- Conference Title: 2027 AI Policing and Fraud Prevention Criminal Justice Symposium
- Organizer: Department of Criminal Justice at Ming Chuan University
- Conference Date: March 18, 2027 (Thursday)
- Conference Theme: Applications and Challenges of AI in Crime Prevention
- Submission Deadline: Abstracts will be submitted by November 30, 2026 (Monday)
- Submission Guidelines:
- Abstracts may be written in Chinese or English. Chinese abstracts should be no more than 1000 words, and English abstracts no more than 500 words.
- Please send your paper (in both PDF and Word formats) to Assistant Professor Lin Shu-Li at npacib@gmail.com before the deadline.
- Target Audience: Full-time and part-time teachers and graduate students at all levels of schools.
- Abstract Review Notification: December 30, 2026 (Wednesday)
- Full Text Submission Deadline: February 15, 2027 (Monday)
- Full Text Count: No more than 15,000 Chinese characters, no more than 5,000 English characters.
- Abstract Review Results: The abstract will be reviewed by the conference’s paper review committee, and the review results will be notified by letter.
- Online Registration Deadline: February 20, 2027 (Saturday)
- Organizer: Department of Criminology, Ming Chuan University
- Abstracts may be written in Chinese or English. Chinese abstracts should be no more than 1000 words, and English abstracts no more than 500 words.
- Please send your paper (in both PDF and Word formats) to Assistant Professor Lin Shu-Li at npacib@gmail.com before the deadline.
- Target Audience: Full-time and part-time teachers and graduate students at all levels of schools.
Contact Person: Assistant Professor LIN,SHU-LI
Email: npacib@gmail.com
Address: No. 5, Deming Rd., Guishan District, Taoyuan City, 33348, Taiwan
Tel: 886-3-3507001 ext3776
The Department of Criminal Justice at Ming Chuan University, cordially invites experts and scholars in related fields to submit papers! With the development of artificial intelligence (AI), the global security risks brought about by technology are constantly increasing. AI may increase the likelihood of malicious use for crime. From deepfake videos manipulating public opinion to aggressive propaganda fueling cybercrime, criminals are seeking new ways to use these tools to achieve their criminal goals. However, AI may also transform crime prevention detection and protection. With appropriate safeguards, AI can provide powerful tools to detect crime, track illicit financial flows, and analyze massive amounts of data to identify new criminalization patterns.
Ming Chuan University, recognizing the opportunities and challenges of using AI in crime prevention, invites experts from various fields to attend this international symposium on March 18, 2027. The symposium will collaboratively explore the impact of AI on crime prevention and corresponding strategies.
Open discussions will cover the rise of online misinformation, the transformation of traditional media, and new challenges to trust and security measures in cyberspace. To deepen engagement with these emerging threats, the symposium will highlight key gaps in digital regulatory frameworks, emphasize the importance of public-private partnerships, and stress the necessity of increased involvement from the criminal justice system.
Related topics include AI-driven crime prevention measures, particularly the increasingly difficult-to-prevent new forms of telecommunications and internet fraud. The aim is to leverage AI technology for crime prevention, efficiently providing services in crime detection, police deployment, and crime prevention/prediction. This involves combining various technologies and equipment, such as surveillance cameras, image collection, building massive databases, and digital activity tracking, to instantly identify high-risk individuals and activities, such as ATM drivers, stolen goods, and illicit funds.
Simultaneously, the importance of transparency, accountability, and adherence to international human rights standards in AI technology applications is emphasized, integrating it into cross-industry sustainable management practices and transformation. Through generative AI technology and information and communication technology, technology-driven crime prevention is achieved.