Recent rapid advances in Artificial Intelligence (AI) and Machine Learning have raised many questions about the regulatory and governance mechanisms for autonomous machines. Many commentators, scholars, and policy-makers now call for ensuring that algorithms governing our lives are transparent, fair, and accountable. Here, I propose a conceptual framework for the regulation of AI and algorithmic systems. I argue that we need tools to program, debug and maintain an algorithmic social contract, a pact between various human stakeholders, mediated by machines. To (...) achieve this, we can adapt the concept of human-in-the-loop (HITL) from the fields of modeling and simulation, and interactive machine learning. In particular, I propose an agenda I call society-in-the-loop (SITL), which combines the HITL control paradigm with mechanisms for negotiating the values of various stakeholders affected by AI systems, and monitoring compliance with the agreement. In short, ‘SITL = HITL + Social Contract.’. (shrink)

Argumentation is a very fertile area of research in Artificial Intelligence, and various semantics have been developed to predict when an argument can be accepted, depending on the abstract structure of its defeaters and defenders. When these semantics make conflicting predictions, theoretical arbitration typically relies on ad hoc examples and normative intuition about what prediction ought to be the correct one. We advocate a complementary, descriptive-experimental method, based on the collection of behavioral data about the way human reasoners handle these (...) critical cases. We report two studies applying this method to the case of reinstatement (both in its simple and floating forms). Results speak for the cognitive plausibility of reinstatement and yet show that it does not yield the full expected recovery of the attacked argument. Furthermore, results show that floating reinstatement yields comparable effects to that of simple reinstatement, thus arguing in favor of preferred argumentation semantics, rather than grounded argumentation semantics. Besides their theoretical value for validating and inspiring argumentation semantics, these results have applied value for developing artificial agents meant to argue with human users. (shrink)

In multi-agent systems (MAS), abstract argumentation and argumentation schemes are increasingly important. To be useful for MAS, argumentation schemes require a computational approach so that agents can use the components of a scheme to construct and present arguments and counterarguments. This paper proposes a syntactic analysis that integrates argumentation schemes with abstract argumentation. Schemes can be analysed into the roles that propositions play in each scheme and the structure of the associated propositions, yielding a greater understanding of the schemes, a (...) uniform method of analysis, and a systematic means to relate one scheme to another. This analysis of the schemes helps to clarify what is needed to provide denotations of the terms and predicates in a semantic model. (shrink)

Firewalls are an important tool in the assurance of network security. Packet filtering firewalls are configured by providing a set of rules that identify how to handle individual data packets that arrive at the firewall. In large firewall configurations, conflicts may arise between these rules. Argumentation provides a way of handling conflicts such that their origin is illuminated, and hence can help a system administrator understand the effects of a given configuration. To show how argumentation might help in this domain (...) we examine the use of a system of metalevel argumentation for firewall configuration, showing how it makes conflicts and their origins clear, and showing how different instantiations of a metalevel argumentation system provide alternative ways to resolve conflicts. (shrink)

Models of deliberative dialogue are fundamental for developing autonomous systems that support human practical reasoning. The question discussed in this paper is whether existing models are able to capture the complexity and richness of natural deliberation. In real-world contexts, circumstances relevant to the decision can change rapidly. We reflect on today’s leading model of deliberation dialogue and we propose an extension to capture how newly exchanged information about changing circumstances may shape the dialogue. Moreover, in natural deliberation, a dialogue may (...) be successful even if a decision on what to do has not been made. A set of criteria is proposed to address the problem of when to close off the practical reasoning phase of dialogue. We discuss some measures for evaluating the success of a dialogue after closure and we present some initial efforts to introduce the new deliberation features within an existing model of agent dialogue. We believe that our extended model of dialogue may contribute to representing that richness of natural deliberative dialogue that is yet to be addressed in existing models of agent deliberation. (shrink)

Cybernetics, or self-governance of animal and machine, requires the ability to sense the world and to act on it in an appropriate manner. Likewise, self-governance of a human society requires groups of people to collectively sense and act on their environment. I argue that the evolution of political systems is characterized by a series of innovations that attempt to solve two ‘scalability’ problems: scaling up a group’s ability to make sense of an increasingly complex world, and to cooperate in increasingly (...) larger groups. I then explore some recent efforts toward using the Internet and social media to provide alternative means for addressing these scalability challenges, under the banners of crowdsourcing and computer-supported argumentation. I present some lessons from those efforts about the limits of technology, and the research directions more likely to bear fruit. (shrink)

Over the past decade or so, a new interdisciplinary field has emerged in the ground between, on the one hand, computer science – and artificial intelligence in particular – and, on the other, the area of philosophy concentrating on the language and structure of argument. There are now hundreds of researchers worldwide who would consider themselves a part of this nascent community. Various terms have been proposed for the area, including "Computational Dialectics," "Argumentation Technology," and "Argument-based Computing," but the term (...) that has stuck is simply Argument & Computation. It encompasses several specific strands of research, such as: . the use of theories of argument, and dialectic in particular, in the design and implementation of protocols for multi-agent action and communication; . the application of theories of argument and rhetoric in natural language processing and affective computing; . the use of argument-based structures for autonomous reasoning in artificial intelligence, and in particular, for defeasible reasoning; . computer-supported collaborative argumentation – the implementation of software tools for enabling online argument in domains such as education and e-government. These strands come together to form the core of a research field that covers parts of artificial intelligence (AI), philosophy, linguistics, and cognitive science, but, increasingly, is building an identity of its own. (shrink)

The importance of negotiation has increased in the last years as a relevant interaction to solve conflicts in multi-agent systems. Although there are many different scenarios, a typical negotiating situation involves two cooperative agents that cannot reach their goals by themselves because they do not have some resources needed to reach such goals. Therefore, a way to improve their mutual benefit is to start a negotiation dialogue, taking into account that they might have incomplete or incorrect beliefs about the other (...) agent’s goals and resources. The exchange of arguments during the negotiation gives them information that makes it possible to update their beliefs and consequently they can offer proposals which are closer for reaching a deal. In order to formalize their proposals in a negotiation setting, the agents must be able to generate, select and evaluate arguments associated with such offers, updating their mental state accordingly. We situate our work on this kind of scenarios with two argumentation-based negotiation agents equipped with belief revision operations in the generation and interpretation of arguments. It has been proved that those agents that take advantage of belief revision during the negotiation achieve an overall better performance. Because the belief revision process depends on the information the agents exchange in their utterances, in this paper we focus on different communication strategies the agents may implement and the impact that they have in the negotiation process. For this purpose, we present a negotiation protocol where the messages are extended to include a critique to the last proposal received and a counterproposal. Also, we define proposals that may be more or less informative containing different justifications. An intentional agent architecture is proposed and following this model different kind of negotiating agents are created using diverse communication strategies. To assess the impact these strategies have in the negotiation process some simulations are conducted, analyzing the results obtained. (shrink)

In this paper 1 1 This is a version of a paper originally presented at ArgMAS 2014. we address some limitations with proposals concerning an argumentation scheme for practical reasoning grounded on action-based alternating transition systems augmented with values. In particular, we extend the machinery to enable the proper representation of, and ability to reason with, goals. This allows the more satisfactory representation of certain critical questions, and the means to explicitly record differences between agents as to what will count (...) as the fulfillment of goals and the promotion of values. It also allows us to express desires in terms of values, and to make plain the relation between a change in circumstances and the promotion and demotion of values. Three detailed examples are used to illustrate the additional kinds of problem the extensions allow us to consider. (shrink)