Difference between revisions of "Intelligence Analysis: A Crash Course"
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==November 11: Artificial Intelligence, Deep Learning, Machine Learning ==
==November 11: Artificial Intelligence, Deep Learning, Machine Learning ==
Revision as of 10:08, 27 October 2019
Intelligence Analysis: A Crash Course
Special Topic PHI 579
- Class#: 24032 (PHI)
Prerequisites: Open to all persons with an undergraduate degree.
- 1 The Course
- 2 August 26: Introduction: Will World War 3 be fought on the internet?
- 3 September 9: Ontology and the Intelligence Process
- 4 September 16: An Introduction to Basic Formal Ontology
- 5 September 23: Object-Based Production and Referent Tracking
- 6 September 30: Enhanced Object-Based Production
- 7 October 7: Joint Doctrine Ontology
- 8 October 14: Meaningful AI vs. Deep Learning
- 9 October 21: Ontology of Terrorism
- 10 October 28: Ontology of Documents
- 11 November 4: Organized Military Action
- 12 November 11: Artificial Intelligence, Deep Learning, Machine Learning
- 13 November 18: Pedigree, Provenance, Classification, Clearance
- 14 November 25: Ontology and Data Fusion
- 15 December 2: Student Projects
- 16 Further topics
- 17 Reading
- 18 Student Learning Outcomes
- 19 Important dates
- 20 Grading
- 21 Related Policies and Services
- 22 Background Reading and Video Materials
Course Description: This course will provide an introduction to intelligence analysis, covering both the practical and the theoretical aspects of the intelligence process. We will cover a range of topics including: the nature and goals of intelligence analysis; the cognitive processes involved; the different types of evidence used; analytical reasoning; the role of AI and other forms of computer support to intelligence analysis.
Course Structure: This is a three credit hour graduate seminar, with a practical exercise forming part of each class. The final session will be structured around youtube videos created by the students in the class. Students will be trained in the basic tools and methods of intelligence analysis, and will also receive an insight into the overall context into which intellligence analysis fits.
Target Audience: The course is open to all interested students, and will presupposen no knowledge of philosophy or of intelligence analysis.
Intelligence Analysis in Buffalo: UB scientists are involved in a variety of projects in which intelligence analysis plays a role, and some of the intelligence community collaborators in these projects will be involved in the teaching.
August 26: Introduction: Will World War 3 be fought on the internet?
Will the World War 3 be fought on the internet?
An Introduction to the Joint Doctrine Ontology
September 9: Ontology and the Intelligence Process
Will feature presentation by COL William Mandrick, PhD on
The Intelligence Process
Background reading: Joint Intelligence
September 16: An Introduction to Basic Formal Ontology
September 23: Object-Based Production and Referent Tracking
- Introduction to Object-Based Production
- Agent-Based Intelligence and the philosophy of action
Werner Ceusters, Shahid Manzoor, "How to track absolutely everything", Ontologies and Semantic Technologies for the Intelligence Community (Frontiers in Artificial Intelligence and Applications), 2010, 13-36.
September 30: Enhanced Object-Based Production
- RDF triples and Linked Open Data
- Tracking change and tracking errors
Frederik Stjernfelt, "The ontology of espionage in reality and fiction", Sign Systems Studies, 31:1 (2003), 133-161
Werner Ceusters and Barry Smith, "Aboutness: Towards Foundations for the Information Artifact Ontology", Proceedings of the Sixth International Conference on Biomedical Ontology (ICBO). CEUR vol. 1515. pp. 1-5 (2015).
October 7: Joint Doctrine Ontology
Peter Morosoff, Ron Rudnicki, Jason Bryant, Robert Farrell, Barry Smith, "Joint Doctrine Ontology: A Benchmark for Military Information Systems Interoperability", Semantic Technology for Intelligence, Defense and Security (STIDS), 2015, CEUR vol. 1523, 2-9.
- Department of Defense Dictionary of Military and Associated Terms
- P. Morossof et al., "Joint Doctrine Ontology: A Benchmark for Military Information Systems Interoperability" (2015)
October 14: Meaningful AI vs. Deep Learning
Jobst Landgrebe and Barry Smith, "Making AI Meaningful Again", arXiv, 2019.
Jobst Landgrebe and Barry Smith, "Why Turing machines cannot pass the Turing test", arXiv, 2019.
October 21: Ontology of Terrorism
- R. R. Larsen and J. Hastings, "From Affective Science to Psychiatric Disorder: Ontology as a Semantic Bridge" (2018)
October 28: Ontology of Documents
From Speech Acts to Document Acts
"IAO-Intel: An Ontology of Information Artifacts in the Intelligence Domain”, Proceedings of the Eighth International Conference on Semantic Technologies for Intelligence, Defense, and Security, Fairfax, VA (STIDS 2013), 33-40.
November 4: Organized Military Action
Massively planned social agency
Presentations of draft powerpoint slides.
November 11: Artificial Intelligence, Deep Learning, Machine Learning
- Overview of machine learning and other approaches to the exploitation of Big Data
- Role of ontology in Data Science
November 18: Pedigree, Provenance, Classification, Clearance
November 25: Ontology and Data Fusion
December 2: Student Projects
- Common Knowledge
- Internet of Battlefield Things (IoBT)
- Belief Revision
- Geographic Information Science
- Intelligence Preparation of the Operational Environment
- Machine Support for Intelligence Analysis
Joint Intelligence (to be read in advance of COL Mandrick class on September 9)
Robert Arp, Barry Smith and Andrew Spear, Building Ontologies with Basic Formal Ontology, Cambridge, MA: MIT Press, August 2015.
