Assessing whether artificial intelligence is an enabler or an inhibitor of sustainability at indicator level

"Since the early phase of the artificial-intelligence (AI) era expectations towards AI are high, with experts believing that AI paves the way for managing and handling various global challenges. However, the significant enabling and inhibiting influence of AI for sustainable development needs to be assessed carefully, given that the technology diffuses rapidly and affects millions of people worldwide on a day-to-day basis. To address this challenge, a panel discussion was organized by the KTH Royal Institute of Technology, the AI Sustainability Center and MIT Massachusetts Institute of Technology, gathering a wide range of AI experts. This paper summarizes the insights from the panel discussion around the following themes: The role of AI in achieving the Sustainable Development Goals (SDGs) AI for a prosperous 21st century Transparency, automated decision-making processes, and personal profiling and Measuring the relevance of Digitalization and Artificial Intelligence (D&AI) at the indicator level of SDGs. The research-backed panel discussion was dedicated to recognize and prioritize the agenda for addressing the pressing research gaps for academic research, funding bodies, professionals, as well as industry with an emphasis on the transportation sector. A common conclusion across these themes was the need to go beyond the development of AI in sectorial silos, so as to understand the impacts AI might have across societal, environmental, and economic outcomes. The recordings of the panel discussion can be found at: https://www.kth.se/en/2.18487/evenemang/the-role-of-ai-in-achieving-the-sdgs-enabler-or-inhibitor-1.1001364?date=2020â 08â 20&length=1&orglength=185&orgdate=2020â 06â 30 Short link: https://bit.ly/2Kap1tE © 2021"The authors acknowledge the KTH Sustainability Office and the KTH Digitalization Platform for their provided funding, which enabled the organization of this panel discussion. SG acknowledges the funding provided by the German Federal Ministry for Education and Research (BMBF) for the project “digitainable”. SDL acknowledges support through the Spanish Governmen

\u3ci\u3eMedicine Meets Virtual Reality 21\u3c/i\u3e

Editors: James D. Westwood, Susan W. Westwood, Li Felländer-Tsai, Cali M. Fidopiastis, Randy S. Haluck, Richard A. Robb, Steven Senger, Kirby G. Vosburgh. Chapter, Varying the Speed of Perceived Self-Motion Affects Postural Control During Locomotion, co-authored by Joshua Pickhinke, Jung Hung Chien, Mukul Mukherjee, UNO faculty and staff members. Virtual reality environments have been used to show the importance of perception of self-motion in controlling posture and gait. In this study, the authors used a virtual reality environment to investigate whether varying optical flow speed had any effect on postural control during locomotion. Healthy young adult participants walked under two conditions, with optical flow matching their preferred walking speed, and with a randomly varying optic flow speed compared to their preferred walking speed. Exposure to the varying optic flow increased the variability in their postural control as measured by area of COP when compared with the matched speed condition. If perception of self-motion becomes less predictable, postural control during locomotion becomes more variable and possibly riskier.https://digitalcommons.unomaha.edu/facultybooks/1261/thumbnail.jp

A Voice-Based Automated System for PTSD Screening and Monitoring

Comprehensive evaluation of PTSD includes diagnostic interviews, self-report testing, and physiological reactivity measures. It is often difficult and costly to diagnose PTSD due to patient access and the variability in symptoms presented. Additionally, potential patients are often reluctant to seek help due to the stigma associated with the disorder. A voice-based automated system that is able to remotely screen individuals at high risk for PTSD and monitor their symptoms during treatment has the potential to make great strides in alleviating the barriers to cost effective PTSD assessment and progress monitoring. In this paper we present a voice-based automated Tele-PTSD Monitor (TPM) system currently in development, designed to remotely screen, and provide assistance to clinicians in diagnosing PTSD. The TPM system can be accessed via a Public Switched Telephone Network (PSTN) or the Internet. The acquired voice data is then sent to a secure server to invoke the PTSD Scoring Engine (PTSD-SE) where a PTSD mental health score is computed. If the score exceeds a predefined threshold, the system will notify clinicians (via email or short message service) for confirmation and/or an appropriate follow-up assessment and intervention. The TPM system requires only voice input and performs computer-based automated PTSD scoring, resulting in low cost and easy field-deployment. The concept of the TPM system was supported using a limited dataset with an average detection accuracy of up to 95.88%

TPM: Cloud-Based Tele PTSD Monitor Using Multi-Dimensional Information

An automated system that can remotely and non-intrusively screen individuals at high risk for Post-Traumatic Stress Disorder (PTSD) and monitor their progress during treatment would be desired by many Veterans Affairs (VAs) as well as other PTSD treatment and research organizations. In this paper, we present an automated, cloud-based Tele-PTSD Monitor (TPM) system based on the fusion of multiple sources of information. The TPM system can be hosted in a cloud environment and accessed through landline or cell phones, or on the Internet through a web portal or mobile application (app)