their expertise in fundamental business operations. It showcases how AI technology innovations can enhance various aspects of business management, such as business strategy, finance, and marketing. Readers interested in AI for business management will find several topics of particular interest, including how AI can improve decision-making in business strategy, streamline operational processes, and enhance customer satisfaction. As AI becomes an increasingly important tool in the business world, this book offers valuable insights into how it can be applied to various industries and business settings. Through this book, readers will gain a better understanding of how AI can be applied to improve business management practices and practical guidance on how to implement AI projects in a business context. This book also provides practical guides on how to implement AI projects in a business context using Python programming. By reading this book, readers will be better equipped to make informed decisions about how to leverage AI for business success.
  contract management machine learning: Artificial Intelligence Kerrigan, Charles, 2022-03-17 This timely book provides an extensive overview and analysis of the law and regulation as it applies to the technology and uses of Artificial Intelligence (AI). It examines the human and ethical concerns associated with the technology, the history of AI and AI in commercial contexts.
  contract management machine learning: A Legal Theory for Autonomous Artificial Agents Samir Chopra, Laurence F. White, 2011-07-28 “An extraordinarily good synthesis from an amazing range of philosophical, legal, and technological sources . . . the book will appeal to legal academics and students, lawyers involved in e-commerce and cyberspace legal issues, technologists, moral philosophers, and intelligent lay readers interested in high tech issues, privacy, [and] robotics.” —Kevin Ashley, University of Pittsburgh School of Law As corporations and government agencies replace human employees with online customer service and automated phone systems, we become accustomed to doing business with nonhuman agents. If artificial intelligence (AI) technology advances as today’s leading researchers predict, these agents may soon function with such limited human input that they appear to act independently. When they achieve that level of autonomy, what legal status should they have? Samir Chopra and Laurence F. White present a carefully reasoned discussion of how existing philosophy and legal theory can accommodate increasingly sophisticated AI technology. Arguing for the legal personhood of an artificial agent, the authors discuss what it means to say it has “knowledge” and the ability to make a decision. They consider key questions such as who must take responsibility for an agent’s actions, whom the agent serves, and whether it could face a conflict of interest.
  contract management machine learning: Machine Learning with Dynamics 365 and Power Platform Aurelien Clere, Vinnie Bansal, 2022-01-06 Apply cutting-edge AI techniques to your Dynamics 365 environment to create new solutions to old business problems In Machine Learning with Dynamics 365 and Power Platform: The Ultimate Guide to Apply Predictive Analytics, an accomplished team of digital and data analytics experts delivers a practical and comprehensive discussion of how to integrate AI Builder with Dataverse and Dynamics 365 to create real-world business solutions. It also walks you through how to build powerful machine learning models using Azure Data Lake, Databricks, Azure Synapse Analytics. The book is filled with clear explanations, visualizations, and working examples that get you up and running in your development of supervised, unsupervised, and reinforcement learning techniques using Microsoft machine learning tools and technologies. These strategies will transform your business verticals, reducing costs and manual processes in finance and operations, retail, telecommunications, and manufacturing industries. The authors demonstrate: What machine learning is all about and how it can be applied to your organization's Dynamics 365 and Power Platform Projects The creation and management of environments for development, testing, and production of a machine learning project How adopting machine learning techniques will redefine the future of your ERP/CRM system Perfect for Technical Consultants, software developers, and solution architects, Machine Learning with Dynamics 365 and Power Platform is also an indispensable guide for Chief Technology Officers seeking an intuitive resource for how to implement machine learning in modern business applications to solve real-world problems.
  contract management machine learning: The Cambridge Handbook of the Law of Algorithms Woodrow Barfield, 2020-11-05 Algorithms are a fundamental building block of artificial intelligence - and, increasingly, society - but our legal institutions have largely failed to recognize or respond to this reality. The Cambridge Handbook of the Law of Algorithms, which features contributions from US, EU, and Asian legal scholars, discusses the specific challenges algorithms pose not only to current law, but also - as algorithms replace people as decision makers - to the foundations of society itself. The work includes wide coverage of the law as it relates to algorithms, with chapters analyzing how human biases have crept into algorithmic decision-making about who receives housing or credit, the length of sentences for defendants convicted of crimes, and many other decisions that impact constitutionally protected groups. Other issues covered in the work include the impact of algorithms on the law of free speech, intellectual property, and commercial and human rights law.
