Toward Self-Aware Robots

Ironies of artificial intelligence

Bainbridge's Ironies of Automation was a prescient description of automation related challenges for human performance that have characterised much of the 40 years since its publication. Today a new wave of automation based on artificial intelligence (AI) is being introduced across a wide variety of domains and applications. Not only are Bainbridge's original warnings still pertinent for AI, but AI's very nature and focus on cognitive tasks has introduced many new challenges for people who interact with it. Five ironies of AI are presented including difficulties with understanding AI and forming adaptations, opaqueness in AI limitations and biases that can drive human decision biases, and difficulties in understanding the AI reliability, despite the fact that AI remains insufficiently intelligent for many of its intended applications. Future directions are provided to create more human-centered AI applications that can address these challenges.

Artificial intelligence in conservative dentistry and endodontics: A game-changer

Artificial intelligence (AI) technology has mostly been used by dental practitioners to diagnose problems, plan treatments, make clinical judgments, and predict outcomes. In endodontics, convolutional neural networks and artificial neural networks, two types of (AI) models, have been used to study the anatomy of the root canal system, measure the length of root canal, identify periapical pathology and root fractures, prediction of success of retreatment procedures, and dental pulp stem cells viability. The goal of this review is to assess AI's role in conservative dentistry and endodontics.

The Prospects of Artificial Consciousness: Ethical Dimensions and Concerns

Can machines be conscious and what would be the ethical implications? This article gives an overview of current robotics approaches toward machine consciousness and considers factors that hamper an understanding of machine consciousness. After addressing the epistemological question of how we would know whether a machine is conscious and discussing potential advantages of potential future machine consciousness, it outlines the role of consciousness for ascribing moral status. As machine consciousness would most probably differ considerably from human consciousness, several complex questions must be addressed, including what forms of machine consciousness would be morally relevant forms of consciousness, and what the ethical implications of morally relevant forms of machine consciousness would be. While admittedly part of this reflection is speculative in nature, it clearly underlines the need for a detailed conceptual analysis of the concept of artificial consciousness and stresses the imperative to avoid building machines with morally relevant forms of consciousness. The article ends with some suggestions for potential future regulation of machine consciousness.

Telehealth and Artificial Intelligence Insights into Healthcare during the COVID-19 Pandemic

Soon after the coronavirus disease 2019 pandemic was proclaimed, digital health services were widely adopted to respond to this public health emergency, including comprehensive monitoring technologies, telehealth, creative diagnostic, and therapeutic decision-making methods. The World Health Organization suggested that artificial intelligence might be a valuable way of dealing with the crisis. Artificial intelligence is an essential technology of the fourth industrial revolution that is a critical nonmedical intervention for overcoming the present global health crisis, developing next-generation pandemic preparation, and regaining resilience. While artificial intelligence has much potential, it raises fundamental privacy, transparency, and safety concerns. This study seeks to address these issues and looks forward to an intelligent healthcare future based on best practices and lessons learned by employing telehealth and artificial intelligence during the COVID-19 pandemic.

Autopoiesis and Its Efficacy—A Metacybernetic View

This paper seeks to explain the nature of autopoiesis and its capacity to be efficacious, and to do this, it uses agency theory as embedded in metacybernetics. Agency, as a generalised intelligent adaptive living system, can anticipate the future once it has internalised a representation of an active contextual situation through autopoiesis. The role of observation and the nature of internalisation will be discussed, explaining that the latter has two states that determine agency properties of cognition. These are assimilation and accommodation. Assimilation is an information process and results in implicit cognition and recognition, whereas accommodation uses assimilated information delivering explicit cognition, recognition, and conscious awareness with rationality. Similarly, anticipation, a required property of the living, has two states, weak and strong, and these correspond to the two states of internalisation. Autopoiesis has various properties identifiable through the lenses of three autonomous but configurable schemas: General Collective Intelligence (GCI), Eigenform, and Extreme Physical Information (EPI). GCI is a pragmatic evolutionary approach concerned with a contextually connected purposeful and relatable set of task processes, each undertaken by a team of subagencies seeking collective fitness. Eigenform is a symbolic approach that is concerned with how observations can be suitably internalised and thus be used as a token to determine future behaviour, and how that which has been internalised can be adopted to anticipate the future. Extreme Physical Information (EPI) is an empirical approach concerned with acquiring information through observation of an unknown parameter through sampling regimes. The paper represents the conceptualisations of each schema in terms of autopoietic efficacy, and explores their configurative possibilities. It will adopt the ideas delivered to enhance explanations of the nature of autopoiesis and its efficacy within metacybernetics, providing a shift in thinking about autopoiesis and self-organisation.

On the Design of Social Robots Using Sheaf Theory and Smart Contracts

The incorporation of robots in the social fabric of our society has taken giant leaps, enabled by advances in artificial intelligence and big data. As these robots become increasingly adept at parsing through enormous datasets and making decisions where humans fall short, a significant challenge lies in the analysis of robot behavior. Capturing interactions between robots, humans and IoT devices in traditional structures such as graphs poses challenges in the storage and analysis of large data sets in dense graphs generated by frequent activities. This paper proposes a framework that uses the blockchain for the storage of robotic interactions, and the use of sheaf theory for analysis of these interactions. Applications of our framework for social robots and swarm robots incorporating imperfect information and irrationality on the blockchain sheaf are proposed. This work shows the application of such a framework for various blockchain applications on the spectrum of human-robot interaction, and identifies key challenges that arise as a result of using the blockchain for robotic applications.

Robotic assistance for people with dementia: a viable option for the future?

INTRODUCTION

Demographic changes in society and fewer personnel working in healthcare services have resulted in an increase in the speed of development of safe, reliable robotic assistance technologies for patients with neurological diseases. This paper aims to advocate for the frailty of patients in light of the economic need for robotic assistance, discuss potential hazards, and outline related factors that influence positive outcomes.

AREAS COVERED

This article reviews the state of the art and perspectives regarding the use of robotics in older adults with dementia. We focus on current trends in the development of robotic technologies for these patients and discuss the potential hazards associated with the implementation of such cutting-edge technology in daily practice.

EXPERT OPINION

We envisage a gradual increase in the usage of robot-based devices for the management and support of patients with cognitive deficits. In particular, the introduction of artificial intelligence will enhance the functionality of these technologies, but also increase potential hazards resulting from human-robot interactions. The development of such technology must consider whether neurological syndromes are static or progressive. Progressive syndromes pose the biggest challenge since the functionality of robotic devices must adapt to patients changing cognitive and motor performance profiles.