Postgraduate Course: Information Technology, Investigation & Evidence (LAWS11172)
Course Outline
| School | School of Law |
College | College of Humanities and Social Science |
| Course type | Standard |
Availability | Available to all students |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Credits | 20 |
| Home subject area | Law |
Other subject area | None |
| Course website |
http://www.law.ed.ac.uk/ahrc/teaching/llm/information/moduleinformation/ |
Taught in Gaelic? | No |
| Course description | This module deals with the interaction of Artificial Intelligence and the law. It highlights the impacts, opportunities and problems arising from the use and design of AI applications for the legal domain.
The module covers the process of criminal investigation from the commission of the first crime to the point at which a charge can be brought against a suspected criminal, focusing on technology support for the gathering of evidence for crimes. It shows how technology can be used to identify links between criminals; to discern temporal or geographical patterns in crimes; to assist in identity recognition from biometrics; to help investigators consider multiple scenarios rather than focusing too closely on one hypothesis; and to understand the context of evidence extracted from databases to avoid potential miscarriages of justice.
The module also covers methods for fraud prevention and detection, and for legal compliance, in a commercial environment; the use of electronic discovery methods for analysing large volumes of online documents; searching the Internet for 'suspect' websites; and issues surrounding technologies for facial reconstruction.
Session titles are:
Link analysis 1
Link analysis 2
Situational crime prevention 1
Situational crime prevention 2
Monitoring and pattern identification 1
Monitoring and pattern identification 2
Identity and identity fraud 1
Identity and identity fraud 2
Text mining
CSI: databases |
Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
| Additional Costs | Students should have regular and reliable access to the Internet.
Print consumables (paper and ink) would be recommended to provide hard copy of some on screen text and materials (e.g. articles).
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Information for Visiting Students
| Pre-requisites | None |
| Displayed in Visiting Students Prospectus? | Yes |
Course Delivery Information
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| Delivery period: 2013/14 Semester 1, Available to all students (SV1)
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Learn enabled: Yes |
Quota: None |
Web Timetable |
Web Timetable |
| Class Delivery Information |
This course is taught by distance learning. |
| Course Start Date |
16/09/2013 |
| Breakdown of Learning and Teaching activities (Further Info) |
Please contact the School directly for a breakdown of Learning and Teaching Activities |
| Additional Notes |
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| Breakdown of Assessment Methods (Further Info) |
Please contact the School directly for a breakdown of Assessment Methods
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| No Exam Information |
Summary of Intended Learning Outcomes
Summary of intended learning outcomes
The aims of this module are to:
-raise awareness of how computer techniques can help the investigation and evidence process;
-develop an understanding of how various techniques can be used in investigations, with their respective strengths and weaknesses;
-raise awareness of software that supports the investigation and evidence process.
By the end of this module, you will be able to:
-critically discuss and assess the use of AI applications for the legal domain;
-describe the strengths and weaknesses of these techniques;
-identify future application areas and develop ideas for suitable software.
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Assessment Information
| One essay of up to 4,000 words (60%); one piece of assessed work (20%); contribution to online discussions (20%). |
Special Arrangements
| This course is taught by distance learning. |
Additional Information
| Academic description |
Not entered |
| Syllabus |
Not entered |
| Transferable skills |
Not entered |
| Reading list |
Not entered |
| Study Abroad |
Not entered |
| Study Pattern |
Not entered |
| Keywords | Not entered |
Contacts
| Course organiser | Mr Burkhard Schafer
Tel: (0131 6)50 2035
Email: B.Schafer@ed.ac.uk |
Course secretary | Ms Clare Polson
Tel: (0131 6)51 4411
Email: Clare.Polson@ed.ac.uk |
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