  contract management machine learning: Insights, Strategies, and Applications of Business Analytics A. Arun Kumar, 2024-03-06 This book is a transformative guide catering to undergraduate and graduate students and research scholars, providing a comprehensive understanding of critical concepts in modern analytics. In today’s fast-paced business landscape, data utilization is paramount for success. This book delves into tools and techniques facilitating the conversion of raw data into actionable insights, covering descriptive, predictive, and prescriptive analytics. Beginning with foundational principles, it ensures accessibility for readers of all backgrounds. Real-world case studies seamlessly woven throughout the text illustrate successful business analytics implementations, showcasing how organizations make strategic decisions. This precise and insightful guide equips readers with the knowledge to optimize processes, making it an indispensable resource for navigating the dynamic realm of business analytics.
  contract management machine learning: Smart Legal Contracts Jason Allen, Peter Hunn, 2022-04-04 Smart Legal Contracts: Computable Law in Theory and Practice is a landmark investigation into one of the most important trends at the interface of law and technology: the effort to harness emerging digital technologies to change the way that parties form and perform contracts. While developments in distributed ledger technology have brought the topic of 'smart contracts' into the mainstream of legal attention, this volume takes a broader approach to ask how computers can be used in the contracting process. This book assesses how contractual promises are expressed in software and how code-based artefacts can be incorporated within more conventional legal structures. With incisive contributions from members of the judiciary, legal scholars, practitioners, and computer scientists, this book sets out to frame the borders of an emerging area of law and start a more productive dialogue between the various disciplines involved in the evolution of contracts as software. It provides the first step towards a more disciplined approach to computational contracts that avoids the techno-legal ambiguities of 'smart contracts' and reveals an emerging taxonomy of approaches to encoding contracts in whole or in part. Conceived and written during a time when major legal systems began to engage with the advent of contracts in computable form, and aimed at a fundamental level of enquiry, this collection will provide essential insight into future trends and will provide a point of orientation for future scholarship and innovation.
  contract management machine learning: AI in Legal Matters: Revolutionizing Justice and Law DIZZY DAVIDSON, 2024-08-01 Struggling to fully understand the impact of AI on the legal system? Are you curious about how AI is revolutionizing justice and law? Wondering how AI can enhance legal research, contract management, and crime prevention? Look no further! “AI in Legal Matters: Revolutionizing Justice and Law” is your comprehensive guide to understanding the transformative power of AI in the legal field. This book delves into the myriad ways AI is reshaping legal practices, from predictive analytics to document automation, and from fraud detection to crime prevention. Benefits of Reading This Book: Gain Insight: Understand how AI tools streamline legal research and due diligence. Enhance Efficiency: Learn how AI automates contract analysis and document creation. Predict Outcomes: Discover how predictive analytics can forecast case results. Improve Security: Explore AI applications in fraud detection and crime prevention. Access Justice: See how AI-driven chatbots and virtual assistants provide legal advice. This book is a must-read for legal professionals, tech enthusiasts, and anyone interested in the future of law. It provides practical insights and real-world examples of AI applications in legal matters, making complex concepts accessible and engaging. Why This Book is Essential: Comprehensive Coverage: Covers all major AI applications in the legal field. Practical Examples: Includes case studies and success stories. Expert Insights: Written by experts in AI and law. Future-Oriented: Discusses emerging trends and technologies. Bullet Points Streamline Legal Research: Discover AI tools that make legal research faster and more accurate. Automate Contracts: Learn how AI can manage and analyze contracts efficiently. Predict Case Outcomes: Understand the power of predictive analytics in legal decisions. Detect Fraud: Explore AI systems that identify fraudulent activities. Enhance Security: See how AI predicts and prevents crime. Access Legal Advice: Utilize AI-driven chatbots for quick legal assistance. Reduce Bias: Learn about AI tools that promote fairness in legal proceedings. Future Trends: Stay updated on the latest AI technologies in law. Call to Action: Get your copy of “AI in Legal Matters: Revolutionizing Justice and Law” today and unlock the benefits of AI in the legal field. Become knowledgeable about AI and stay ahead in the rapidly evolving world of legal technology.
  contract management machine learning: Legalese Decoded Kalpana Muthireddi, 2021-05-14 A useful guide covering important information and best practices to understand legal concepts in business ~ Manupatra Have you ever had to deal with legal documents or contracts and couldn’t get them off your hands soon enough? Not sure if you can sign off on that investor agreement? Maybe words like “GDPR compliance,” “outsourcing contracts,” or “re-negotiations” make you feel strangely queasy. This book demystifies and puts into perspective those legal terms and obligations you encounter as a corporate executive or entrepreneur and decisions that could have potential legal consequences. If you are a young lawyer new to the corporate world, this book will help you make sense of the business aspects of your job. If you have ever been in a business meeting, wishing for more clarity on those legal terms, but hesitated to ask for fear of being misunderstood; or if the very idea of discussing legal concepts bores you to tears, then this book is for you. It is a handbook filled with tips to handle issues that do not require profound legal erudition, but a well-thought-out action that could prevent legal issues. It will help you recognize potential red flags, prevent easily avoidable mistakes, and realize when you are out of depth. For more information, log on to www.legalesedecoded.com
