The Covid 19 Intelligence Failure

An in-depth analysis of why COVID-19 warnings failed and how to avert the next disaster Epidemiologists and national security agencies warned for years about the potential for a deadly pandemic, but in the end global surveillance and warning systems were not enough to avert the COVID-19 disaster. In The COVID-19 Intelligence Failure, Erik J. Dahl demonstrates that understanding how intelligence warnings work—and how they fail—shows why the years of predictions were not enough. In the first in-depth analysis of the topic, Dahl examines the roles that both traditional intelligence services and medical intelligence and surveillance systems play in providing advance warning against public health threats—and how these systems must be improved for the future. For intelligence to effectively mitigate threats, specific, tactical-level warnings must be collected and shared in real time with receptive decision makers who will take appropriate action. Dahl shows how a combination of late and insufficient warnings about COVID-19, the Trump administration’s political aversion to scientific advice, and decentralized public health systems all exacerbated the pandemic in the United States. Dahl’s analysis draws parallels to other warning failures that preceded major catastrophes from Pearl Harbor to 9/11, placing current events in context. The COVID-19 Intelligence Failure is a wake-up call for the United States and the international community to improve their national security, medical, and public health intelligence systems and capabilities.

The emergence of COVID-19 has raised urgent and important questions about the role of Canadian intelligence and national security within a global health crisis. Some argue that the effects of COVID-19 on Canada represent an intelligence failure, or a failure of early warning. Others argue that the role of intelligence and national security in matters of health is--and should remain--limited. At the same time, traditional security threats have rapidly evolved, themselves impacted and influenced by the global pandemic. Stress Tested brings together leading experts to examine the role of Canada's national security and intelligence community in anticipating, responding to, and managing a global public welfare emergency. This interdisciplinary collection offers a clear-eyed view of successes, failures, and lessons learned in Canada's pandemic response. Addressing topics including supply chain disruptions, infrastructure security, the ethics of surveillance within the context of pandemic response, the threats and potential threats of digital misinformation and fringe beliefs, and the challenges of maintaining security and intelligence operations during an ongoing pandemic, Stress Tested is essential reading for anyone interested in the lasting impacts of the COVID-19 pandemic.

This study evaluates whether surprise and intelligence failure leading to mass casualty terrorism are inevitable. It explores the extent to which four factors – failures of public policy leadership, analytical challenges, organizational obstacles, and the inherent problems of warning information – contribute to intelligence failure. The study applies existing theories of surprise and intelligence failure to case studies of five mass casualty terrorism incidents: World Trade Center 1993; Oklahoma City 1995; Khobar Towers 1996; East African Embassies 1998; and September 11, 2001. A structured, focused comparison of the cases is made using a set of thirteen probing questions based on the factors above. The study concludes that while all four factors were influential, failures of public policy leadership contributed directly to surprise. Psychological bias and poor threat assessments prohibited policy makers from anticipating or preventing attacks. Policy makers mistakenly continued to use a law enforcement approach to handling terrorism, and failed to provide adequate funding, guidance, and oversight of the intelligence community. The study has implications for intelligence reform, information sharing, congressional oversight, and society’s expectations about the degree to which the intelligence community can predict or prevent surprise attacks.

How can the United States avoid a future surprise attack on the scale of 9/11 or Pearl Harbor, in an era when such devastating attacks can come not only from nation states, but also from terrorist groups or cyber enemies? Intelligence and Surprise Attack examines why surprise attacks often succeed even though, in most cases, warnings had been available beforehand. Erik J. Dahl challenges the conventional wisdom about intelligence failure, which holds that attacks succeed because important warnings get lost amid noise or because intelligence officials lack the imagination and collaboration to “connect the dots” of available information. Comparing cases of intelligence failure with intelligence success, Dahl finds that the key to success is not more imagination or better analysis, but better acquisition of precise, tactical-level intelligence combined with the presence of decision makers who are willing to listen to and act on the warnings they receive from their intelligence staff. The book offers a new understanding of classic cases of conventional and terrorist attacks such as Pearl Harbor, the Battle of Midway, and the bombings of US embassies in Kenya and Tanzania. The book also presents a comprehensive analysis of the intelligence picture before the 9/11 attacks, making use of new information available since the publication of the 9/11 Commission Report and challenging some of that report’s findings.