Barry Smith, Tatiana Malyuta, David Salmen, William Mandrick, Kesny Parent, Shouvik Bardhan, Jamie Johnson, "Ontology for the Intelligence Analyst", CrossTalk: The Journal of Defense Software Engineering, November/December 2012, 18-25.
Terry Janssen, Herbert Basik, Mike Dean, Barry Smith, "A Multi-INT Semantic Reasoning Framework for Intelligence Analysis Support", in: L. Obrst, T. Janssen, W. Ceusters (eds.), Ontologies and Semantic Technologies for the Intelligence Community (Frontiers in Artificial Intelligence and Applications), Amsterdam: IOS Press, 2010, 57-69.
David Salmen, Tatiana Malyuta, Alan Hansen, Shaun Cronen, Barry Smith, Integration of Intelligence Data through Semantic Enhancement", Proceedings of the Conference on Semantic Technology in Intelligence, Defense and Security (STIDS), George Mason University, Fairfax, VA, November 16-17, 2011, CEUR, Vol. 808, 6-13.
Barry Smith, Tatiana Malyuta, William S. Mandrick, Chia Fu, Kesny Parent, Milan Patel, "http://ontology.buffalo.edu/smith/articles/Horizontal-integration.pdf Horizontal Integration of Warfighter Intelligence Data. A Shared Semantic Resource for the Intelligence Community", Proceedings of the Conference on Semantic Technology in Intelligence, Defense and Security (STIDS), George Mason University, Fairfax, VA, October 23-25, 2012, CEUR 996, 112-119.
Student Learning Outcomes
|Program Outcomes/Competencies||Instructional Method(s)||Assessment Method(s)|
|The student will acquire a knowledge of the principles and procedures of intelligence analysis, and an insight into the philosophical methods and theories relevant thereto. The student will also acquire a familiarity with current theoretical research in areas relating to intelligence analysis.||Lectures and class discussions||Review of reading matter and associated online content and participation in class discussions|
|The student will acquire experience in practical tasks involved in intelligence analysis||Participation in practical experiments||Review of results|
|The student will acquire experience in communicating the results of work on intelligence analysis and its philosophical understanding||Creation of youtube presentation and of associated documentation||Review of results|
|Sep 20||- about now start to discuss by email the content of your video and essay with Drs Smith and Limbaugh|
|Sep 28||- submit a proposed title and abstract|
|Oct 31||- submit a table of contents and 300 word summary plus draft of associated ppt slides|
|Nov 20||- submit penultimate draft of essay and powerpoint|
|Dec2||- class presentation|
|Dec 4||- submit final version of essay and powerpoint and upload final version of video to youtube|
Grading will be based on two factors:
I: understanding and criticism of the material presented in classes 1-13
All students are required to take an active part in class (and where relevant on-line) discussions throughout the semester.
II: preparation of a youtube video and associated documentation (including powerpoint slides and essay).
Content and structure of the essay should be discussed with Drs Smith or Limbaugh. Where the essay takes the form of the documentation of a specific ontology developed by the student it should include:
- Statement of scope of the ontology
- Summary of existing ontologies in the relevant domain
- Explanation of how your ontology differs from (or incorporates) these ontologies
- Screenshots of parts of the ontology with some examples of important terms and definitions
- Summaries of potential applications of the ontology
Grading Policy: Grading follows standard Graduate School policies. Grades will be weighted according to the following breakdown:
- 40% - class discussions
- 20% - youtube video presentation
- 20% - powerpoint slides
- 20% - essay / ontology content
Percentages refer to sum of assignment grades as listed above
Grade Quality Percentage
|A-||3.67||87.0% - 89.9%|
|B+||3.33||84.0% - 86.9%|
|B||3.00||80.0% - 83.9%|
|B-||2.67||77.0% - 79.9%|
|C+||2.33||74.0% - 76.9%|
|C||2.00||71.0% - 73.9%|
|C-||1.67||68.0% - 70.9%|
|D+||1.33||65.0% - 67.9%|
|D||1.00||62.0% - 64.9%|
|F||0||61.9% or below|
An interim grade of Incomplete (I) may be assigned if the student has not completed all requirements for the course. An interim grade of 'I' shall not be assigned to a student who did not attend the course. The default grade accompanying an interim grade of 'I' shall be 'U' and will be displayed on the UB record as 'IU.' The default Unsatisfactory (U) grade shall become the permanent course grade of record if the 'IU' is not changed through formal notice by the instructor upon the student's completion of the course.
Assignment of an interim 'IU' is at the discretion of the instructor. A grade of 'IU' can be assigned only if successful completion of unfulfilled course requirements can result in a final grade better than the default 'U' grade. The student should have a passing average in the requirements already completed. The instructor shall provide the student specification, in writing, of the requirements to be fulfilled.
The university’s Graduate Incomplete Policy can be found here.
Related Policies and Services
Academic integrity is a fundamental university value. Through the honest completion of academic work, students sustain the integrity of the university while facilitating the university's imperative for the transmission of knowledge and culture based upon the generation of new and innovative ideas. See http://grad.buffalo.edu/Academics/Policies-Procedures/Academic-Integrity.html.
Accessibility resources: If you have any disability which requires reasonable accommodations to enable you to participate in this course, please contact the Office of Accessibility Resources in 60 Capen Hall, 645-2608 and also the instructor of this course during the first week of class. The office will provide you with information and review appropriate arrangements for reasonable accommodations, which can be found on the web here.