  contract management machine learning: SAP Sudipta Malakar, 2019-09-19 Phases of SAP Activate Methodology DESCRIPTION The book promises to make you understand and practise the SAP Activate Framework. The focus is to take you on a journey of all the phases of SAP Activate methodology and make you understand all the phases with real life examples, lessons learnt, accelerators and best practices. Well articulation on how SAP Activate methodology can be used through real-world use cases, with a comprehensive discussion on Agile and Scrum, in the context of SAP Project. Ê SAP Activate is an innovative, next generation business suite that allows producing working deliverables straight away. SAP Activate Methodology is a harmonized agile implementation approach for cloud, on premise, and hybrid deployments for delivering shippable product increments in an iterative and incremental way. KEY FEATURES 400 PLUS Real-time SAP Activate & SAP S/4 HANA Interview questions and answers Numerous Tricky Real-time SAP Activate Case Studies and Demos SAP S/4 HANAÑApproach & Guidelines Explore the application scenarios of SAP Activate SAP Activate issues and challenges in large-, mid- and small-scale projects and mitigation plan Digital transformation tips and tricks Intelligent enterprise tips and tricks Integration of SAP S/4HANA with machine learning intelligence. WHAT WILL YOU LEARN You will get familiar with SAP S4HANA which is an incredibly innovative platform for businesses that can store business data, interpret it, analyze it, process it in real time, and use it when it is needed depending upon the business requirement. This book articulates integration of SAP S/4HANA with machine learning intelligence, intelligent enterprise tips & tricks, SAP Geographical Enablement Framework, Agricultural Contract Management, SAP Activate issues and challenges in large-, mid- and small-scale projects and mitigation plan, Fit/Gap Workshops, Master Data Management, Vendor-Managed Inventory, useful Tips & Tricks for successful implementation of any Greenfield or brownfield, use of Agile, Scrum, Kanban, XP in SAP S/4 HANA Project and contains 400 PLUS Real-time SAP Activate & SAP S/4 HANA Interview questions and answers. WHO THIS BOOK IS FOR SAP Consultants, SAP technical, business analysts, architects, team leads, project Leads, project managers, account manager, account executives, CEO, CTO, COO, CIO, Sr. VP, and Directors. Table of Contents 1. SAP Activate Methodology - Introduction 2. Journey New Implementation (In Cloud) 3. Journey New Implementation (On-Premise) 4. Journey System Conversion for SAP S/4 HANAÊ 5. Journey Landscape Transformation for SAP S/4 HANAÊ 6. Activate Methodology and SAP Activate Ð Top 410 Plus 7. SAP S/4 HANA and SAP Activate Ð Test your knowledge 8. SAP S/4 HANA and SAP Activate Ð Key Takeaways
  contract management machine learning: The Cambridge Handbook of Private Law and Artificial Intelligence Ernest Lim, Phillip Morgan, 2024-03-28 AI appears to disrupt key private law doctrines, and threatens to undermine some of the principal rights protected by private law. The social changes prompted by AI may also generate significant new challenges for private law. It is thus likely that AI will lead to new developments in private law. This Cambridge Handbook is the first dedicated treatment of the interface between AI and private law, and the challenges that AI poses for private law. This Handbook brings together a global team of private law experts and computer scientists to deal with this problem, and to examine the interface between private law and AI, which includes issues such as whether existing private law can address the challenges of AI and whether and how private law needs to be reformed to reduce the risks of AI while retaining its benefits.
  contract management machine learning: Machine Learning and Cognitive Computing for Mobile Communications and Wireless Networks Krishna Kant Singh, Akansha Singh, Korhan Cengiz, Dac-Nhuong Le, 2020-07-08 Communication and network technology has witnessed recent rapid development and numerous information services and applications have been developed globally. These technologies have high impact on society and the way people are leading their lives. The advancement in technology has undoubtedly improved the quality of service and user experience yet a lot needs to be still done. Some areas that still need improvement include seamless wide-area coverage, high-capacity hot-spots, low-power massive-connections, low-latency and high-reliability and so on. Thus, it is highly desirable to develop smart technologies for communication to improve the overall services and management of wireless communication. Machine learning and cognitive computing have converged to give some groundbreaking solutions for smart machines. With these two technologies coming together, the machines can acquire the ability to reason similar to the human brain. The research area of machine learning and cognitive computing cover many fields like psychology, biology, signal processing, physics, information theory, mathematics, and statistics that can be used effectively for topology management. Therefore, the utilization of machine learning techniques like data analytics and cognitive power will lead to better performance of communication and wireless systems.
  contract management machine learning: I-Byte Telecommunication & Media July 2021 IT Shades, 2021-07-21 ITShades.com has been founded with singular aim of engaging and enabling the best and brightest of businesses, professionals and students with opportunities, learnings, best practices, collaboration and innovation from IT industry. This document brings together a set of latest data points and publicly available information relevant for Telecommunication & Media Industry. We are very excited to share this content and believe that readers will benefit from this periodic publication immensely.
