Conflict Resolution and its Context

Conflicts emerge naturally and daily from our constant social interactions. While conflicts exist also in other species, the more refined ways we Humans have to resolve them is one of the things that distinguishes us. Conflicts and approaches to their resolution have indeed evolved significantly over time, with technology providing a valuable contribution in the last decades. Artificial Intelligence, in particular, has been providing this field with new approaches to old problems, alleviating the work of legal practitioners and the participation of the parties in such procedures. This book covers these issues in some detail, touching aspects such as the definition of software architectures for conflict resolution platforms or the several ways in which sub-fields of Artificial Intelligence can improve conflict resolution. A particular emphasis is placed on the analysis of the behavior of the parties and their context to better frame the conflict and enrich the decision-making process. This first chapter provides an overview of the topic and of the book.

The existence of conflicts is universal, old and indissoluble from our sense of civilized and evolved species. Since conflicts must be seen as natural and inevitable, focus should be placed on efficient ways to avoid and solve them. This chapter introduces the notion of conflict and its different shapes. It moves on to introduce the two main approaches to conflict resolution: litigation in the courtroom and alternative methods. The advantages and disadvantages of each one are presented, with the latter being detailed in its different forms. The chapter highlights the need for alternative approaches in face of the current disadvantages of litigation, namely in what concerns its inefficiency. However, its alternatives are also not without disadvantages. These are hence also analyzed in detail. Specifically, a first view on the drawbacks of current online alternatives is put forward in what concerns the lack of the contextual richness of face-to-face interaction. This lays the ground for the following chapters.

Currently, there are two main trends from which parties involved in a conflict can choose to resolve it. On the one hand, parties can choose to initiate a litigation process in a courtroom, making their stands before a judge or a jury and having these establishing an outcome. On the other hand, parties can go for alternative approaches such as negotiation, mediation or arbitration, either in their traditional forms or through an electronic mean, with the assurance that they will undergo a more flexible process, with emphasis on building empathy and searching for mutually satisfactory solutions. This chapter focuses particularly on these alternative means: their advantages and their disadvantages. It does so in a systematic manner, pointing out the current causes for the identified problems and ending with the enumeration of a series of potential solutions for these problems. One particular issue addressed is the one of Media Richness and how the current lean communication means are hindering conflict resolution processes conducted online. The solutions pointed out will be addressed individually in the upcoming chapters.

Artificial Intelligence is currently an umbrella for a wide range of scientific sub-fields, with application domains that span many different areas such as aviation, city planning, traffic management or disease diagnosis, just to name a few. Knowledge-based domains are especially suited to be dealt with by approaches from Artificial Intelligence that enable to learn, infer or reason in an automated way. Thus, the intersection of Artificial Intelligence and The Law comes as no surprise. This chapter is dedicated to this intersection. It starts by analyzing a large number of classical Artificial Intelligence sub-fields, pointing out how each one can or could improve the current state of affairs in conflict resolution. Then, it focuses on one particularly interesting yet unexplored sub-field: Ambient Intelligence. A scenario of its potential uses is laid out that clearly points out the innovation considered. The chapter ends with a critical analysis of the current state of affairs in the intersection of Artificial Intelligence and The Law.

Contextual factors allow us to fully grasp an event, situation, communication process or action. Frequently, the context in which an event takes place provides more valuable information than the event itself. This chapter addresses context and its importance from a general perspective and in the particular domain of conflict resolution. It describes many different contextual dimensions such as the verbal, social or cultural, pointing out the importance of each one to understand individuals’ actions. It then moves on to the address the recent field of Context-aware Computing: the vision of computers that are sensible to contextual cues, harness it and use such information to provide better services. Several context-aware solutions are described in this chapter that point out the range of application domains. However, no such application exists in the domain of conflict resolution. While the next chapters are dedicated do describing the components of such an application, this chapter ends with the enumeration of several contextual dimensions that are of relevance to fully describe a conflict and its resolution process.

