About the analogy between the epistemological and methodological aspects of the activity of intelligence agencies and some scientific disciplines, advocating for a more scientific approach to the process of collecting and analyzing information within the intelligence cycle. I assert that the theoretical, ontological and epistemological aspects of the activity of many intelligence agencies are underestimated, leading to incomplete understanding of current phenomena and confusion in inter-institutional collaboration. After a brief Introduction, which includes a history of the evolution of the intelligence concept after World War II, Intelligence Activity defines the objectives and organization of intelligence agencies, the core model of these organizations (the intelligence cycle), and the relevant aspects of the intelligence gathering and intelligence analysis. In the Ontology section, I highlight the ontological aspects and the entities that threaten and are threatened. The Epistemology section includes aspects specific to intelligence activity, with the analysis of the traditional (Singer) model, and a possible epistemological approach through the concept of tacit knowledge developed by scientist Michael Polanyi. In the Methodology section there are various methodological theories with an emphasis on structural analytical techniques, and some analogies with science, archeology, business and medicine. In Conclusions I argue on the possibility of a more scientific approach to methods of intelligence gathering and analysis of intelligence agencies. CONTENTS: Abstract 1 Introduction 1.1. History 2. Intelligence activity 2.1. Organizations 2.2. Intelligence cycle 2.3 Intelligence gathering 2.4. Intelligence analysis 2.5. Counterintelligence 2.6. Epistemic communities 3. Ontology 4. Epistemology 4.1. The tacit knowledge (Polanyi) 5. Methodologies 6. Analogies with other disciplines 6.1. Science 6.2. Archeology 6.3. Business 6.4. Medicine 7. Conclusions Bibliography DOI: 10.13140/RG.2.2.12971.49445

Drawing on the individual and collective experience of recognized intelligence experts and scholars in the field, Analyzing Intelligence provides the first comprehensive assessment of the state of intelligence analysis since 9/11. Its in-depth and balanced evaluation of more than fifty years of U.S. analysis includes a critique of why it has under-performed at times. It provides insights regarding the enduring obstacles as well as new challenges of analysis in the post-9/11 world, and suggests innovative ideas for improved analytical methods, training, and structured approaches. The book's six sections present a coherent plan for improving analysis. Early chapters examine how intelligence analysis has evolved since its origins in the mid-20th century, focusing on traditions, culture, successes, and failures. The middle sections examine how analysis supports the most senior national security and military policymakers and strategists, and how analysts must deal with the perennial challenges of collection, politicization, analytical bias, knowledge building and denial and deception. The final sections of the book propose new ways to address enduring issues in warning analysis, methodology (or "analytical tradecraft") and emerging analytic issues like homeland defense. The book suggests new forms of analytic collaboration in a global intelligence environment, and imperatives for the development of a new profession of intelligence analysis. Analyzing Intelligence is written for the national security expert who needs to understand the role of intelligence and its strengths and weaknesses. Practicing and future analysts will also find that its attention to the enduring challenges provides useful lessons-learned to guide their own efforts. The innovations section will provoke senior intelligence managers to consider major changes in the way analysis is currently organized and conducted, and the way that analysts are trained and perform.

This report assesses intelligence analysis across the main U.S. intelligence agencies and makes a number of recommendations, some of which parallel initiatives that have begun in the wake of the December 2004 legislation, for instance, create a Deputy Director of National Intelligence as a focal point for analysis, establish a National Intelligence University, build a Long Term Analysis Unit at the National Intelligence Council, and form an Open Source Center for making more creative use of open-source materials.

This book critiques the reliance of Western intelligence agencies on the use of a method for intelligence analysis developed by the CIA in the 1990s, the Analysis of Competing Hypotheses (ACH).

In this seminal work, published by the C.I.A. itself, produced by Intelligence veteran Richards Heuer discusses three pivotal points. First, human minds are ill-equipped ("poorly wired") to cope effectively with both inherent and induced uncertainty. Second, increased knowledge of our inherent biases tends to be of little assistance to the analyst. And lastly, tools and techniques that apply higher levels of critical thinking can substantially improve analysis on complex problems.

Can we make machines that think and act like humans or other natural intelligent agents? The answer to this question depends on how we see ourselves and how we see the machines in question. Classical AI and cognitive science had claimed that cognition is computation, and can thus be reproduced on other computing machines, possibly surpassing the abilities of human intelligence. This consensus has now come under threat and the agenda for the philosophy and theory of AI must be set anew, re-defining the relation between AI and Cognitive Science. We can re-claim the original vision of general AI from the technical AI disciplines; we can reject classical cognitive science and replace it with a new theory (e.g. embodied); or we can try to find new ways to approach AI, for example from neuroscience or from systems theory. To do this, we must go back to the basic questions on computing, cognition and ethics for AI. The 30 papers in this volume provide cutting-edge work from leading researchers that define where we stand and where we should go from here.

Articles by various authors arranged in 5 parts.

If you are responsible for the management of an intelligence enterprise operation and its timely and accurate delivery of reliable intelligence to key decision-makers, this book is must reading. It is the first easy-to-understand, system-level book that specifically applies knowledge management principles, practices and technologies to the intelligence domain. The book describes the essential principles of intelligence, from collection, processing and analysis, to dissemination for both national intelligence and business applications.

What is intelligence - why is it so hard to define, and why is there no systematic theory of intelligence? Kjetil Anders Hatlebrekke creates a new, systematic model of intelligence analysis, arguing that good intelligence is based on understanding the threats that appear beyond our experience, and are therefore the most dangerous to society.

Against the traditional view, Alvin Goldman argues that logic, probability theory, and linguistic analysis cannot by themselves delineate principles of rationality or justified belief. The mind's operations must be taken into account.