Our Research

Taxation of Automation and Artificial Intelligence as a Tool of Labour Policy

Published Date: 31/10/2018

Ooi, Vincent and Goh, Glendon SMU Centre for AI & Data Governance Research Paper No. 2019/01 (2021) 19(1) eJournal of Tax Research (Forthcoming)

The Law and Finance of Initial Coin Offerings

Published Date: 20/05/2018

Gurrea-Martínez, Aurelio and Remolina, Nydia Ibero-American Institute for Law and Finance Working Paper No. 4/2018; SMU Centre for AI & Data Governance Research Paper No. 2019/06.

The Singapore Personal Data Protection Act and an Assessment of Future Trends in Data Privacy Reform

Published Date: 28/10/2013

Chik, Warren B. 2013. Computer Law & Security Review 29(5):554–75.

Traffic Rule Formalization for Autonomous Vehicle

Author(s): Hanif Bhuiyan, Guido Governatori, Andry Rakotonirainy, Meng Weng Wong, Singapore Management University, and Avishkar Mahajan

This study devised and implemented a Defeasible Deontic Logic (DDL)-based formalization approach for translating traffic rules into a machine-computable (M/C) format and thus solving rule issues: rule vagueness (open tex-ture expressions) and exceptions in rules. The resulting M/C format of traffic rules can be utilized for automatic traffic rule reasoning to assist the Autonomous Vehicle (AV) in making legal decisions. The method incorporates the compo-nents and behaviour of regulations based on the rule's obligation, prohibition, and permission activities.

The need for the encoding methodology is motivated by the desire for auto-mated reasoning over Autonomous Vehicle information involving traffic rules. A Queensland (QLD) overtaking traffic rule is used as a use case to illustrate this proposed encoding methodology’s mechanism and usefulness.

BHUIYAN, Hanif; GOVERNATORI, Guido; RAKOTONIRAINY, Andry; WONG, Meng Weng; and MAHAJAN, Avishkar. Traffic rule formalization for autonomous vehicle. (2022). LN2FR 2022: Workshop on Methodologies for Translating Legal Norms into Formal Representations in conjunction with JURIX 2022, the 35th International Conference on Legal Knowledge and Information Systems, Saarbrücken, Germany December 14. 1-14.

An End-to-End Pipeline from Law Text to Logical Formulas

Author(s): Aarne RANTA, Chalmers University of Technology, Inari LISTENMAA, Singapore Management University, Jerrold SOH, Singapore Management University, Meng Weng (HUANG Mingrong) WONG, Singapore Management University

This paper develops a pipeline for converting natural English law texts into logical formulas via a series of structural representations. The goal is to study how law-to-logic translation can be achieved with a sequence of well-defined steps. The texts are first parsed using a formal grammar derived from light-weight text annotations designed to minimise the need for manual grammar construction. An intermediate representation, called assembly logic, is then used for logical interpretation and supports translations to different back-end logics and visualisations. The approach, while rule-based and explainable, is also robust: it can deliver useful results from day one, but allows subsequent refinements and variations. While some work is needed to extend the method to new laws, the software presented here reduces the marginal effort necessary. As a case study, we demonstrate our approach on one part of Singapore’s Personal Data Protection Act. Our code is available open-source.

RANTA, Aarne; LISTENMAA, Inari; SOH, Jerrold; and WONG, Meng Weng (HUANG Mingrong). An end-to-end pipeline from law text to logical formulas. (2022). Legal knowledge and information systems: Proceedings of the 35th International Conference, Saarbrücken, Germany, 2022 December 14-16. 362, 237-242.

Towards CNL-based Verbalization of Computational Contracts

Author(s): Inari LISTENMAA, Singapore Management University, Maryam HANAFIAH, Singapore Management University, Regina CHEONG, Singapore Management University, Andreas KALLBERG, Singapore Management University

At CCLAW, our work aims at computerizing legal reasoning in a manner that is both formally precise and intuitively accessible to legal experts. The cornerstone is a domain specific language (DSL) for the legal domain, called L4, which can be converted to natural language but is also the basis for formal verification procedures.

L4's applied focus places it within the "Rules as Code" movement (e.g. OpenFisca, Catala) that itself draws on early computational law thinking. But rather than focusing on encoding laws into existing programming languages, we devise an external DSL designed for legal specification. From this specification, we generate a range of output formats. Key augmentations include IDE support, formal verification engines, transpilation to operational rule engines, and natural language generation (NLG). The latter is done via a controlled natural language (CNL) implemented in Grammatical Framework (GF), and is the focus of this paper.

