Ronald Prescott Loui

A history of AI and Law in 50 papers: 25 years of the international conference on AI and Law

We provide a retrospective of 25xa0years of the International Conference on AI and Law, which was first held in 1987. Fifty papers have been selected from the thirteen conferences and each of them is described in a short subsection individually written by one of the 24 authors. These subsections attempt to place the paper discussed in the context of the development of AI and Law, while often offering some personal reactions and reflections. As a whole, the subsections build into a history of the last quarter century of the field, and provide some insights into where it has come from, where it is now, and where it might go.

An ontology for active and passive aerial drone threat automatic plan recognition

This paper initiates a discussion on the design of terms, features, and descriptors that would support machine learning for automated plan recognition of drone and drone swarms engaged in threatening activity. A few prototype aerial missions for drones are discussed and semantic markers, such as distance and line of sight to potential targets, mirrored motion, path and position optimality, coordination, and formation, are noted. This semantic description of motion in terms of objectives and capabilities contrasts with a naïve description of motion in a 3d coordinate system without reference to targets; terminology is the first step in automated anomaly detection analytics. The paper further discusses active plan recognition, which selects interventions in order to force the drone or swarm to reveal its intentions. Analogies to, and distinctions from, two-dimensional active plan discernment, e.g., stalking, tailing, pursuing, and intercepting, are given.

Virtualized dynamic port assignment and windowed whitelisting for securing infrastructure servers

We describe a novel method of securing services by adding windowed whitelisting to an arbitrary and constantly changing assignment of services to ports (or virtual ports). This is aimed at mitigating port scanning threats and unauthorized intrusion attempts, and to protect a community of known users from data loss. In essence, port numbers, time, and IP address will be used as part of the password/access mechanism; this segregates traffic so that content-based restrictions can be more effective. It also provides a connection-based security wrapper for services that might be vulnerable to software exploits, such as the buffer overruns and backdoors. The method requires a portal to authenticate users and disseminate knowledge of the current port assignment, in addition to permitting users to request a “window” of time to be white-listed. It requires a firewall with dynamic port and whitelist reconfigurability. The method is intended to enhance byte frequency histogram analysis and regexp restriction of traffic. It also requires a policy for keeping alive long-lasting connections. It can be implemented easily with virtual ports using redirection. We discuss some implications for web page rewriting and cgi security, as well as legacy services such as ssh and sftp. The effect is to create a cross-product of IP range, port range, and time specificity, to create a large and sparse search space for any adversary.

From Berman and Hafner's teleological context to Baude and Sachs' interpretive defaults: an ontological challenge for the next decades of AI and Law

This paper revisits the challenge of Berman and Hafner’s “missing link” paper on representing teleological structure in case-based legal reasoning. It is noted that this was mainly an ontological challenge to represent some of what made legal reasoning distinctive, which was given less attention than factual similarity in the dominant AI and Law paradigm, deriving from HYPO. The response to their paper is noted and briefly evaluated. A parallel is drawn to a new challenge to provide deep structure to the legal context of textual meaning, drawing on the forthcoming work of two Constitutional law scholars who appear to place some faith in the ways of thinking that AI and Law has developed.

Investigating a two-way-audio query-response command interface with navigation data extraction for driver assistance

Navigation systems for drivers tend to vocalize what they want, when they want. Drivers who need to clarify instructions are often required to read directions in text form, which is a safety risk during real-time control. Instead, we investigate how a two-way-audio command interface might work. Data is easily extracted from text directions so that questions can be answered without knowledge of the GPS location, as long as the system is aware of the most recently vocalized directional cue (and elapsed time since last utterance). Functions envisioned are as simple as scrolling forward or back through the directions, spelling names or pronouncing differently, repeating the road name or directional change, and saying what is next on command. The queries require modest data extraction with potentially great improvement in usability. Queries may further refer to time and the results of some intermittent internet search, but do not attempt to interpret 2d map data. This project is ongoing, and the contribution includes a novel design architecture that puts a second AI assistant in the co-pilots seat. This design provides domain-specific memory and vocalization assistance on top of the navigational assistance already familiar to the driver: voice AI (vAI) for improved voice UI (vUI). It aims more for a smart TiVo than co-pilot Siri. When navigation assistance and two-way audio dialogue are provided by the same vendor, the audio recognition and current location errors can be significantly reduced, but the current design is intended as a third-party intervention, adding assistance where the original product is lacking and possibly creating pressure for their products to improve.