As seen in previous chapters, there are currently many different commercial ODR service providers and research projects. It can also be concluded that these systems are rather specific, focused on a single domain, type of conflict or conflict resolution method. These factors constitute some of the reasons that hold back further or faster development of new ODR service providers. Indeed, single-domain or highly-focused ODR tools have markedly fewer potential clients, thus making them less appealing to investors and developers alike. This chapter addresses this specific issue by proposing an architecture that provides ODR services based on abstract concepts and processes: UMCourt. Indeed, many concepts and processes are cross-domain: they have the same meaning independently of the legal domain. They are, however, implemented differently. These different implementations should, nevertheless, be transparent to the users. The architecture described here achieves these objectives by implementing a hierarchic relationship between software agents in which higher-level agents have coordination tasks and lower-level agents implement domain-specific knowledge. The architecture has also the advantage of being easily extensible to additional domains without changes to existing agents.

Retrieval information processes are fairly common in our knowledge-based society. While in the past information retrieval would consist in searching for a book in a library or finding a suitable train schedule, nowadays most information retrieval processes take place through computers and in an online environment. Undeniably, one of the most significant contributors to this trend was Google: a search engine that provided its users with an unprecedented access to all kinds of information. Other less generic information retrieval systems exist, targeting specific fields. In this chapter, one of these specialized information retrieval approaches is described. It targets the field of conflict resolution and provides different methods to compile a wide range of information from past cases and legal rules that include potential outcomes and a measure of their likeliness, boundary values, most likely outcomes, among others. Moreover, it also allows to take past similar cases and adapt them to the context and characteristics of the current case so that parties can have an intuitive and clear notion of what would their chances be if an outcome such as a previous one would result from their dispute.

In a conflict resolution process, several key tasks can be identified that have a preponderant role on its success or failure. Of these, the generation of valid solutions is among the most important. Indeed, parties are often unwilling (as in when they are avoiding the conflict) or unable (when they lack the required skills) to do it. Moreover, in order for the process to be successful, solutions must not only be valid: they must also be consensual, fair and appealing for all the parties. This makes the task harder since parties often disregard each other’s expectation or find it difficult to put themselves in the place of the other and evaluate their proposal from the other’s point of view. This chapter addresses this problem by proposing two different methods to provide support during the actual conflict resolution process by generating solutions. The first one relies on a case-based approach that looks at similarities between past known cases and the current one in order to suggest possible and likely solutions. The second one is meant to be used if the case-based approach fails (e.g. when there are not enough past cases). It is based on genetic algorithms that evolve solutions over successive rounds through the application of genetic operators. It is a much more flexible and domain-independent approach, which allows to explore sometimes unexpected areas of the search space. All in all, these approaches can be incorporated in the midst of a conflict resolution platform such as UMCourt to facilitate the development of dynamic and autonomous conflict resolution processes.

In interpersonal relationships, information about each individual’s state is paramount for a correct interpretation of everyone’s actions and reactions. Some of this information is available to our “eyes” in a face-to-face interaction, including the posture of the body, particular gestures, speech rhythm or the volume of the voice. Other, possibly more accurate information, is slightly more hidden and includes the temperature of our body, the amount of perspiration or the rhythm of our hearth. Alternatively, we can always ask people how they “feel” in each moment. These are the two big approaches available so far to assess one’s state: physiological sensors and questionnaires. In this chapter, we detail the development of an environment that is sensible to its user’s state. It has, however, one particular requirement: access to this information must be non-invasive and non-intrusive. None of the two approaches mentioned are suited. This chapter thus details the development of an environment that fulfills these requirements by integrating concepts from behavioral analysis. The key idea is that if the environment knows how each individual user behaves in a given state, the environment will know how the state of the user from their behaviors. Following this approach, this chapter describes an environment that is not only sensible to the users’ state but that can also influence it to attain some goal of the environment.

