A Trembling House of Cards? Mapping Adversarial Attacks against Language Agents

Language agents powered by large language models (LLMs) have seen exploding development. Their capability of using language as a vehicle for thought and communication lends an incredible level of flexibility and versatility. People have quickly capitalized on this capability to connect LLMs to a wide range of external components and environments: databases, tools, the Internet, robotic embodiment, etc. Many believe an unprecedentedly powerful automation technology is emerging. However, new automation technologies come with new safety risks, especially for intricate systems like language agents. There is a surprisingly large gap between the speed and scale of their development and deployment and our understanding of their safety risks. Are we building a house of cards? In this position paper, we present the first systematic effort in mapping adversarial attacks against language agents. We first present a unified conceptual framework for agents with three major components: Perception, Brain, and Action. Under this framework, we present a comprehensive discussion and propose 12 potential attack scenarios against different components of an agent, covering different attack strategies (e.g., input manipulation, adversarial demonstrations, jailbreaking, backdoors). We also draw connections to successful attack strategies previously applied to LLMs. We emphasize the urgency to gain a thorough understanding of language agent risks before their widespread deployment

A “Lawyer for All Seasons”: The Lawyer as Conflict Manager

This interdisciplinary Article explores why interpersonal conflict management principles and skills are essential to good lawyering and, thus, why law schools should teach these principles and skills to all their students. In demonstrating the immense practical value an understanding of interpersonal conflict management principles and skills have in the practice of law, this Article examines case studies involving organizations that have dramatically reduced legal costs, among other benefits, by abandoning a solely legalistic approach to conflict and embracing conflict management principles. The lessons learned from these studies and the interpersonal conflict management principles that underlie them support the idea that the legal profession’s transformation from one that emphasizes a narrower legalistic approach to one that embraces a broader conflict management approach applies to all lawyers and benefits all clients

Shifting the culture and design of complaints systems: Participation, reflexivity and ethics

This thesis comprises of a critical appraisal evaluating the collective contribution to knowledge of six of my peer reviewed publications in relation to how participatory, reflexive and ethical approaches to complaints can create a complaint systems culture that supports all actors affected by complaints and ensure greater accountability for learning. By adopting a constructionist approach to complaints, the appraisal draws attention to the negativity associated with complaints and the tension within complaints handling where parties to the disputes have different versions of truth and subjectivity and perspectivism play a part. Using a lens informed by critical theory and reflexivity, key learnings generated from these publications relate to the impact of power asymmetries on complaints including institutionalisation and gender. The critical appraisal goes on to develop a conceptual framework that situates complaints within conditions of power, subjectivity and underpinning values and highlights the importance of participation, reflexivity and ethics in giving agency to the parties affected by complaints. It argues that this can lead to greater accountability for learning, recognising that resolving complaints can involve different perspectives, multiple and complex issues and the answer is unlikely to be binary. Implications for practice include the fact that that the framework is a firm reminder of the role that consumer ADR, complaint systems and complaint handlers have in addressing power differentials. Further, that in order to facilitate participation, reflexivity and ethics complaint system designers may require collaborative approaches qualitatively different than some complaint systems in the UK currently accommodate

A Lawyer for All Seasons : The Lawyer as Conflict Manager

This interdisciplinary Article explores why interpersonal conflict management principles and skills are essential to good lawyering and, thus, why law schools should teach these principles and skills to all their students. In demonstrating the immense practical value an understanding of interpersonal conflict management principles and skills have in the practice of law, this Article examines case studies involving organizations that have dramatically reduced legal costs, among other benefits, by abandoning a solely legalistic approach to conflict and embracing conflict management principles. The lessons learned from these studies and the interpersonal conflict management principles that underlie them support the idea that the legal profession?s transformation from one that emphasizes a narrower legalistic approach to one that embraces a broader conflict management approach applies to all lawyers and benefits all clients

How Do Complainants Experience the Ombuds Procedure? Detecting cultural patterns of disputing behavior: A comparative analysis of users that complain about financial services

