What is it about humanity that we can't give away to intelligent machines? A European perspective

One of the most significant recent technological developments concerns the development and implementation of ‘intelligent machines’ that draw on recent advances in artificial intelligence (AI) and robotics. However, there are growing tensions between human freedoms and machine controls. This article reports the findings of a workshop that investigated the application of the principles of human freedom throughout intelligent machine develop- ment and use. Forty IS researchers from ten different countries discussed four contemporary AI and humanity issues and the most relevant IS domain challenges. This article summarizes their experiences and opinions regarding four AI and humanity themes: Crime & conflict, Jobs, Attention, and Wellbeing. The outcomes of the workshop discussions identify three attributes of humanity that need preservation: a critique of the design and application of AI, and the intelligent machines it can create; human involvement in the loop of intelligent ma- chine decision-making processes; and the ability to interpret and explain intelligent machine decision-making processes. The article provides an agenda for future AI and humanity researchpublishedVersio

Underactuated Rehabilitation Robotics for Hand Function

Normal hand function plays an important role in daily life. At present, the incidence of hand dysfunction caused by diseases such as cerebral palsy or stroke is increasing year by year. For the rehabilitation of hand dysfunction, in addition to surgical treatment, effective rehabilitation exercise is also particularly important. It is also a necessary link in the efficient and intelligent development of rehabilitation medicine to develop robots that can effectively help patients with rehabilitation hand functions.In this paper, based on the analysis of the design principles and objectives of the rehabilitation robot with hand function, the kinematics model of the rehabilitation robot with hand function is constructed,based on top-down principle in the design of the machine, the design of the machine hand function rehabilitation robots design optimization process framework, and based on the kinematics model and the virtual prototype technology, build its skeleton model, and carries on the kinematics simulation analysis, the design is verified the correctness of the hand function rehabilitation robot kinematics model

Selected Papers from IEEE ICASI 2019

The 5th IEEE International Conference on Applied System Innovation 2019 (IEEE ICASI 2019, https://2019.icasi-conf.net/), which was held in Fukuoka, Japan, on 11–15 April, 2019, provided a unified communication platform for a wide range of topics. This Special Issue entitled “Selected Papers from IEEE ICASI 2019” collected nine excellent papers presented on the applied sciences topic during the conference. Mechanical engineering and design innovations are academic and practical engineering fields that involve systematic technological materialization through scientific principles and engineering designs. Technological innovation by mechanical engineering includes information technology (IT)-based intelligent mechanical systems, mechanics and design innovations, and applied materials in nanoscience and nanotechnology. These new technologies that implant intelligence in machine systems represent an interdisciplinary area that combines conventional mechanical technology and new IT. The main goal of this Special Issue is to provide new scientific knowledge relevant to IT-based intelligent mechanical systems, mechanics and design innovations, and applied materials in nanoscience and nanotechnology

RLOps:Development Life-cycle of Reinforcement Learning Aided Open RAN

Radio access network (RAN) technologies continue to witness massive growth, with Open RAN gaining the most recent momentum. In the O-RAN specifications, the RAN intelligent controller (RIC) serves as an automation host. This article introduces principles for machine learning (ML), in particular, reinforcement learning (RL) relevant for the O-RAN stack. Furthermore, we review state-of-the-art research in wireless networks and cast it onto the RAN framework and the hierarchy of the O-RAN architecture. We provide a taxonomy of the challenges faced by ML/RL models throughout the development life-cycle: from the system specification to production deployment (data acquisition, model design, testing and management, etc.). To address the challenges, we integrate a set of existing MLOps principles with unique characteristics when RL agents are considered. This paper discusses a systematic life-cycle model development, testing and validation pipeline, termed: RLOps. We discuss all fundamental parts of RLOps, which include: model specification, development and distillation, production environment serving, operations monitoring, safety/security and data engineering platform. Based on these principles, we propose the best practices for RLOps to achieve an automated and reproducible model development process.Comment: 17 pages, 6 figrue

Cognitive Feedback Theories and Artificial Intelligence: A Case for A Grammarly of UI/UX Design

This thesis is concerned with utilizing artificial intelligence and machine learning (AI/ML) techniques and cognitive theories of feedback to enhance learning outcomes in the field of user interface and user experience (UI/UX) design. The capabilities of AI/ML have expanded immensely over the past several years, and it is now being effectively used in software programs like Grammarly, a tool that provides intelligent feedback on writing skills including grammar, tone, and clarity. Grammarly has been uniquely successful as a feedback tool because it relies on lessons from cognitive science regarding student feedback and learning outcomes. Currently, there is no comparable software available for UI/UX, making it a uniquely untapped area for effective learning tools. The question that this thesis attempts to answer, therefore, is: How can the successes of Grammarly and established cognitive feedback principles inform the design of an AI/ML-based feedback tool for UI/UX design? To answer that question, this thesis explores previous work on AI/ML techniques, cognitive feedback theories, structural similarities between grammar and design, and design heuristics in order to ultimately define the theoretical groundwork for a “Grammarly for UI/UX design.