Digital flight plans for server access control: Restricting anomalous activity with path-based declarations of intentions

In response to increasing threats of malicious activity and data loss on servers, we propose a different and practical strategy for access control modeled after flight plans for pilots, which mixes existing role-based, object-based, and intention-based access models; it supports much finer grained, real-time, sequence-oriented anomaly detection. Users are required to declare their intended “flight path” in advance, a sketch of resource use: this may vary in detail, but could include database tables, file system directories, byte and bandwidth limits, use of encryption and archive creation, command sets, connection time, number and origin of connections, and ports. Sequence information provides especially strong constraint, even if it incomplete. We find an important place for active, on-line human sampling of flight plans, as well as pre-authorization for non-standard paths, and alerts for deviation from path. We also find a place for improved user profiling and a paradigm shift from ex-post log-based reconstruction of user activity to ex-ante declaration.

How to Survive a Cyber Pearl Harbor

An examination of parallels between the Day of Infamy and a major cyberattack reveals lessons for organizations about vulnerability, the nature of survival, and the tenets of protection that can help boost resilience against hackers and other cyberthreats.

Auralization of process and port status using program binaries to generate semantically meaningful non-fatiguing noise as canonical sound signals

We describe using auralization to monitor process stack and netstat status on a server or small group of servers. Using the auditory channel is especially useful for monitoring because it can be done without taking much attention. Our contribution is to suggest generating noise-like sounds that more naturally fade into the background, and are less fatiguing over long monitoring sessions. Although our noises are not musically or tonally interesting, they are nevertheless semantically identifiable and succeed in indicating changes of state.

An Easily Adopted Markup Discipline for Annotating Electronic Medical Records with Ontological and Epistemological Qualification: Toward Disciplined Asterisks, Parentheticals, Marginalia, Footnotes, and Hashtags

Structured data and controlled vocabularies in medical records are common goals, but widespread and eager clinical adoption might require more modest, incremental change. One small step along the path to structured data is a voluntary discipline of annotation, supported by simple, user-friendly, dynamic text affordances. A second step is to discipline the meta-vocabulary rather than the clinical vocabulary: one can target the epistemological attitudes (probability, degree of uncertainty, pedigree of claims) and ontological criteria (fuzziness or vagueness, version of definition, reporting standard) for optional mark up, and even plain text can support disciplined annotation. The methods seem especially useful for summary views of patient records that have multiple authors, contributing at different times, using various criteria. The methods may also support more nuanced outcomes research and reporting, and aid transitions between policies, regulations, and billing codes. It may be too difficult to impose ontologies on so many different participants in medical record-keeping, all at once, with little room for customization. A more organic, evolutionary path to the same end starts with the smaller step of asking medical records keepers to settle on the common annotations. Even as a crowd-sourced meta-language takes shape, the freedom to use epistemic and ontological qualifiers makes controlled terminologies and vocabularies, with discrete and structured data, easier to live with.

What if intraverted women tend to dislike Java and object oriented programming

We consider the strong possibility that extraverted and intraverted women differ on preference for some aspects of programming, and how this difference might be more significant than its expression among men. We discuss the reasons why we are moved to design a new study confirming a gender-specific relation of Myers-Briggs personality types to programming paradigms and specific language features. We discuss the implications of a significant gender difference on representation in industry, advancement in profession, and curriculum design. We invite hypotheses that explain a significant difference. Past classroom questionnaires and future questions will be shown (but not data, since we are bound by IRB rules not to report them), as well as method of analysis and test for robustness in subcategories. We have a specific method for mitigating ambiguity and non-repeatability in Myers-Briggs type determination. Our cohort is expected to include about 500 Masters students per year, most from the same region in India, with about 25% women respondents, if we sample at past rates.