Slides: Legal Informatics Research Today: Implications for Legal Prediction, 3D Printing, and eDiscovery

I’ve posted slides of my presentation entitled Legal Informatics Research Today: Implications for Legal Prediction, 3D Printing, and eDiscovery, given 16 May 2013 at CICL 2013: The Fifth Conference on Innovation and Communications Law, 16 May 2013, Glen Arbor, Michigan, sponsored by Michigan State University College of Law.

Here is the abstract:

This presentation describes methodologies and results of recent legal informatics research on eDiscovery and legal prediction, and describes two possible scenarios for the application of legal technology to 3D printing. In addition, the presentation describes a four-level framework that enables comparison of legal informatics research studies in different areas.

I thank Professor Adam Candeub of Michigan State University College of Law for inviting me to give this presentation.

Lagnado, Fenton, and Neil: Legal idioms: A framework for evidential reasoning

Dr. David A. Lagnado of University College London, and Professor Dr. Norman Fenton and Professor Dr. Martin Neil, both of Queen Mary University of London, have published Legal idioms: A framework for evidential reasoning, Argument & Computation 4(1), 46-63 (2013).

Here is the abstract:

How do people make legal judgments based on complex bodies of interrelated evidence? This paper outlines a novel framework for evidential reasoning using causal idioms. These idioms are based on the qualitative graphical component of Bayesian networks, and are tailored to the legal context. They can be combined and reused to model complex bodies of legal evidence. This approach is applied to witness and alibi testimony, and is illustrated with a real legal case. We show how the framework captures critical aspects of witness reliability, and the potential interrelations between witness reliabilities and other hypotheses and evidence. We report a brief empirical study on the interpretation of alibi evidence, and show that people’s intuitive inferences fit well with the qualitative aspects of the idiom-based framework.

Articles on legal information or decision making in new issue of Journal of Empirical Legal Studies

The new issue of Journal of Empirical Legal Studies (10(2), June 2013) includes several articles on legal information or decision making:

• Doug Williams: Do Racial Preferences Affect Minority Learning in Law Schools?
• Andreas Glöckner and Christoph Engel: Can We Trust Intuitive Jurors? Standards of Proof and the Probative Value of Evidence in Coherence-Based Reasoning
• Christina L. Boyd, David A. Hoffman, Zoran Obradovic and Kosta Ristovski: Building a Taxonomy of Litigation: Clusters of Causes of Action in Federal Complaints
• Ryan C. Black and James F. Spriggs II: The Citation and Depreciation of U.S. Supreme Court Precedent
• William C. Thompson, Suzanne O. Kaasa and Tiamoyo Peterson: Do Jurors Give Appropriate Weight to Forensic Identification Evidence?

HT @aabibliographer

Call for Papers: Special issue of AI & Law on Computational Methods for Enforcing Privacy and Fairness

Dr. Thomas F. Gordon of Fraunhofer Institute for Open Communications Systems (FOKUS) tells us that a call for papers has been issued for a special issue of the journal Artificial Intelligence and Law on the topic, “Computational Methods for Enforcing Privacy and Fairness in the Knowledge Society”.

The submission deadline is 15 April 2013.

Here is an excerpt from the call:

We invite contributions on methodologies, techniques, algorithms, and tools in support of the analysis or of the enforcement of privacy, non-discrimination, and other personal rights in ICT systems for the knowledge society. Special focus is on multi-disciplinary approaches on the following, non-exhaustive, list of topics, and that relate to Artificial Intelligence and Law:

• Methods for enforcing data privacy and anonymity
• Methods for data portability, and for the right to oblivion
• Methods for data protection and law enforcement
• Privacy by-design in intelligent systems
• Privacy-preserving data mining
• Privacy policies in social networks
• Context-aware location privacy
• Methods for unbiased data collection and processing
• Methods for enforcing fairness in profiling and targeting
• Methods for discrimination discovery from data
• Statistical measures of discrimination
• Methods for discrimination prevention in data mining
• Computational argumentation in discrimination analysis
• Design of (quasi-)experimental methods
• Computational models of segregation in social networks
• Computational models of evidential reasoning
• Tools and systems, with case studies [...]

For more details, please see the complete call.

HT Tom Gordon

Fornaciari and Poesio on Automatic deception detection in Italian court cases

Tommaso Fornaciari of the University of Trento, and Professor Dr. Massimo Poesio of the University of Essex, have published Automatic deception detection in Italian court cases, forthcoming in Artificial Intelligence and Law.

Here is the abstract:

Effective methods for evaluating the reliability of statements issued by witnesses and defendants in hearings would be an extremely valuable support to decision-making in court and other legal settings. In recent years, methods relying on stylometric techniques have proven most successful for this task; but few such methods have been tested with language collected in real-life situations of high-stakes deception, and therefore their usefulness outside lab conditions still has to be properly assessed. In this study we report the results obtained by using stylometric techniques to identify deceptive statements in a corpus of hearings collected in Italian courts. The defendants at these hearings were condemned for calumny or false testimony, so the falsity of (some of) their statements is fairly certain. In our experiments we replicated the methods used in previous studies but never before applied to high-stakes data, and tested new methods. We also considered the effect of a number of variables including in particular the homogeneity of the dataset. Our results suggest that accuracy at deception detection clearly above chance level can be obtained with real-life data as well.