  contract management machine learning: Liquid Legal Kai Jacob, Dierk Schindler, Roger Strathausen, 2016-12-01 This book compels the legal profession to question its current identity and to aspire to become a strategic partner for corporate executives, clients and stakeholders, transforming legal into a function that creates incremental value. It provides a uniquely broad range of forward-looking perspectives from several different key-players in the legal industry: in-house legal, law firms, LPO’s, legal tech, HR, associations and academia. This publication is a platform for leading legal professionals that offers a new perspective on the accelerating transformation in legal. Combining expert contributions with editorial insights, it argues that the new legal function will shift from a paradigm of security to one of opportunity; that future corporate lawyers will no longer primarily be negotiators, litigators and administrators, but that instead they will be coaches, arbiters and intrapreneurs; that legal knowledge and data-based services will become a commodity; and that analytics and measurement will be key drivers of the future of the profession. A must-read for all legal professionals, this book sets the course for revitalizing the profession.
  contract management machine learning: Artificial Intelligence for Marketing Management Park Thaichon, Sara Quach, 2022-11-10 Artificial intelligence (AI) has driven businesses to adopt new business practices rapidly, enhance product development and services, has helped to power AI-based market intelligence and customer insights, and improve customer relationship management. This timely book addresses the use of AI in marketing. This book also explores the dark side of AI in marketing management and discusses ethics and transparency of automated decision-making in AI applications, data privacy, cyber security issues, and biases in various facets of marketing. Emerging applications of AI such as DeepFakes which use deep learning technology could increase risks of manipulation and deception. Hence, apart from leveraging AI capabilities and advantages, the book cautions the need for prevention strategies to deal with potential issues that could arise from the adoption of AI in marketing management. This book will provide practical insights into the role of AI in marketing management. It will be a useful reference for those researching marketing and marketing professionals.
  contract management machine learning: Data-Driven Law Edward J. Walters, 2018-07-16 For increasingly data-savvy clients, lawyers can no longer give it depends answers rooted in anecdata. Clients insist that their lawyers justify their reasoning, and with more than a limited set of war stories. The considered judgment of an experienced lawyer is unquestionably valuable. However, on balance, clients would rather have the considered judgment of an experienced lawyer informed by the most relevant information required to answer their questions. Data-Driven Law: Data Analytics and the New Legal Services helps legal professionals meet the challenges posed by a data-driven approach to delivering legal services. Its chapters are written by leading experts who cover such topics as: Mining legal data Computational law Uncovering bias through the use of Big Data Quantifying the quality of legal services Data mining and decision-making Contract analytics and contract standards In addition to providing clients with data-based insight, legal firms can track a matter with data from beginning to end, from the marketing spend through to the type of matter, hours spent, billed, and collected, including metrics on profitability and success. Firms can organize and collect documents after a matter and even automate them for reuse. Data on marketing related to a matter can be an amazing source of insight about which practice areas are most profitable. Data-driven decision-making requires firms to think differently about their workflow. Most firms warehouse their files, never to be seen again after the matter closes. Running a data-driven firm requires lawyers and their teams to treat information about the work as part of the service, and to collect, standardize, and analyze matter data from cradle to grave. More than anything, using data in a law practice requires a different mindset about the value of this information. This book helps legal professionals to develop this data-driven mindset.
  contract management machine learning: Stop Selling Stuff and Start Selling Business Outcomes: A Comprehensive B2B Sales Guide Rick Spair, Welcome to the comprehensive B2B sales guide titled Stop Selling Stuff and Start Selling Business Outcomes. In today's competitive business landscape, simply selling products or services is no longer enough to meet customer demands and drive success. B2B buyers are increasingly focused on achieving specific business outcomes and measurable results. This guide is designed to help B2B sales professionals make a shift in their approach by placing a strong emphasis on delivering tangible business outcomes to customers. Instead of merely selling features and functionalities, the guide will provide you with the strategies, tips, and recommendations to understand, align, and communicate the value of your offerings in terms of the outcomes they can enable for your customers. Throughout this comprehensive guide, we will explore a wide range of topics and chapters, delving into the various aspects of business outcome selling. We will start by understanding the principles and benefits of adopting this approach and how it compares to traditional product-based selling. From there, we will dive into identifying your target market, conducting market research, and