Are systems we use for resolving disputes designed in a user-friendly manner? What motivates us to accept a decision handed down by an ombuds? There is scant empirical evidence to help understand what users of ombuds expect from them and what informs these expectations. Yet, in a recent wide-ranging study Creutzfeldt (2016) asked people who had just been through an ombuds procedure about precisely these issues. Exploring the importance of fairness perceptions for ombuds procedures, one of the findings of the project was that decision-acceptance (and trust) was linked to users being heard, having a voice, and especially their “first impressions” of the ombuds. Does this finding hold true across different jurisdictions, though? By focusing on users of the German insurance ombuds (Versicherungsombudsmann) and the Financial Ombudsman Services (FOS) in the UK, this chapter will explore how procedural justice matters in different ways in different legal cultures. The data reveal culturally distinct narratives about expectations towards ombuds, which we suggest is partially a result of the different legal socialization experiences of people in Germany and the UK. Having identified patterns within the private sector, lessons learned for the public sector are discussed. We conclude this chapter with some thoughts as to how this study might direct future understandings of user experience and future research

Redressing grievances and complaints regarding basic service delivery

Redress procedures are important for basic fairness. In addition, they can help address principal-agent problems in the implementation of social policies and provide information to policy makers regarding policy design. To function effectively, a system of redress requires a well-designed and inter-linked supply of redress procedures as well as, especially if rights consciousness is not well-developed in a society, a set of organizations that stimulate and aggregate demand for redress. On the supply side, this paper identifies three kinds of redress procedures: administrative venues within government agencies, independent institutions outside government departments, and courts. On the demand side, the key institutions are nongovernmental organizations/civil society organizations and the news media, both of which require a receptive political and economic climate to function effectively. Overall, procedures for redressing grievances and complaints regarding basic service delivery are under-developed in many countries, and deserve further analysis, piloting, and support.Public Sector Corruption&Anticorruption Measures,Corruption&Anticorruption Law,Public Sector Regulation,Health Monitoring&Evaluation,Governance Indicators

Interpretability of AI in Computer Systems and Public Policy

Advances in Artificial Intelligence (AI) have led to spectacular innovations and sophisticated systems for tasks that were thought to be capable only by humans. Examples include playing chess and Go, face and voice recognition, driving vehicles, and more. In recent years, the impact of AI has moved beyond offering mere predictive models into building interpretable models that appeal to human logic and intuition because they ensure transparency and simplicity and can be used to make meaningful decisions in real-world applications. A second trend in AI is characterized by important advancements in the realm of causal reasoning. Identifying causal relationships is an important aspect of scientific endeavors in a variety of fields. Causal models and Bayesian inference can help us gain better domain-specific insight and make better data-driven decisions because of their interpretability. The main objective of this dissertation was to adapt theoretically sound AI-based interpretable data-analytic approaches to solve domain-specific problems in the two un-related fields of Storage Systems and Public Policy. For the first task, we considered the well-studied problem of cache replacement problem in computing systems, which can be modeled as a variant of the well-known Multi-Armed Bandit (MAB) problem with delayed feedback and decaying costs, and developed an algorithm called EXP4-DFDC. We proved theoretically that EXP4-DFDC exhibits an important feature called vanishing regret. Based on the theoretical analysis, we designed a machine-learning algorithm called ALeCaR, with adaptive hyperparameters. We used extensive experiments on a wide range of workloads to show that ALeCaR performed better than LeCaR, the best machine learning algorithm for cache replacement at that time. We concluded that reinforcement machine learning can offer an outstanding approach for implementing cache management policies. For the second task, we used Bayesian networks to analyze the service request data from three 311 centers providing non-emergency services in the cities of Miami-Dade, New York City, and San Francisco. Using a causal inference approach, this study investigated the presence of inequities in the quality of the 311 services to neighborhoods with varying demographics and socioeconomic status. We concluded that the services provided by the local governments showed no detectable biases on the basis of race, ethnicity, or socioeconomic status