LISTENMAA, Inari; HANAFIAH, Maryam; CHEONG, Regina; and KALLBERG, Andreas. Towards CNL-based verbalization of computational contracts. (2021). CNL 2020/21 7th International Workshop in Controlled Natural Language: Workshop Proceedings, 2021, September 8-9. 1-7.

Deontics and Time in Contracts: An Executable Semantics for the L4 DSL

Author(s): Seng Joe WATT, Singapore Management University, Oliver GOODENOUGH, Meng Weng (HUANG Mingrong) WONG, Singapore Management University

Existing approaches to modelling contracts often rely on deontic logic to reason about norms, and only treat time qualitatively. Using L4, a textual domain specific language (DSL) for the law, we offer a more operational interpretation of norms, based on states and transitions, that also accounts for the granular timing of events. In this paper, we present a higher-level rendering of the loan agreement from Flood & Goodenough in L4, and an accompanying operational semantics amenable to execution and static analysis. We also implement this semantics in Maude and show how this lets us visualize the execution of the loan agreement.

WATT, Seng Joe; GOODENOUGH, Oliver; and WONG, Meng Weng (HUANG Mingrong). Deontics and time in contracts: An executable semantics for the L4 DSL. (2023). Legal Knowledge and Information Systems: Proceedings of JURIX 2023. 379, 119-124.

Driving-Decision Making of Autonomous Vehicle according to Queensland Overtaking Traffic Rules

Author(s): Hanif BHUIYAN, Guido GOVERNATORI, Avishkar MAHAJAN, Andry RAKOTONIRAINY, Meng Weng (HUANG Mingrong) WONG, Singapore Management University

Making a driving decision according to traffic rules is a challenging task for improving the safety of Autonomous Vehicles (AVs). Traffic rules often contain open texture expressions and exceptions, which makes it hard for AVs to follow them. This paper introduces a Defeasible Deontic Logic (DDL) based driving decision-making methodology for AVs. We use DDL to formalize traffic rules and facilitate automated reasoning. DDL is used to effectively handle rule exceptions and resolve open texture expressions in rules. Furthermore, we supplement the information provided by the traffic rules by an ontology for AV driving behaviour and environment information. This methodology performs auto-mated reasoning on formalized traffic rules and ontology-based AV driving information to make the driving decision by following the traffic rule. The over-taking traffic rule is our case study to illustrate the usefulness of our methodology. The case study evaluation showed the effectiveness of this proposed driving decision-making methodology.

BHUIYAN, Hanif; GOVERNATORI, Guido; MAHAJAN, Avishkar; RAKOTONIRAINY, Andry; and WONG, Meng Weng (HUANG Mingrong). Driving-decision making of autonomous vehicle according to Queensland overtaking traffic rules. (2022). International Workshop on AI Compliance Mechanism WAICOM 2022.

User Guided Abductive Proof Generation for Answer Set Programming Queries

Author(s): Avishkar MAHAJAN, Martin STRECKER, Meng Weng (HUANG Mingrong) WONG, Singapore Management University

We present a method for generating possible proofs of a query with respect to a given Answer Set Programming (ASP) rule set using an abductive process where the space of abducibles is automatically constructed just from the input rules alone. Given a (possibly empty) set of user provided facts, our method infers any additional facts that may be needed for the entailment of a query and then outputs these extra facts, without the user needing to explicitly specify the space of all abducibles. We also present a method to generate a set of directed edges corresponding to the justification graph for the query. Furthermore, through different forms of implicit term substitution, our method can take user provided facts into account and suitably modify the abductive solutions. Past work on abduction has been primarily based on goal directed methods. However these methods can result in solvers that are not truly declarative. Much less work has been done on realizing abduction in a bottom up solver like the Clingo ASP solver. We describe novel ASP programs which can be run directly in Clingo to yield the abductive solutions and directed edge sets without needing to modify the underlying solving engine.

MAHAJAN, Avishkar; STRECKER, Martin; and WONG, Meng Weng (HUANG Mingrong). User guided abductive proof generation for answer set programming queries. (2022). Proceedings of the 24th International Symposium on Principles and Practice of Declarative Programming, Tbilisi, Georgia, 2022 September 20-22. 1-14.

Constraint Answer Set Programming as a Tool to Improve Legislative Drafting

Author(s): Jason MORRIS, Singapore Management University

"Rules as Code" in this paper is used to refer to a proposed methodology of legislative and regulatory drafting. That legislation can be represented in declarative code for automation has long been recognized, as has the opportunity for improving the quality of legal drafting with the techniques of formal representation.