segmenting your audience based on desired outcomes. You will learn how to gather valuable information about your prospects' industries, competitors, and challenges using online resources, social media, and industry reports. We will also explore the significance of leveraging existing customer relationships to gain insights and refine your approach. As we move forward, we will discuss the art of building relationships and trust, developing consultative sales approaches, and building rapport with prospects. We will delve into mapping business outcomes to customer needs, customizing your sales pitch, and crafting compelling value propositions that resonate with your prospects. Furthermore, we will explore strategies to overcome objections, address risks, and negotiate for successful outcomes. You will gain insights into building business cases, managing stakeholder buy-in, and presenting business outcomes effectively to secure buy-in from decision-makers. Throughout the guide, we will emphasize the importance of nurturing long-term customer relationships, incorporating customer testimonials and case studies, and continuously improving your sales approach based on customer feedback and market dynamics. We will discuss the significance of leveraging technology, data, and analytics to gain insights, streamline processes, and adapt to evolving customer needs. In addition, we will explore the importance of managing change, fostering a culture of continuous learning, and building strategic partnerships to enhance your business outcome selling efforts. We will provide recommendations for staying ahead in an ever-changing landscape and share insights into the future of B2B sales. Whether you are a seasoned sales professional or new to the field, this guide aims to equip you with the knowledge and tools to transform your sales approach and achieve success by focusing on delivering tangible business outcomes. The strategies, tips, and recommendations provided in this guide are based on industry best practices and real-life experiences, enabling you to adapt and apply them to your specific industry and target market. So, let's embark on this journey together and learn how to stop selling stuff and start selling business outcomes. By embracing this approach, you can differentiate yourself in the market, build stronger customer relationships, and drive meaningful results for your customers and your business.
  contract management machine learning: Artificial Intelligence for Business Hemachandran K, Raul V. Rodriguez, 2023-11-21 Artificial intelligence (AI) is transforming the business world at an unprecedented pace. From automating mundane tasks to predicting consumer behaviour, AI is changing the way businesses operate across all sectors. This book is an exploration of AI in business applications, highlighting the diverse range of ways in which AI is being used across different industries. The book begins with an overview of AI in business and its impact on the workforce. It then explores the role of AI in marketing, advertising, and tourism. The use of AI in personalized recommendations and chatbots is discussed in detail. The book then moves on to examine how AI is changing the retail industry, improving supply chain management, and enhancing the customer experience. The media and entertainment industry is also examined, with a focus on how AI is being used to personalize content and improve the user experience. The book also explores the use of AI in human resources, insurance, legal, and finance. The impact of AI on talent identification, recruitment, underwriting, document analysis, and financial forecasting is discussed in detail. In the healthcare and sports industries, AI is transforming the way we approach diagnosis, treatment, and training. The book examines how AI is being used to analyse medical images, develop personalized treatment plans, and improve patient outcomes. The use of AI in sports performance analysis is also discussed in detail. Finally, the book explores the use of AI in agriculture, energy, education, and the public sector. The potential of AI to optimize crop yields, reduce energy consumption, and improve the quality of education is discussed in detail. The book also examines how AI is being used to improve public services, such as transportation and emergency services. This book is a valuable resource for academics, researchers, professionals, and policymakers who are interested in understanding the potential of AI in the business world. The contributions from leading experts and researchers provide a comprehensive overview of AI in business applications, and how it is transforming different sectors. The book also examines the ethical dilemmas that arise from the use of AI in business, such as the impact on privacy and data security, and the potential for bias in AI algorithms. It provides valuable insights into how businesses can ensure that the use of AI is ethical and responsible. In conclusion, this book is a must-read for anyone interested in the potential of AI in the business world. It provides a comprehensive overview of AI in business applications and how it is transforming different sectors. The book examines the ethical dilemmas that arise from the use of AI in business, providing valuable insights into how businesses can ensure that the use of AI is ethical and responsible. We hope that readers will find this book informative and thought-provoking.
