Neuroprediction and A.I. in Forensic Psychiatry and Criminal Justice: A Neurolaw Perspective

Advances in the use of neuroimaging in combination with A.I., and specifically the use of machine learning techniques, have led to the development of brain-reading technologies which, in the nearby future, could have many applications, such as lie detection, neuromarketing or brain-computer interfaces. Some of these could, in principle, also be used in forensic psychiatry. The application of these methods in forensic psychiatry could, for instance, be helpful to increase the accuracy of risk assessment and to identify possible interventions. This technique could be referred to as ‘A.I. neuroprediction,’ and involves identifying potential neurocognitive markers for the prediction of recidivism. However, the future implications of this technique and the role of neuroscience and A.I. in violence risk assessment remain to be established. In this paper, we review and analyze the literature concerning the use of brain-reading A.I. for neuroprediction of violence and rearrest to identify possibilities and challenges in the future use of these techniques in the fields of forensic psychiatry and criminal justice, considering legal implications and ethical issues. The analysis suggests that additional research is required on A.I. neuroprediction techniques, and there is still a great need to understand how they can be implemented in risk assessment in the field of forensic psychiatry. Besides the alluring potential of A.I. neuroprediction, we argue that its use in criminal justice and forensic psychiatry should be subjected to thorough harms/benefits analyses not only when these technologies will be fully available, but also while they are being researched and developed

Object Detection Using Various Camera System

Multiple cameras use to simultaneously view an object from multiple angles and at high resolutions detect using real time tracking for surveillance and security management. The component key of tracking for surveillance system are extracting the feature, back-ground subtraction and identification of extracted object. Video surveillance, object de-tection and tracking have drawn a successful increased interest in recent years. An object tracking can be understood as the problem of finding the path (i.e. trajectory) and it can be defined as a procedure to identify the different positions of the object in each frame of a video

Beyond the Prediction Paradigm: Challenges for AI in the Struggle Against Organized Crime

In the future, audiological rehabilitation of adults with hearing loss will be more available, personalized and thorough due to the possibilities offered by the internet. By using the internet as a platform it is also possible to perform the process of rehabilitation in a cost-effective way. With tailored online rehabilitation programs containing topics such as communication strategies, hearing tactics and how to handle hearing aids it might be possible to foster behavioral changes that will positively affect hearing aid users. Four studies were carried out in this thesis. The first study investigated internet usage among adults with hearing loss. In the second study the administration format, online vs. paper- and pencil, of four standardized questionnaires was evaluated. Finally two randomized controlled trials were performed evaluating the efficacy of online rehabilitation programs including professional guidance by an audiologist. The programs lasted over five weeks and were designed for experienced adult hearing-aid users. The effects of the online programs were compared with the effects of a control group. It can be concluded that the use of computers and the internet overall is at least at the same level for people with hearing loss as for the general age-matched population in Sweden. Furthermore, for three of the four included questionnaires, the participants’ scores remained the same across formats. It is however recommended that the administration format remain consistent across assessment points. Finally, results from the two concluding intervention studies provide preliminary evidence that the internet can be used to deliver education and rehabilitation to experienced hearing aid users who report residual hearing problems and that their problems are reduced by the intervention; however the content and design of the online rehabilitation program requires further investigation

The use of software tools and autonomous bots against vandalism: eroding Wikipedia’s moral order?

English - language Wikipedia is constantly being plagued by vandalistic contributions on a massive scale. In order to fight them its volunteer contributors deploy an array of software tools and autonomous bots. After an analysis of their functioning and the ‘ coactivity ’ in use between humans and bots, this research ‘ discloses ’ the moral issues that emerge from the combined patrolling by humans and bots. Administrators provide the stronger tools only to trusted users, thereby creating a new hierarchical layer. Further, surveillance exhibits several troubling features : questionable profiling practices, the use of the controversial measure of reputation, ‘ oversurveillance ’ where quantity trumps quality, and a prospective loss of the required moral skills whenever bots take over from humans. The most troubling aspect, though, is that Wikipedia has become a Janus - faced institution. One face is the basic platform of MediaWiki software, transparent to all. Its other face is the anti - vandalism system, which, in contrast, is opaque to the average user, in particular as a result of the algorithms and neural networks in use. Finally it is argued that this secrecy impedes a much needed discussion to unfold ; a discussion that should focus on a ‘ rebalancing ’ of the anti - vandalism system and the development of more ethical information practices towards contributors

Statistical Methods to Measure Reading Progression Using Eye-Gaze Fixation Points

In this thesis, we investigate methods to accurately track reading progression by analyzing eye-gaze fixation points, using commercially available eye tracking devices and without the imposition of unnatural movement constraints. In order to obtain the most accurate eye-gaze fixation point data possible, the current state of the art relies on expensive, cumbersome apparatuses. Eye-gaze tracking using less expensive hardware, and without constraints imposed on the individual whose gaze is being tracked, results in less reliable, noise-corrupt data which proves difficult to interpret. Extending the accessibility of accurate reading progression tracking beyond its current limits and enabling its feasibility in a real-world, constraint-free environment will enable a multitude of futuristic functionalities for educational, enterprise, and consumer technologies. We first discuss the ``Line Detection System\u27\u27 (LDS), a Kalman filter and hidden Markov model based algorithm designed to infer from noisy data the line of text associated with each eye-gaze fixation point reported every few milliseconds during reading. This system is shown to yield an average line detection accuracy of 88.1\%. Next, we discuss a ``Horizontal Saccade Tracking System\u27\u27 (HSTS) which aims to track horizontal progression within each line, using a least squares approach to filter out noise. Finally, we discuss a novel ``Slip-Kalman\u27\u27 filter which is custom designed to track the progression of reading. This method improves upon the original LDS, performing at an average line detection accuracy of 97.8\%, and offers advanced capability in horizontal tracking compared to the HSTS. The performance of each method is demonstrated using 25 pages worth of data collected during readin