Difference between revisions of "Intelligence Analysis: A Philosophical Introduction"

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==October 28: Ontology of Terrorism==
 
==October 28: Ontology of Terrorism==
  
[https://buffalo.box.com/s/edi8jqz4voaid8wcw21n4q9fb0n8xhrm Slides] [https://www.youtube.com/watch?v=YeMWBt-rH8s Video]
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:[https://buffalo.box.com/s/edi8jqz4voaid8wcw21n4q9fb0n8xhrm Slides]
[https://www.researchgate.net/publication/328145335_From_Affective_Science_to_Psychiatric_Disorder_Ontology_as_a_Semantic_Bridge R. R. Larsen and J. Hastings, "From Affective Science to Psychiatric Disorder: Ontology as a Semantic Bridge" (2018)]
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:[https://www.youtube.com/watch?v=YeMWBt-rH8s Video]
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:[https://www.researchgate.net/publication/328145335_From_Affective_Science_to_Psychiatric_Disorder_Ontology_as_a_Semantic_Bridge R. R. Larsen and J. Hastings, "From Affective Science to Psychiatric Disorder: Ontology as a Semantic Bridge" (2018)]
  
 
==November 4: Organized Military Action ==
 
==November 4: Organized Military Action ==

Revision as of 15:57, 24 February 2019

Intelligence Analysis: A Philosophical Introduction Special Topic PHI 589

Registration:

Class#: XXXXX (PHI)

Instructors: Barry Smith, David Limbaugh

Prerequisites: Open to all persons with an undergraduate degree.

Office hours: By appointment via email at phismith@buffalo.edu or dglimbau@buffalo.edu

The Course

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.

Background Reading: 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.



Intelligence Analysis in Buffalo: UB scientists are involved in a variety of projects in which intelligence analysis plays a role, and some of their intelligence community collaborators in these projects will be involved in the teaching.

Schedule:

August 26: Introduction to Intelligence Analysis

September 2: Labor Day – No class

September 9 The Intelligence Process

September 16: Intelligence Documents

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

Disease from the clinician’s perspective,
Ontological approaches to disease,
The Ontology for General Medical Science

Slides

Third class assignment: Summarize in a 2-page essay the issues discussed in pages 16-21 of Haendel et. al., 2018 and describe how the framework offered by Scheuermann, Ceusters and Smith, 2009 might resolve them.

Advance reading (prior to September 17 lecture): Chapters 5 and 6 of Arp, Smith and Spear, 2016

September 30: Intelligence Doctrine

Peter Morosoff, Ron Rudnicki, Jason Bryant, Robert Farrell, Barry Smith, "[http://ceur-ws.org/Vol-1523/STIDS_2015_T01_Morosoff_etal.pdf 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:

From speech acts to document acts

Slides Video

October 21: Intelligence Doctrine

Joint Doctrine Ontology (JDO)

Slides Video

Readings:

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

Slides
Video
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

Slides Video

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

Reading

G. Marcus (2018), "Deep Learning: A Critical Appraisal"

November 18:

November 25:

December 2: Student Projects

Provisional list of further topics

We should add: opaque ai vs. transparent ai

A very practical demonstration or perhaps an assigned project that helps students understand how ontology solves problems.

Maybe this is included in the ontology sections, but we should include something about the relationship between entities that are about... and entities that are not. This comes up so often and it's really hard for people to understand until they take some time to focus on the distinction. In my experience, it also helps when teaching logic to get this out of the way.

Referent tracking and Object-Based Production Agent-Based Intelligence and the philosophy of action Common Knowledge Uncertainty

Belief Revision Uncertainty Pedigree and Provenance Geographic Information Science Intelligence Preparation of the Operational Environment

Ontology, AI and Robotics
Services, Commodities, Infrastructure
Product Life Cycle Ontology
Ontology and Information Engineering in the Healthcare Domain
The Science of Document Informatics
Finance Ontology
The Ontology of Plans
Ontology of Military Logistics
Ontology and Intelligence Analysis
Ontology and Data Fusion
Ontology of Terrorism

Student Learning Outcomes

Program Outcomes/Competencies Instructional Method(s) Assessment Method(s)
The student will acquire a thorough knowledge of current ontology research in areas relating to engineering, data fusion, defense and intelligence Video lectures and online discussions Review of submitted online content and of participation in online discussion forum
The student will acquire experience in ontology development Video lectures and critique of successive drafts Review of results in the form of xsl spreadsheet or Protégé file
The student will acquire experience in communicating the results of work on ontology development Creation of youtube presentation and of associated documentation Review of results

Important dates

Jan 28 - first video released by Dr Smith at 9am
Feb 20 - about now start to discuss by email the content of your video and essay with Dr Smith
Feb 28 - submit a proposed title and abstract
Mar 16 - create a simple ontology using Protege
Mar 31 - submit a table of contents and 300 word summary plus draft of associated ppt slides
Apr 27 - submit penultimate draft of essay and powerpoint
May 4 - submit final version of essay and powerpoint and upload final version of video to youtube

Grading

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:

Weighting Assignment

26% - video summaries (2% per summary)
14% - forum participation
20% - youtube video
20% - powerpoint slides
20% - essay / ontology content

Final Grades

Grade Quality Percentage

A 4.0 93.0% -100.00%
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.

Background Reading and Video Materials