  contract management machine learning: The AI Book Ivana Bartoletti, Anne Leslie, Shân M. Millie, 2020-06-29 Written by prominent thought leaders in the global fintech space, The AI Book aggregates diverse expertise into a single, informative volume and explains what artifical intelligence really means and how it can be used across financial services today. Key industry developments are explained in detail, and critical insights from cutting-edge practitioners offer first-hand information and lessons learned. Coverage includes: · Understanding the AI Portfolio: from machine learning to chatbots, to natural language processing (NLP); a deep dive into the Machine Intelligence Landscape; essentials on core technologies, rethinking enterprise, rethinking industries, rethinking humans; quantum computing and next-generation AI · AI experimentation and embedded usage, and the change in business model, value proposition, organisation, customer and co-worker experiences in today’s Financial Services Industry · The future state of financial services and capital markets – what’s next for the real-world implementation of AITech? · The innovating customer – users are not waiting for the financial services industry to work out how AI can re-shape their sector, profitability and competitiveness · Boardroom issues created and magnified by AI trends, including conduct, regulation & oversight in an algo-driven world, cybersecurity, diversity & inclusion, data privacy, the ‘unbundled corporation’ & the future of work, social responsibility, sustainability, and the new leadership imperatives · Ethical considerations of deploying Al solutions and why explainable Al is so important
  contract management machine learning: The Attorney Meets ChatGPT Dr. Ope Banwo, Encounter Between Attorney And ChatGPT Reveals Everything Lawyers Need To Know About Using Artificial Intelligence In Law Practice.
  contract management machine learning: Contracting and Contract Law in the Age of Artificial Intelligence Martin Ebers, Cristina Poncibò, Mimi Zou, 2022-06-30 This book provides original, diverse, and timely insights into the nature, scope, and implications of Artificial Intelligence (AI), especially machine learning and natural language processing, in relation to contracting practices and contract law. The chapters feature unique, critical, and in-depth analysis of a range of topical issues, including how the use of AI in contracting affects key principles of contract law (from formation to remedies), the implications for autonomy, consent, and information asymmetries in contracting, and how AI is shaping contracting practices and the laws relating to specific types of contracts and sectors. The contributors represent an interdisciplinary team of lawyers, computer scientists, economists, political scientists, and linguists from academia, legal practice, policy, and the technology sector. The chapters not only engage with salient theories from different disciplines, but also examine current and potential real-world applications and implications of AI in contracting and explore feasible legal, policy, and technological responses to address the challenges presented by AI in this field. The book covers major common and civil law jurisdictions, including the EU, Italy, Germany, UK, US, and China. It should be read by anyone interested in the complex and fast-evolving relationship between AI, contract law, and related areas of law such as business, commercial, consumer, competition, and data protection laws.
  contract management machine learning: Changing Purchasing towards Procurement 4.0 Dennis Roßbach , 2021-11-05 Because Procurement and Purchasing and the supply chain are crucial in today’s fast-changing world, this book gives you a comprehensive overview of what Procurement and Purchasing are. The focus lies on Procurement 4.0 and what the future will provide to us all in this work area, not only for Procurement professionals but also for everyone who wants to deepen their knowledge on this important topic. Every company procures goods and services. Learn how you can adapt your processes to the future and learn more about new technologies like Blockchain, AI, Robotic Process Automation, and many more. Agile methods are tied together with all these processes, and we will look at Lean principles as well. In the end, you will learn how you can set up a smart contract with Ethereum. Get future-ready and let´s “Redefine Procurement”. Da Beschaffung und Einkauf sowie die Lieferkette in der heutigen, sich schnell verändernden Welt von entscheidender Bedeutung sind, gibt Ihnen dieses Buch einen umfassenden Überblick darüber, was Beschaffung und Einkauf sind. Der Schwerpunkt liegt auf den Einkauf 4.0 und dem, was die Zukunft uns allen in diesem Arbeitsbereich bieten wird, nicht nur für Einkaufs-Profis, sondern auch für alle, die ihr Wissen zu diesem wichtigen Thema vertiefen wollen. Jedes Unternehmen beschafft Waren und Dienstleistungen. Erfahren Sie, wie Sie Ihre Prozesse an die Zukunft anpassen können und lernen Sie mehr über neue Technologien wie Blockchain, KI, Robotic Process Automation und viele mehr. Agile Methoden sind mit all diesen Prozessen verbunden, und wir werden uns auch mit Lean-Prinzipien befassen. Zum Schluss erfahren Sie, wie Sie einen Smart Contract mit Ethereum aufsetzen können. Machen Sie sich fit für die Zukunft und lassen Sie uns “Einkauf neu definieren”.
  contract management machine learning: Machine Learning Hybridization and Optimization for Intelligent Applications Tanvir Habib Sardar, Bishwajeet Kumar Pandey, 2024-10-28 This book discusses state-of-the-art reviews of the existing machine learning techniques and algorithms including hybridizations and optimizations. It covers applications of machine learning via artificial intelligence (AI) prediction tools, discovery of drugs, neuroscience, diagnosis in multiple imaging modalities, pattern recognition approaches to functional magnetic resonance imaging, image and speech recognition, automatic language translation, medical diagnostic, stock market prediction, traffic prediction, and product automation. Features: • Focuses on hybridization and optimization of machine learning techniques. • Reviews supervised, unsupervised, and reinforcement learning using case study-based applications. • Covers the latest machine learning applications in as diverse domains as the Internet of Things, data science, cloud computing, and distributed and parallel computing. • Explains computing models using real-world examples and dataset-based experiments. • Includes case study-based explanations and usage for machine learning technologies and applications. This book is aimed at graduate students and researchers in machine learning, artificial intelligence, and electrical engineering.