Each one of us has a particular way to behave before a conflict. We can assume a cooperative and collaborative attitude or we can behave in a more selfish or competitive way. Given our personality traits or our past experiences, each one has a tendency to behave more towards one or the other. Nonetheless, there are also external factors that influence our conflict handling style including the individuals we are conflicting with, our level of stress or fatigue, the level of escalation of the conflict or even the context or the setting in which it is being settled. Undeniably, the personal conflict resolution style of the parties is preponderant for the outcome of the conflict resolution process. The mediator, while knowing the style of each party, may better conduct the process, namely by pointing out and changing unrealistic, selfish or overly competitive behaviors. Traditionally, the mediator makes use of questionnaires to assess the conflict resolution style of the parties. In this chapter we detail a new view on the problem in which this knowledge is built in real-time, in a non-invasive way, based on the behavior evidenced by the parties during the conflict resolution process. The level of escalation of the conflict is also analyzed similarly, through the non-invasive analysis of the level of stress of the parties during the actual negotiation process. The relationship between stress and the personal conflict handling style is also studied.

Stress is nowadays one of the most serious health-related issues, being even deemed by some as the health epidemic of the century. Many studies have approached stress from different angles, being stress in the workplace and its associated economic costs one of the most studied topics. Nonetheless, stress has consequences that go much further than the economic ones, impacting decision making skills, mood, social relationships, productivity, performance or health. In this line of work, we look at stress as one of the most preponderant factors in decision-making. Excessive stress may lead to poor judgment or hasty decisions while lack of stress may lead to inaction and indecision. For these reasons, stress emerges as an important factor to consider in a conflict resolution scenario, in which the pressure of the proceedings, the unknown potential outcomes or the escalation of emotions may easily result in significant stressful moments. At the same time it must be emphasized the importance of weighted decisions and interpersonal relationships towards a successful outcome: two of the issues that are definitely affected by stress. With such a motivation in mind, in this chapter we describe the approach followed to study stress on the users of technological devices, in a non-intrusive way. We aim to understand how people behave when under stress so that we can incorporate such knowledge in a next generation conflict resolution framework such as UMCourt.

This chapter describes both the performance of the several practical approaches described in the last chapters and the results of the studies conducted to assess individual’s behavior under stress. The chapter starts with an evaluation of the performance of the several information retrieval methods implemented in terms of its efficiency (how fast they perform) and their efficacy (how well they perform). Afterwards it presents some results on the relationship between stress and personal conflict handling style. A significant part of the chapter is then devoted to detailing the results of the studies conducted on stress and its effect on interaction patterns, focusing on several especially interesting features. The performance of the classifiers developed, used to quantify a level of stress in real time, is also detailed. At this point it is still not a critical analysis of the results, which is performed in the following chapter, but rather an objective and statistical view on the data collected. It is concluded that the most affected features are the ones that people do not conscientiously control, such as the acceleration of our gestures or the intensity of the touch. On the other hand, the parameters that are more rational are not influenced in such a significant manner. This can be seen as positive, in the sense that unconscious behaviors and reactions are more difficult to forge and are usually true reactions of the human body. Thus, the results that stem from their analysis are more reliable.

As technological tools find their way into the realms of conflict resolution, the field gains increased complexity. Until a few years ago, conflict resolution would only touch fields such as Psychology, Philosophy, Economy or Law. Now, it also touches a wide range of technological fields that go much further than communication technologies to include Artificial Intelligence and many of its sub-fields. This significantly expands the possible future directions of research which, at the same time, plunges the field in a certain degree of uncertainty. One must, nonetheless, bear in mind that such uncertainty, doubt and suspicion is natural in any revolution and that, at the time, it is a Technological Revolution that we are living. Thus, a significant focus should be placed on analyzing the work carried out so far by researchers and commercial providers in an attempt to draw conclusions that can better guide the future steps. Moreover, these future steps should be guided not only by the technical challenges or the improvement of performance but also by more abstract notions such as fairness and transparency, with a marked concern on ethics. Only this way can the support and trust of significant slices of the society be harnessed, fundamental for the successful implementation and active use of the type of tools described in this book.