Intelligence Analysis: A Philosophical Introduction
Intelligence Analysis: A Crash Course Special Topic PHI 589
- Class#: XXXXX (PHI)
Prerequisites: Open to all persons with an undergraduate degree.
- 1 The Course
- 2 Reading
- 3 August 26: Why the next world war will be fought on the internet
- 4 September 2: Labor Day – No class
- 5 September 9 The Intelligence Process
- 6 September 16: Intelligence Documents
- 7 September 23: Referent Tracking
- 8 September 30: Intelligence Doctrine
- 9 October 7: Meaningful AI vs. Deep Learning
- 10 October 14: Aboutness
- 11 October 21: Intelligence Doctrine
- 12 October 28: Ontology of Terrorism
- 13 November 4: Organized Military Action
- 14 November 11: Artificial Intelligence, Deep Learning, Machine Learning
- 15 November 18: Pedigree, Provenance, Classification, Clearance
- 16 November 25: Ontology and Data Fusion
- 17 December 2: Student Projects
- 18 Further topics
- 19 Student Learning Outcomes
- 20 Important dates
- 21 Grading
- 22 Related Policies and Services
- 23 Background Reading and Video Materials
Course Description: The aim of the course is to provide a philosophical introduction to intelligence analysis. We will apply the methods of philosophy to a range of topics including: the nature and goals of intelligence analysis; the cognitive processes involved; the different types of evidence used; statistical aspects of analytic reasoning; the role of AI and other forms of computer support. Philosophical methods employed will include those of epistemology, social ontology, cognitive ontology, and the philosophy of computing and information.
Course Structure: This is a three credit hour graduate seminar. Components of each three-hour seminar will be incorporated into a series of on-line videos. The final session will be structured around youtube videos created by the students in the class. The course will also feature a practical component in which students will be trained in the basic cognitive tools 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 theintelligence community collaborators in these projects will be involved in the teaching.
Robert Arp, Barry Smith and Andrew Spear, Building Ontologies with Basic Formal Ontology, Cambridge, MA: MIT Press, August 2015.
Jobst Landgrebe and Barry Smith, "Making AI Meaningful Again", arXiv, 2019.
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.
August 26: Why the next world war will be fought on the internet
September 2: Labor Day – No class
September 9 The Intelligence Process
September 16: Intelligence Documents
From speech acts to document acts
Barry Smith, Tatiana Malyuta, Ron Rudnicki, William Mandrick, David Salmen, Peter Morosoff, Danielle K. Duff, James Schoening, Kesny Parent, "http://ontology.buffalo.edu/smith/articles/STIDS-2013.pdf 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), CEUR, vol. 1097, 33-40.
September 23: Referent Tracking
- Referent tracking and 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: Intelligence Doctrine
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.
October 7: Meaningful AI vs. Deep Learning
October 14: Aboutness
Frederik Stjernfelt, "The ontology of espionage in reality and fiction", Sign Systems Studies, 31:1 (2003), 133-161
October 21: Intelligence Doctrine
Joint Doctrine Ontology (JDO)
- 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 28: Ontology of Terrorism
- R. R. Larsen and J. Hastings, "From Affective Science to Psychiatric Disorder: Ontology as a Semantic Bridge" (2018)
November 4: Organized Military Action
Massively planned social agency
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
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 Dr Smith|
|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|
|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 videos presented in classes 1-13
All students are required to ingest the content of all videos and to take an active part in 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 Dr Smith. 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:
- 26% - video summaries (2% per summary)
- 14% - forum participation
- 20% - youtube video
- 20% - powerpoint slides
- 20% - essay / ontology content
Grade Quality Percentage
|A-||3.67||90.0% - 92.9%|
|B+||3.33||87.0% - 89.9%|
|B||3.00||83.0% - 86.9%|
|B-||2.67||80.0% - 82.9%|
|C+||2.33||77.0% - 79.9%|
|C||2.00||73.0% - 76.9%|
|C-||1.67||70.0% - 72.9%|
|D+||1.33||67.0% - 69.9%|
|D||1.00||60.0% - 66.9%|
|F||0||59.9% 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.