  contract management machine learning: AI - The new intelligence in sales Livia Rainsberger, 2022-09-26 This book offers sales managers a quick overview of the possible applications of artificial intelligence in sales and explains basic functionalities. What is behind terms such as Sales Automation, Sales AI Analytics, Sales Enablement, Conversational AI, Lead Intelligence, Dynamic Pricing, Sales Management Intelligence and many more? Where is the concrete potential for sales organizations? And how will AI change the work in sales? The author presents the AI tools available on the market today and their application and describes the advantages and disadvantages as well as the limits and possibilities using clear examples. Executives in marketing and sales as well as entrepreneurs and managing directors, especially in medium-sized companies, will receive answers to the most important questions and additionally concrete recommendations for action for the implementation in their own companies.
  contract management machine learning: International Construction Arbitration Law Jane Jenkins, 2021-02-10 Arbitration in Context Series Volume 1 There is probably no area of activity more in need of reliable dispute resolution procedures than construction projects, especially if more than one jurisdiction is involved. The third edition of this eminently practical guide greatly facilitates the process for all parties concerned. The text, updated to include the latest edition of arbitral rules and introducing the Prague Rules, considers the full range of available dispute resolution methods, including mediation, conciliation and determination by dispute review boards, before focusing specifically on arbitration. The book then looks in detail at all aspects of arbitration, from commencement of proceedings, selection of the tribunal, through preparation and collection of the evidence necessary in complex construction cases, to common procedural issues, the conduct of the hearing, the effect of the award, challenges to it and its enforcement. The third edition addresses fresh thinking on MedArb, guidance on preparation for and conduct of virtual hearings in the wake of COVID-19, technological advances to assist collection and presentation of evidence, litigation funding and includes a new chapter on the role of arbitration in tender disputes. Specific valuable features include the following: guidance on the drafting of dispute resolution provisions designed to minimise disputes and facilitate their swift resolution; flowcharts to illustrate the stages in dispute procedures and arbitration; a comparison between common law and civil law approaches to key concepts; details of the key features of a construction contract, common standard forms and procurement structures; expert guidance on effective contract administration; step-by-step advice on the conduct of a construction arbitration to maximise efficiency; and coverage of particular issues thrown up by complex construction disputes which differentiate them from other commercial disputes, with guidelines on how to approach such issues in the presentation before a tribunal. As an easy-to-use resource for both general counsel and the lawyers in private practice, this book has no peers. It has proved to be of particular value to commercial contract negotiators and corporate counsel who may have many years of experience but have not had to live through a construction dispute or manage a construction contract during the life of a project. Lawyers in private practice embarking on a construction dispute for the first time will also find this book of value, as will students of dispute resolution.
  contract management machine learning: Machine Landscapes Liam Young, 2019-02-11 The most significant architectural spaces in the world are now entirely empty of people. The data centres, telecommunications networks, distribution warehouses, unmanned ports and industrialised agriculture that define the very nature of who we are today are at the same time places we can never visit. Instead they are occupied by server stacks and hard drives, logistics bots and mobile shelving units, autonomous cranes and container ships, robot vacuum cleaners and internet-connected toasters, driverless tractors and taxis. This issue is an atlas of sites, architectures and infrastructures that are not built for us, but whose form, materiality and purpose is configured to anticipate the patterns of machine vision and habitation rather than our own. We are said to be living in a new geological epoch, the Anthropocene, in which humans are the dominant force shaping the planet. This collection of spaces, however, more accurately constitutes an era of the Post-Anthropocene, a period where it is technology and artificial intelligence that now computes, conditions and constructs our world. Marking the end of human-centred design, the issue turns its attention to the new typologies of the post-human, architecture without people and our endless expanse of Machine Landscapes. Contributors: Rem Koolhaas, Merve Bedir and Jason Hilgefort, Benjamin H Bratton, Ingrid Burrington, Ian Cheng, Cathryn Dwyre, Chris Perry, David Salomon and Kathy Velikov, John Gerrard, Alice Gorman, Adam Harvey, Jesse LeCavalier, Xingzhe Liu, Clare Lyster, Geoff Manaugh, Tim Maughan, Simone C Niquille, Jenny Odell, Trevor Paglen, Ben Roberts. Featured interviews: Deborah Harrison, designer of Microsoft’s Cortana; and Paul Inglis, designer of the urban landscapes of Blade Runner 2049.
Capture the value of your contracts - KPMG
Seeking to improve operational eficiencies and reduce costs, leading companies are already beginning to apply machine learning (ML) and advanced analytics to contract life cycle …

