Edited by Roland Vogl, Executive Director and Lecturer in Law, CodeX - The Stanford Center for Legal Informatics, Stanford Law School, US

'With insights across a spectrum of experts, this Handbook serves as a vital guide for thinking through some of the opportunities and challenges that arise with the use of big data in legal settings.'

• Contents:Introduction to the Research Handbook on Big Data Law 1Roland Vogl1 The accuracy, equity, and jurisprudence of criminal risk assessment 9Sharad Goel, Ravi Shroff, Jennifer Skeem and Christopher Slobogin2 The many faces of facial recognition 29Stephen Caines3 Artificially intelligent government: A review and agenda 57David Freeman Engstrom and Daniel E. Ho4 Big data and copyright law 87Daniel Seng5 Big data analytics, online terms of service and privacy policies 115Przemysław Pałka and Marco Lippi6 Data analytics and tax law 135Benjamin Alarie, Anthony Niblett and Albert Yoon7 Experience of big data anti-corruption in China 150Ran Wang8 Machine learning and law: An overview 171Harry Surden9 SCOTUS outcome prediction: A new machine learning approach 185Ashkon Farhangi and Ajay Sohmshetty10 Legal information retrieval 198Ashraf Bah Rabiou11 LexNLP: Natural language processing and information extraction forlegal and regulatory texts 216Michael J. Bommarito II, Daniel Martin Katz and Eric M. Detterman12 Quantitative legal research in Germany 228Dirk Hartung13 Big data analytics for e-discovery 252Johannes C. Scholtes and Hendrik Jacob van den Herik14 Generalizability: Machine learning and humans-in-the-loop 284John Nay and Katherine J. Strandburg15 The VICTOR Project: Applying artificial intelligence to Brazil’sSupreme Federal Court 303Ricardo Vieira de Carvalho Fernandes, Danilo Barros Mendes, GustavoHenrique T.A. Carvalho and Hugo Honda Ferreira16 Explainable artificial intelligence 317Mary-Anne Williams17 Explainability and transparency of machine learning in ADM systems 340Bernhard Waltl18 Certifying artificial intelligence systems 356Florian Möslein and Roberto V. Zicari19 Rules, cases and arguments in artificial intelligence and law 373Heng Zheng and Bart Verheij20 Artificial intelligence and the zealous litigator 388James Yoon21 Evaluating legal services: The need for a quality movement andstandard measures of quality and value 403Daniel W. Linna Jr.22 Machine learning and EU data-sharing practices: Legal aspects ofmachine learning training datasets for AI systems 431Mauritz Kop23 AI-driven contract review: A product development journey 453Shlomit Labin and Uri Segal24 Practical guide to artificial intelligence and contract review 466Andrew Antos and Nischal Nadhamuni25 Legal marketplaces using machine learning techniques 481Verónica Sorin and Martí ManentIndex

Edited by Roland Vogl, Executive Director and Lecturer in Law, CodeX - The Stanford Center for Legal Informatics, Stanford Law School, US

'With insights across a spectrum of experts, this Handbook serves as a vital guide for thinking through some of the opportunities and challenges that arise with the use of big data in legal settings.'