Rules as Code further proposes that both drafting and automation would be improved by initially co-drafting statute law in both natural and computer languages simultaneously.

Knowledge acquisition bottlenecks and roadblocks associated with statutory interpretation are largely avoided. The co-drafted encoding need only reflect what the legislation says, and not what the legislators meant. Legislative intent is instead encoded as tests by people with authoritative knowledge of the intent, the drafters. In this way, failed tests can be used in the drafting process to signal issues with the natural language draft. When the drafting process is complete an authoritative encoding consistent with the legislative intent already exist. This encoding can be used by regulators and regulated entities to automate services and compliance tasks.

MORRIS, Jason. Constraint answer set programming as a tool to improve legislative drafting. (2021). Proceedings of the 18th International Conference on Artificial Intelligence and Law, São Paulo, Brazil, 2021 June 21-25. 262-263.

Defeasible Semantics for L4

Author(s): Guido GOVERNATORI, Meng Weng (HUANG Mingrong) WONG, Singapore Management University

The importance of defeasibility for legal reasoning has been investigated for a long time (see among other [10, 3, 11]). This notion mostly concerns the issue that textual provisions of (legal) norms typically provide prima facie conditions for their applicability, but to understand a norm in full, we have to evaluate the norms in the context in which the norm is used and to see if other norms prevent it either to apply or to be effective. In other words, when evaluating norms, we must account for possible (prima facie) conflicts and exceptions. Indeed, in general, norms first provide the basic conditions for their applicability. Then, they give the exceptions and exclusions (and they can go on, with exceptions/exclusions of the exceptions/exclusions and so on).

The first issue to address to model legal reasoning is how to model norms. Here, we follow the approach of [12, 4] and stipulate that a norm is represented by an “IF · · · THEN . . .” rule, where the IF part establishes the conditions of applicability of the norm and the THEN part specifies the legal effect of the norm. Where the legal effect of the norm is either that a proposition is taken to hold legally or that a legal requirement (obligation, prohibition, permission) is in force. Moreover, as we have alluded to, the norms are defeasible; thus, the IF/THEN conditional used to model legal norms does not correspond to the material implication of classical logic, and it has a non-monotonic nature. Several approaches have been proposed to reduce or compile the normative IF/THEN conditional. However, in general, as discussed by [13, 8], they suffer from some limitations; for example, the translation to classical propositional logic requires complete knowledge (for any atomic proposition, we have to determine whether it is true or not), it is not resilient to contradictions, and changes to the norms might require a complete rewriting of the translation.

In this work, we are going to examine how to provide an effective and constructive non-monotonic interpretation of (a restricted version of) L4 based on Answer Set Programming (ASP) meta-program. The meta-program gives the semantics of the underlying L4 constructs as well as a computational framework for them.

GOVERNATORI, Guido and WONG, Meng Weng (HUANG Mingrong). Defeasible semantics for L4. (2023). POPL ProLaLa 2023.

Compliance through Model Checking

Author(s): Avishkar MAHAJAN, STRECKER Martin, Seng Joe WATT, Meng Weng (HUANG Mingrong) WONG, Singapore Management University

In this short note, we describe part of a case study about Singapore’s Personal Data Protection Act, which we first presented informally, then formally as interacting Timed Automata. From these, we derive desiderata on a language and verification framework for reasoning about compliance.

MAHAJAN, Avishkar; STRECKER Martin; WATT, Seng Joe; and WONG, Meng Weng (HUANG Mingrong). Compliance through model checking. (2022). International Workshop on AI Compliance Mechanism WAICOM 2022.

Automating Defeasible Reasoning in Law

Author(s): How Khang LIM, Singapore Management University, Avishkar MAHAJAR, Singapore Management University, Martin STRECKER, Meng Weng WONG, Singapore Management University

The paper studies defeasible reasoning in rule-based systems, in particular about legal norms and contracts. We identify rule modifiers that specify how rules interact and how they can be overridden. We then define rule transformations that eliminate these modifiers, leading in the end to a translation of rules to formulas. For reasoning with and about rules, we contrast two approaches, one in a classical logic with SMT solvers, which is only briefly sketched, and one using non-monotonic logic with Answer Set Programming solvers, described in more detail.

LIM, How Khang; MAHAJAR, Avishkar; STRECKER, Martin; and WONG, Meng Weng. Automating defeasible reasoning in law with answer set programming. (2022). ICLP 2022: Proceedings of the International Conference on Logic Programming 2022 Workshops: Haifa, Israel, 31 July - 1 August: Workshop on Goal-Directed Execution of Answer Set Programs 2nd GDE 2022, August 1. 1-11.