All the effects of the use of artificial intelligence for services and national security

All the effects of the use of artificial intelligence for services and national security

What He Said About Intelligence Changes with the Rise of Artificial Intelligence (AI) Anthony Vincey, Senior Fellow added in the National Security and Technology Program at the Center for a New American Security, former senior intelligence officer

In the long history of intelligence, the profession hasn't changed much. Spies have always looked with their eyes, listened with their ears, analyzed and predicted with their minds. A spy from Caesar's legions and Lincoln's Potomac Army would understand each other.

With the arrival of machines, for the first time in the history of intelligence, a revolution is certain. And it is already underway, not everywhere in the world and, given the competitive specificity of the sector, there will be no catching-up process. Those who are not already gearing up for themselves today will succumb in the future.

Currently intelligence, in countries of medium geopolitical stature, is still based on the concept of a human operative who physically follows tracks deemed relevant to national security, and of a human analyst who connects the dots to understand what is happening and try to predict what will happen in the near future.

With the rise of artificial intelligence (AI) and autonomous systems, intelligence radically transforms. The fundamental points of the change emerged during a webinar held on May 5 at the Center for Security and Emerging Technology (CSET) of Georgetown University in which Anthony Vincey provided useful information.

Vincey is an adjunct Senior Fellow in the National Security and Technology Program at the Center for a New American Security, former senior intelligence officer, serving with the Pentagon in Iraq, Africa and Asia in operations, Ph.D in international relations at the London School of Economics, and member of the Council on Foreign Relations.

The essential elements of his speech can be summarized in the following.

  • The introduction of machines for the intelligence community consists of four elements . First, it changes what we spy on, hence the intelligence objectives. Secondly, it changes how we spy, hence the collection mechanisms. Third, it changes how we thwart others who spy on us, hence counterintelligence. And finally, the mission of intelligence changes, therefore the movement surface, traditionally composed of interactions between people.
  • Three technologies can be seen as directional vectors of the Revolution in Intelligence, ubiquitous sensors, AI and autonomy.
  • Autonomy represents the most disruptive change as it removes humans from the intelligence cycle. Autonomy makes it possible to have differentiated entities acting in concert, allowing swarm operations. Swarms are an entirely new form of combat, in which thousands or millions of vehicles operate simultaneously to overwhelm the enemy or fight other swarms. Human beings are not, and will not, be able to keep up with scale and complexity.
  • The conflict changes with the presence of autonomous systems / sensors in all domains (ubiquity) in which human activities, from strategic planning to political decisions, are developed and implemented. As much as we may wish for humans to remain in the loop, several factors limit what humans are able to comprehend in a world of teeming autonomous drones . Humans are unable to keep up with the scale and complexity of an autonomous world of weapon systems, devices with self-evolving tactics that create patterns that no human can perceive with the speed of a machine, microseconds or nanoseconds. be it hypersonic missiles or attacks on financial markets.
  • In the world of autonomous warfare, espionage begins not when the devices are used, but already before their release, therefore in the design, development, and production. Understanding the design intent of such systems becomes an important part of the intelligence analysis process. Autonomous systems are typically designed within a spectrum. What additional decisions the system can take on its own compared to those involving a human operator becomes a factor of strategic knowledge about the opponent. The counter-espionage activity therefore shifts to the development of autonomous systems. The analysis could reveal biases in the developer's work that make it possible to inject codes into the system that weaken it before it hits the market. Software developers will therefore be able to become new sources to be recruited for the collection of secret information and actions against hostile (state and non-state) actors.
  • This necessary anticipation modifies the process of recruiting sources which can no longer be carried out by agents with general knowledge of the IT environment (or worse, without a solid knowledge of it). The recruiter will look in the source for the specialization that is useful to him at that moment. This introduces the need for basic knowledge for the entire intelligence community, from the director to the indexer, making professionals who lack such skills abstruse.
  • Human intelligence (HUMINT) becomes even more important. What changes drastically are the hedged operations . With mass surveillance it becomes practically impossible to operate in hiding. The contrast of invasive surveillance, combined with the fingerprints present in social media, involves the use of other technical tools, such as, for example, models that confuse or manipulate computer vision systems. HUMINT will require full integration with signal intelligence (SIGINT) and geospatial intelligence. In particular, SIGINT, augmented with AI, remains a cornerstone of information gathering , as there will continue to be electromagnetic spectrum signatures and communications to track and encrypt.
  • The adaptation of SIGINT also requires the removal of human beings from the intelligence cycle in order to manage, in a purely technical way, the entire scale and complexity of the operation. This is necessary to effectively collect data on autonomous systems and ubiquity sensors, also in consideration of the abnormal amount of geospatial “Big Data” impossible for humans to analyze alone.
  • The compartmentalization rule becomes counterproductive. In a world dominated by an autonomous systems trust, counterespionage will require new protections, and significantly greater IT and economic expertise. Already today, the so-called "Machine Learning poisoning" is frequent, in which misleading data can be entered inducing an automatic learning system to recognize the wrong object (a computer vision system can be compromised in such a way as to exchange a jet from enemy combat for a passenger jet, and vice versa). The technological transformation of the intelligence community does not take place in a secretive way, as in the Cold War. Instead, it goes in the opposite direction, making intelligence less and less secret, with the presence of small amounts of highly classified information and most of it present in an unclassified space where the capabilities (and not the current bureaucratic organizations) will be security) to constitute barriers to entry. The competition becomes on knowledge, human and AI, on the advantage deriving from innovation.
  • Human-machine interaction becomes a teaming exercise , in which humans team up with computers, thus being able to beat other computers or other humans. This teaming of human intuition, creativity, empathy and strategic thinking, combined with the abilities of computers to embed massive data at speed, scale and complexity ultimately provides the best intelligence capability. All individuals who participate in intelligence work must be comfortable with data science, and with technology in its various forms. It is an integrated man-machine system that continuously evolves to be more competitive. Competitive evolution becomes a natural state of intelligence and national security.
  • The parallel between finance and intelligence is significant. There are lives at stake in safeguarding national security, but for finance there are huge amounts of money where even small changes can mean a lot for the national economy. They are both highly technological, talent-based industries, and both are very risk averse to change. Given the parallels, focusing on finance helps predict the future of homeland security in an AI context. First, in finance, humans are already out of the loop. In high frequency trading, humans have adapted and accepted exclusion from algorithmic “black boxes” at all levels and organizations, leaving (for now) only the aspects of creativity to the human being. This aspect, especially in the way it is implemented, can help in achieving a similar transition in the national security sector.

Fabio Vanorio is a director of the Ministry of Foreign Affairs and International Cooperation. He is an expert on the subject in Intelligence and National Security, as well as in military and security applications of Artificial Intelligence. He also writes for the Italian Institute of Strategic Studies “Niccolò Machiavelli”.

(All the opinions expressed are wholly of the author and do not reflect any official position attributable to either the Italian Government or the Ministry of Foreign Affairs and International Cooperation)

This is a machine translation from Italian language of a post published on Start Magazine at the URL on Mon, 10 May 2021 09:56:45 +0000.