Enhancing Contract Review Processes with Ai and Machine …
This paper explores how integrating Artificial Intelligence (AI) and Machine Learning (ML) into contract review workflows can significantly enhance accuracy, efficiency, and consistency.

Smarter Decision-Making Powered by AI and Contract …
Businesses want intelligent automation, driven by AI and Machine Learning (ML), for accelerated contract reviews and safer negotiations. Geopolitical and economic uncertainties have …

Artificial Intelligence in Contract Management
Machine learning (ML) – a computer process that is not explicitly programmed by a person, but the computer “learns” by processing one data record at a time and revising that model with …

Evaluating and Predicting Contract Performance Using …
We collected 24,364 contract files in PDF format spanning 149 contract numbers and 34 MDAPs. (The MDAPs and their associated contract numbers are in Appendix B.) Finally, we used the …

Automating Construction Contract Review Using Knowledge …
Machine learning or deep learning-based models are trained on annotated contract clauses with risk labels. These models primarily serve as risk classification tools for preliminary contract …

Harness the power of Analytics and AI for contract management
Using the power of AI, dTrax reduces cycle time and streamlines the contract management process by standardizing templates, automating first drafts of agreements, and managing the …

Measuring Transaction Costs in Public Sector Contracting …
• This article shows how machine learning techniques and contract text data can be leveraged to construct theoretically and empirically relevant transaction measures across a large range of …

Towards Smarter Contract Management - Infosys BPM
In this article, we try to understand how AI can bring substantial value-addition for category managers in the area of contract management.

Automated construction contract analysis for risk and …
This research aims to develop models for automating the review of construction contracts to extract information on risk and responsibility that will provide inputs for risk management plans.

Using NLP for Automated Contract Review and Risk Assessment
Automated analysis of contracts can be a solution for early detection of contract risks. This research project involves the development of an automated text analysis model based on …

Contract Management Best Practices Playbook - CobbleStone …
centralized and secure contract repository can help you proactively identify opportunities, improve contract oversight, and manage risk with the help of robust artificial intelligence with machine …

Automated Construction Contract Summarization Using …
To address this research need, the authors proposed to use natural language processing (NLP) and deep learning technology to summarize construction contracts (i.e., text summarization). …

Contract Law and Artificial Intelligence: Examine the …
Nov 1, 2024 · Artificial Intelligence (AI) is changing contract law, especially in the areas of contract negotiation and implementation. The use of AI technologies by businesses is growing, and this …

Contract Information Extraction Using Machine Learning - DTIC
information is extracted from the contracts using machine learning (ML) in combination with natural language processing. Specifically, two types of ML models are used, named

The Dawn of Fully Automated Contract Drafting: Machine …
“Machine learning,” the leading innovative force in these areas, has proven incredibly efficient, performing in mere minutes tasks that would otherwise take a team of lawyers tens of hours.

Construction contract risk identification based on
In this paper, we introduce a novel knowledge-augmented CCRI methodology. It augments an LLM with factual knowledge and the knowledge of contract experts, without fine-tuning the …

project performance: Survey versus machine learning
Construction contracts were analyzed by machine learning to obtain the objective measurement of 11 contract complexity, while questionnaires provide the subjective measurement. Through a ...

INDOT: Building the Bridge from Spreadsheets to Machine …
application of Machine Learning’s sophisticated analytical tools enable contract bundling staff to leverage the full potential bundling offers. This paper reviews the findings from a Machine …

Paid with Models: Optimal Contract Design for Collaborative …
We conduct a de-tailed analysis of the properties that an optimal contract must satisfy when models serve as the rewards, and we explore the potential benefits and welfare implications of …

Capture the value of your contracts - KPMG
Seeking to improve operational eficiencies and reduce costs, leading companies are already beginning to apply machine learning (ML) and …

Enhancing Contract Review Processes with Ai and Mac…
This paper explores how integrating Artificial Intelligence (AI) and Machine Learning (ML) into contract review workflows can significantly enhance …

Smarter Decision-Making Powered by AI and Contrac…
Businesses want intelligent automation, driven by AI and Machine Learning (ML), for accelerated contract reviews and safer negotiations. Geopolitical …

Artificial Intelligence in Contract Management
Machine learning (ML) – a computer process that is not explicitly programmed by a person, but the computer “learns” by processing one …

Evaluating and Predicting Contract Performance Usi…
We collected 24,364 contract files in PDF format spanning 149 contract numbers and 34 MDAPs. (The MDAPs and their associated contract …