One Hundred Year Study on Artificial Intelligence (AI100)

This report is the first in a series to be issued at regular intervals as a part of the One Hundred Year Study on Artificial Intelligence (AI100). Starting from a charge given by the AI100 Standing Committee to consider the likely influences of AI in a typical North American city by the year 2030, the…

Assessing the Risk of Artificial Intelligence

One sector that saw the huge disruptive potential of AI from an early stage is the military. The weaponization of AI will represent a paradigm shift in the way wars are fought, with profound consequences for international security and stability. Serious investment in autonomous weapon systems (AWS) began a few years ago; in July 2016…

Case-based Recommender Systems

We describe recommender systems and especially case-based recommender systems. We define a framework in which these systems can be understood. The framework contrasts collaborative with case-based, reactive with proactive, single-shot with conversational, and asking with proposing. Within this framework, we review a selection of papers from the case-based recommender systems literature, covering the development of…

Emergent case-based reasoning applications

The basic principle underpinning case-based reasoning (CBR) is that new problems can be solved by reusing solutions to past problems. The generality of this idea means that CBR is finding application in a wide variety of areas. The special advantage of CBR is that a case can be a very convenient means of capturing knowledge,…

Case-Based Reasoning Systems in the Health Sciences: A Survey of Recent Trends and Developments

The health sciences are, nowadays, one of the major application areas for case-based reasoning (CBR). The paper presents a survey of recent medical CBR systems based on a literature review and an e-mail questionnaire sent to the corresponding authors of the papers where these systems are presented. Some clear trends have been identified, such as…

A novel modification of the Turing test for artificial intelligence and robotics in healthcare

BACKGROUND: The increasing demands of delivering higher quality global healthcare has resulted in a corresponding expansion in the development of computer-based and robotic healthcare tools that rely on artificially intelligent technologies. The Turing test was designed to assess artificial intelligence (AI) in computer technology. It remains an important qualitative tool for testing the next generation…

A Conceptual and Computational Model of Moral Decision Making in Human and Artificial Agents

Recently, there has been a resurgence of interest in general, comprehensive models of human cognition. Such models aim to explain higher-order cognitive faculties, such as deliberation and planning. Given a computational representation, the validity of these models can be tested in computer simulations such as software agents or embodied robots. The push to implement computational…

AIonAI: A Humanitarian Law of Artificial Intelligence and Robotics

The enduring progression of artificial intelligence and cybernetics offers an ever-closer possibility of rational and sentient robots. The ethics and morals deriving from this technological prospect have been considered in the philosophy of artificial intelligence, the design of automatons with roboethics and the contemplation of machine ethics through the concept of artificial moral agents. Across…

Architectures and Ethics for Robots

The goal of this chapter is to propose constraint satisfaction as a central design concept for intelligent robots. Some proposals for codes of robot ethics apparently presuppose the existence of certain technical abilities on behalf of the robot designer that, simply put, do not yet exist. Namely, given current robot design techniques, it is usually…

Concept learning as motor program induction: A large-scale empirical study

Human concept learning is particularly impressive in two respects: the internal structure of concepts can be representationally rich, and yet the very same concepts can also be learned from just a few examples. Several decades of research have dramatically advanced our understanding of these two aspects of concepts. While the richness and speed of concept…

Effects of etiquette strategy on human–robot interaction in a simulated medicine delivery task

The objective of this study was to examine the extent to which a model of linguistic etiquette in human–human interaction could be applied to the human–robot interaction (HRI) domain, and how different etiquette strategies proposed through the model might influence performance of humans and robots as mediated by manipulations of robot physical features in a…

Human-level concept learning through probabilistic program induction

People learning new concepts can often generalize successfully from just a single example, yet machine learning algorithms typically require tens or hundreds of examples to perform with similar accuracy. People can also use learned concepts in richer ways than conventional algorithms—for action, imagination, and explanation. We present a computational model that captures these human learning…

Real-time inference of mental states from facial expressions and upper body gestures

We present a real-time system for detecting facial action units and inferring emotional states from head and shoulder gestures and facial expressions. The dynamic system uses three levels of inference on progressively longer time scales. Firstly, facial action units and head orientation are identified from 22 feature points and Gabor filters. Secondly, Hidden Markov Models…

Towards Modeling Morality Computationally with Logic Programming

We investigate the potential of logic programming (LP) to model morality aspects studied in philosophy and psychology. We do so by identifying three morality aspects that appear, in our view, amenable to computational modeling by appropriately exploiting LP features: the dual-process model (reactive and deliberative) in moral judgments; justification of moral judgments by contractualism; and…

Towards the automatic detection of spontaneous agreement and disagreement based on nonverbal behaviour: A survey of related cues, databases, and tools

While detecting and interpreting temporal patterns of nonverbal behavioural cues in a given context is a natural and often unconscious process for humans, it remains a rather difficult task for computer systems. Nevertheless, it is an important one to achieve if the goal is to realise a naturalistic communication between humans and machines. Machines that…

User-robot personality matching and assistive robot behavior adaptation for post-stroke rehabilitation therapy

This paper describes a hands-off, socially assistive therapist robot designed to monitor, assist, encourage, and socially interact with post-stroke users engaged in rehabilitation exercises. We investigate the role of the robot’s personality in the hands-off therapy process, focusing on the relationship between the level of extroversion–introversion of the robot and the user. We also demonstrate…

Governing Lethal Behavior: Embedding Ethics in a Hybrid Deliberative/Reactive Robot Architecture

This article provides the basis, motivation, theory, and design recommendations for the implementation of an ethical control and reasoning system potentially suitable for constraining lethal actions in an autonomous robotic system so that they fall within the bounds prescribed by the Laws of War and Rules of Engagement. It is based upon extensions to existing…