• Contents:Introduction to the Research Handbook on Big Data Law 1Roland Vogl1 The accuracy, equity, and jurisprudence of criminal risk assessment 9Sharad Goel, Ravi Shroff, Jennifer Skeem and Christopher Slobogin2 The many faces of facial recognition 29Stephen Caines3 Artificially intelligent government: A review and agenda 57David Freeman Engstrom and Daniel E. Ho4 Big data and copyright law 87Daniel Seng5 Big data analytics, online terms of service and privacy policies 115Przemysław Pałka and Marco Lippi6 Data analytics and tax law 135Benjamin Alarie, Anthony Niblett and Albert Yoon7 Experience of big data anti-corruption in China 150Ran Wang8 Machine learning and law: An overview 171Harry Surden9 SCOTUS outcome prediction: A new machine learning approach 185Ashkon Farhangi and Ajay Sohmshetty10 Legal information retrieval 198Ashraf Bah Rabiou11 LexNLP: Natural language processing and information extraction forlegal and regulatory texts 216Michael J. Bommarito II, Daniel Martin Katz and Eric M. Detterman12 Quantitative legal research in Germany 228Dirk Hartung13 Big data analytics for e-discovery 252Johannes C. Scholtes and Hendrik Jacob van den Herik14 Generalizability: Machine learning and humans-in-the-loop 284John Nay and Katherine J. Strandburg15 The VICTOR Project: Applying artificial intelligence to Brazil’sSupreme Federal Court 303Ricardo Vieira de Carvalho Fernandes, Danilo Barros Mendes, GustavoHenrique T.A. Carvalho and Hugo Honda Ferreira16 Explainable artificial intelligence 317Mary-Anne Williams17 Explainability and transparency of machine learning in ADM systems 340Bernhard Waltl18 Certifying artificial intelligence systems 356Florian Möslein and Roberto V. Zicari19 Rules, cases and arguments in artificial intelligence and law 373Heng Zheng and Bart Verheij20 Artificial intelligence and the zealous litigator 388James Yoon21 Evaluating legal services: The need for a quality movement andstandard measures of quality and value 403Daniel W. Linna Jr.22 Machine learning and EU data-sharing practices: Legal aspects ofmachine learning training datasets for AI systems 431Mauritz Kop23 AI-driven contract review: A product development journey 453Shlomit Labin and Uri Segal24 Practical guide to artificial intelligence and contract review 466Andrew Antos and Nischal Nadhamuni25 Legal marketplaces using machine learning techniques 481Verónica Sorin and Martí ManentIndex

Edited by Roland Vogl, Executive Director and Lecturer in Law, CodeX - The Stanford Center for Legal Informatics, Stanford Law School, US

'With insights across a spectrum of experts, this Handbook serves as a vital guide for thinking through some of the opportunities and challenges that arise with the use of big data in legal settings.'

• Contents:Introduction to the Research Handbook on Big Data Law 1Roland Vogl1 The accuracy, equity, and jurisprudence of criminal risk assessment 9Sharad Goel, Ravi Shroff, Jennifer Skeem and Christopher Slobogin2 The many faces of facial recognition 29Stephen Caines3 Artificially intelligent government: A review and agenda 57David Freeman Engstrom and Daniel E. Ho4 Big data and copyright law 87Daniel Seng5 Big data analytics, online terms of service and privacy policies 115Przemysław Pałka and Marco Lippi6 Data analytics and tax law 135Benjamin Alarie, Anthony Niblett and Albert Yoon7 Experience of big data anti-corruption in China 150Ran Wang8 Machine learning and law: An overview 171Harry Surden9 SCOTUS outcome prediction: A new machine learning approach 185Ashkon Farhangi and Ajay Sohmshetty10 Legal information retrieval 198Ashraf Bah Rabiou11 LexNLP: Natural language processing and information extraction forlegal and regulatory texts 216Michael J. Bommarito II, Daniel Martin Katz and Eric M. Detterman12 Quantitative legal research in Germany 228Dirk Hartung13 Big data analytics for e-discovery 252Johannes C. Scholtes and Hendrik Jacob van den Herik14 Generalizability: Machine learning and humans-in-the-loop 284John Nay and Katherine J. Strandburg15 The VICTOR Project: Applying artificial intelligence to Brazil’sSupreme Federal Court 303Ricardo Vieira de Carvalho Fernandes, Danilo Barros Mendes, GustavoHenrique T.A. Carvalho and Hugo Honda Ferreira16 Explainable artificial intelligence 317Mary-Anne Williams17 Explainability and transparency of machine learning in ADM systems 340Bernhard Waltl18 Certifying artificial intelligence systems 356Florian Möslein and Roberto V. Zicari19 Rules, cases and arguments in artificial intelligence and law 373Heng Zheng and Bart Verheij20 Artificial intelligence and the zealous litigator 388James Yoon21 Evaluating legal services: The need for a quality movement andstandard measures of quality and value 403Daniel W. Linna Jr.22 Machine learning and EU data-sharing practices: Legal aspects ofmachine learning training datasets for AI systems 431Mauritz Kop23 AI-driven contract review: A product development journey 453Shlomit Labin and Uri Segal24 Practical guide to artificial intelligence and contract review 466Andrew Antos and Nischal Nadhamuni25 Legal marketplaces using machine learning techniques 481Verónica Sorin and Martí ManentIndex