PhD position on Actionable open source intelligence and reliability assessment for forensic investigation of cold cases
The goal of this project is to design and realise an open source intelligence (OSINT) system automating search and gathering of new evidence geared towards re-opening of cold cases. We focus in particular on uncertainty and reliability of information, associated plausibility of scenarios, and consequences for responsible use.
The Centrum voor Veiligheid en Digitalisering (Centre for Safety and Digitalisation, CVD) is a knowledge institute in which companies and public organisations are collaborating on questions related to this theme. In this context, the University of Twente, Saxion University of Applied Sciences, and the Police Academy of the Netherlands are setting up a joint research program around this time. The research program is centered around the 3 focus areas of the CVD: critical data & infrastructure, actionable intelligence and cyberresilience.
For each research line, we are looking for two PhD students to work on this theme. The PhD students will work in a multidisciplinary fashion, in close collaboration with each other, and with the supervision teams with members from the different CVD partners. For more information about CVD and the PhD positions, click here
About the Project
Murder, manslaughter and cold cases reliably attract media interest. In addition to official criminal investigation conducted by the police and judiciary, they are popular subjects for investigative journalists and citizens' initiatives. Sometimes done individually, but more often in a collective, the brainpower of creative minds (wisdom of the crowd) is used to distil new lines of investigation in stalled murder investigations.
What these investigative journalist and citizen initiatives have in common is that both use publicly available information usually obtained through the world-wide web, also known as Open Source Intelligence (OSINT). The question is, however, how do you derive reliable and high quality information from data obtained from such public sources, specifically for cold case investigations? The goal of the project is to develop a system to provide automated support for both the search and reasoning activities. Safety, security and the responsible use (including such questions as bias, reliability, privacy, transparency, explainability) of decision-support systems are crucial. As result, the project will research the legal and ethical aspects of this technology and ways to incorporate them into the design and use.
Relying on OSINT data rases a number of epistemological issues, most notably reliability. Sometimes data is subjective, incomplete, not current, or incorrect, sometimes it can be interpreted in different ways, etc. These issues come hand in hand with ethical and legal questions regarding the semi-automatic collection and analysis of cold case data. Besides the obvious privacy and data protection challenges, the project pays special attention to (a) assessing and addressing bias in the data and its reliability (including value assumptions and value by design-strategies), (b) the role of trust in authorities when combing knowledge created by professionals and citizens, (c) responsible use of AI technology and its proper integration in the decision-making process in this domain. Hence, questions at the core of the project are: How can we harvest the potential of AI and citizen-science in the context of “cold case,” while protecting ethical values and preserving the sense of responsibility for decisions made with the help of AI?
Information and application
Are you interested in this position? Please send your application via the 'Apply now' button below before June 1, 2022 and include:
- A motivation letter
- A detailed CV
- Names of 2 or 3 people that we can contact for additional information
It is allowed to apply for multiple positions.
For more information regarding this position, you are welcome to contact Maurice van Keulen firstname.lastname@example.org
About the department
The Data Management and Biometrics (DMB) group's objective is to contribute to explainable, robust, and resilient data science by developing methods for autonomous, reliable, and robust gathering, preparation, and analysis of the data, to enable relevant, trustworthy, and explainable results. Data science's abilities for data analysis and machine learning drive novel innovative services and benefit society in a large variety of domains, including health, engineering, safety and security, business, and science. At the same time, this digitalisation comes with challenges. You can think of concepts like fairness, data quality, and trust, and threats such as fake news that must be addressed. This requires an interdisciplinary approach bridging fields like computational statistics, machine learning, image and signal processing, information retrieval, and data processing and management. The DMB group currently consists of 15 persons academic staff (including four affiliates), three supporting staff, and 24 PhD students and postdoctoral researchers.
For further information, click here
About the organization
The faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) uses mathematics, electronics and computer technology to contribute to the development of Information and Communication Technology (ICT). With ICT present in almost every device and product we use nowadays, we embrace our role as contributors to a broad range of societal activities and as pioneers of tomorrow's digital society. As part of a people-first tech university that aims to shape society, individuals and connections, our faculty works together intensively with industrial partners and researchers in the Netherlands and abroad, and conducts extensive research for external commissioning parties and funders. Our research has a high profile both in the Netherlands and internationally. It has been accommodated in three multidisciplinary UT research institutes: Mesa+ Institute, TechMed Centre and Digital Society Institute.