Call for Papers: AICOL 2013: Workshop on AI Approaches to the Complexity of Legal Systems

A call for papers — with abstract submission deadline of 28 February 2013 and full paper submission deadline of 15 May 2013 — has been issued for AICOL 2013: Workshop on AI Approaches to the Complexity of Legal Systems, to be held at a date to be determined, between 21 and 27 July 2013, in Belo Horizonte, Brazil.

The workshop is being collocated with XXVI. World Congress of Philosophy of Law and Social Philosophy.

Papers for AICOL 2013 are invited on the following topics:

• Law and Science
• Knowledge Management
• Law and Cognitive Science
• Cognitive schemas
• Law and Complexity Theory
• Law and Robotics
• Complex Systems
• Law and Mathematics
• Legal Theory
• Legal Graphic Representation
• Legal Culture
• Game Theory
• Computer Ethics
• Formalization of Legal Systems and Norms
• Artificial Societies
• Rules and Standards
• Argumentative Frameworks
• Agreement technologies
• Legal Ontologies
• Electronic Institutions
• Governance
• Legal Concepts
• Legal Information Retrieval
• Legal Thesauri
• Online Dispute Resolution
• Taxonomies
• Trends in e-Discovery, e-Courts, e-Administration
• Natural Language Processing (NLP)
• Legal Knowledge Acquisition
• Users’ studies
• Legal Knowledge Representation

For more details, please see the call.

HT Professor Dr. Monica Palmirani

Katz and Bommarito: Three Thoughts on E-Discovery in 2015 and Beyond

Professor Dr. Daniel Martin Katz of Michigan State University College of Law and Michael Bommarito of Computational Legal Studies have posted slides of their 2013 Legal Tech New York presentation entitled 3 Thoughts on E-Discovery in 2015 and Beyond.

The slides address topics including predictive coding, machine learning, information visualization, pattern recognition, and “scaling relationships,” including scaling involving costs of computer processing and rates of growth of electronically stored information.

Call for Papers: DESI V: Workshop on Standards for Using Predictive Coding and Other Machine Learning Algorithms

A call for papers — with submission deadline of 1 May 2013 — has been issued for DESI V: Workshop on Standards for Using Predictive Coding and Other Machine Learning Algorithms, to be held 14 June 2013 in Rome, Italy, following ICAIL 2013: International Conference on Artificial Intelligence and Law.

Papers addressing the following questions are invited for DESI V:

1) How transparent can and should the process be in sharing seed sets or training sets of documents with opposing parties, including the sharing of privileged documents?

2) What differences if any exist between seed sets developed through random sampling versus other forms of judgmental sampling (including picking seed documents using keywords)?

3) How are non-relevant documents used to optimize machine learning algorithms and should they be subject to similar disclosure?

4) Are there ways in which predictive coding and machine learning methods can be tuned to find highly relevant (“hot”) documents in large collections?

5) To what extent is metadata important in tuning predictive coding software to find similarity in documents?

6) In light of past research at the TREC Legal Track and elsewhere, are there absolute targets for metrics in recall and precision that could serve as standards in every case, or are achieving certain metrics dependent on the relevant data set and legal context?

7) What kinds of best practice standards are needed to help improve mutual understanding of what was actually done, and to improve overall “search quality”?

8) How should predictive coding techniques be audited in connection with an entity submitting itself to an ISO 9001 quality measurement process?

9) To what extent can and should machine learning approaches be used in other phases of the litigation process, to assist in aspects of the process such as identification, preservation, and collection?

10)What are the applications of predictive coding and other forms of machine learning in related “compliance” areas, including regulatory, enforcement, and investigations?

The workshop discussion will be grounded in the results of the recently completed TREC Legal Track, especially where supervised learning methods have shown promising results in terms of being able to more cost-effectively demonstrate rates of recall and precision that approximate the best that could be obtained through other methods, including exhaustive manual review.

For more details, please see the complete call.

HT Jurix.

Gittelson et al.: Modeling the forensic two-trace problem with Bayesian networks

Simone Gittelson of l’Institut de Police Scientifique, Ecole des Sciences Criminelles, Université de Lausanne, and colleagues, have published Modeling the forensic two-trace problem with Bayesian networks, forthcoming in Artificial Intelligence and Law.

Here is the abstract:

The forensic two-trace problem is a perplexing inference problem introduced by Evett (J Forensic Sci Soc 27:375–381, 1987). Different possible ways of wording the competing pair of propositions (i.e., one proposition advanced by the prosecution and one proposition advanced by the defence) led to different quantifications of the value of the evidence (Meester and Sjerps in Biometrics 59:727–732, 2003). Here, we re-examine this scenario with the aim of clarifying the interrelationships that exist between the different solutions, and in this way, produce a global vision of the problem. We propose to investigate the different expressions for evaluating the value of the evidence by using a graphical approach, i.e. Bayesian networks, to model the rationale behind each of the proposed solutions and the assumptions made on the unknown parameters in this problem.

JURIX 2012: 17-19 December

JURIX 2012: International Conference on Legal Knowledge and Information Systems is being held 17-19 December 2012, at Leibniz Center for Law, University of Amsterdam.

The Twitter hashtag for the conference is #jurix2012

Click here for archived Twitter tweets (in .csv format) from the conference.

Click here for the conference program.

Click here for the list of workshops and tutorials.

HT @jurixfoundation