Interview training of child-welfare and law-enforcement professionals interviewing maltreated children supported via artificial avatars
Pål Halvorsen and Michael A. Riegler from SimulaMet in collaboration with Gunn Astrid Baugerud (PI) and Miriam Johnson from OsloMet Fakultet for Samfunnsvitenskap received fund of 12 million NOK for their FRIPRO project titled: “Interview training of child-welfare and law-enforcement professionals interviewing maltreated children supported via artificial avatars”.
The sexual and physical abuse of children is a significant societal problem in need of attention. Norway’s Child Protective Services received 58,580 allegations of child maltreatment in 2017 alone. An estimated 118 million children in Europe every year are victims of abuse, and 850 children under age 15 die as a result, according to the World Health Organization. Even if the abuse does not result in death, it has often serious damaging effects for many years, often lifetime, on children’s behaviour, psychological development and adjustment.
The main objective of the project is to improve to a consistently high quality the skills of child welfare and law-enforcement professionals at interviewing maltreated children and to maintain these skills over time. The goal of this proposed project is therefore to determine if this interview-training system using realistic interactive avatars can effectively enhance the interviewing competence of Child Protection Services and law enforcement professionals. Furthermore, the project’s overarching goal is to improve the quality and cost-efficiency of police, health and child-welfare efforts to protect maltreated and at-risk children and address the national spoken goal to improve child-welfare and law-enforcement professionals' interview quality to better protect maltreated children.
The project also involves collaborations with researchers from Griffith University in Australia and the University of Cambridge in the United Kingdom.
Co-tester: Collective-Adaptive Testing of Coevolving Autonomous Cyber-Physical Systems of Systems under Uncertainty
Tao Yue and Shaukat Ali have received funding of 12 million NOK for their project titled: "Co-tester: Collective-Adaptive Testing of Coevolving Autonomous Cyber-Physical Systems of Systems under Uncertainty".
Cyber-Physical Systems of Systems (CPSoS) exhibit unpredictable behaviours due to their coevolution, employed machine learning techniques, collective behaviours, and operation in uncertain environments and unreliable communication networks. Consequently, testing these systems is extremely challenging. The Co-tester project aims to addresses this challenge by developing novel collective-adaptive testing strategies. These strategies will be empowered with advanced artificial intelligence technologies (e.g., machine learning and evolutionary computation techniques), supported with novel strategies for discovering uncertain and unknown behaviours of CPSoS, its constituted Cyber-Physical Systems, operating environment, and networks for extensive testing of CPSoS.