The true story of two mass-casualty incidents that occurred within days of each other at a US Air Force base. Using the words of the people who experienced the tragedies, the book provides in-depth look at the before, during and after of a preventable active-shooter incident and an avoidable fatal plane crash. The base psychiatrist knew the airman was dangerous. “This is the kind of patient who … one day … he’s going to come back and kill you.” Aircrews knew the rogue pilot was dangerous. “We predicted the worst air-show disaster in history when we found out that he was gonna fly.” Written by Andy Brown, the man who ended the killing spree, the result of more than seven years of research. Brown "masterfully weaves" the two stories together in a powerful narrative. He also reveals the preparations he made that enabled him to end a pistol-versus-rifle gunfight with a 70 yard shot from his handgun. Part true crime, part law-enforcement biography memoir and part military history. Warnings Unheeded is presented in an objective style that shows what can happen when authorities become complacent, when the precursors of violence are ignored and the lessons from history are forgotten.

"The ongoing COVID-19 pandemic marks the most significant, singular global disruption since World War II, with health, economic, political, and security implications that will ripple for years to come." -Global Trends 2040 (2021) Global Trends 2040-A More Contested World (2021), released by the US National Intelligence Council, is the latest report in its series of reports starting in 1997 about megatrends and the world's future. This report, strongly influenced by the COVID-19 pandemic, paints a bleak picture of the future and describes a contested, fragmented and turbulent world. It specifically discusses the four main trends that will shape tomorrow's world: - Demographics-by 2040, 1.4 billion people will be added mostly in Africa and South Asia. - Economics-increased government debt and concentrated economic power will escalate problems for the poor and middleclass. - Climate-a hotter world will increase water, food, and health insecurity. - Technology-the emergence of new technologies could both solve and cause problems for human life. Students of trends, policymakers, entrepreneurs, academics, journalists and anyone eager for a glimpse into the next decades, will find this report, with colored graphs, essential reading.

If you want your startup to succeed, you need to understand why startups fail. “Whether you’re a first-time founder or looking to bring innovation into a corporate environment, Why Startups Fail is essential reading.”—Eric Ries, founder and CEO, LTSE, and New York Times bestselling author of The Lean Startup and The Startup Way Why do startups fail? That question caught Harvard Business School professor Tom Eisenmann by surprise when he realized he couldn’t answer it. So he launched a multiyear research project to find out. In Why Startups Fail, Eisenmann reveals his findings: six distinct patterns that account for the vast majority of startup failures. • Bad Bedfellows. Startup success is thought to rest largely on the founder’s talents and instincts. But the wrong team, investors, or partners can sink a venture just as quickly. • False Starts. In following the oft-cited advice to “fail fast” and to “launch before you’re ready,” founders risk wasting time and capital on the wrong solutions. • False Promises. Success with early adopters can be misleading and give founders unwarranted confidence to expand. • Speed Traps. Despite the pressure to “get big fast,” hypergrowth can spell disaster for even the most promising ventures. • Help Wanted. Rapidly scaling startups need lots of capital and talent, but they can make mistakes that leave them suddenly in short supply of both. • Cascading Miracles. Silicon Valley exhorts entrepreneurs to dream big. But the bigger the vision, the more things that can go wrong. Drawing on fascinating stories of ventures that failed to fulfill their early promise—from a home-furnishings retailer to a concierge dog-walking service, from a dating app to the inventor of a sophisticated social robot, from a fashion brand to a startup deploying a vast network of charging stations for electric vehicles—Eisenmann offers frameworks for detecting when a venture is vulnerable to these patterns, along with a wealth of strategies and tactics for avoiding them. A must-read for founders at any stage of their entrepreneurial journey, Why Startups Fail is not merely a guide to preventing failure but also a roadmap charting the path to startup success.

This book presents a compilation of the most recent implementation of artificial intelligence methods for solving different problems generated by the COVID-19. The problems addressed came from different fields and not only from medicine. The information contained in the book explores different areas of machine and deep learning, advanced image processing, computational intelligence, IoT, robotics and automation, optimization, mathematical modeling, neural networks, information technology, big data, data processing, data mining, and likewise. Moreover, the chapters include the theory and methodologies used to provide an overview of applying these tools to the useful contribution to help to face the emerging disaster. The book is primarily intended for researchers, decision makers, practitioners, and readers interested in these subject matters. The book is useful also as rich case studies and project proposals for postgraduate courses in those specializations.