Tag Archives: artificial intelligence and nuclear weapons

How Artificial Intelligence Can Help Produce Better Chemical Weapons

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An international security conference convened by the Swiss Federal Institute for NBC (nuclear, biological and chemical) Protection —Spiez Laboratory explored how artificial intelligence (AI) technologies for drug discovery could be misused for de novo design of biochemical weapons.  According to the researchers, discussion of societal impacts of AI has principally focused on aspects such as safety, privacy, discrimination and potential criminal misuse, but not on national and international security. When we think of drug discovery, we normally do not consider technology misuse potential. We are not trained to consider it, and it is not even required for machine learning research.

According to the scientists, this should serve as a wake-up call for our colleagues in the ‘AI in drug discovery’ community. Although some expertise in chemistry or toxicology is still required to generate toxic substances or biological agents that can cause significant harm, when these fields intersect with machine learning models, where all you need is the ability to code and to understand the output of the models themselves, they dramatically lower technical thresholds. Open-source machine learning software is the primary route for learning and creating new models like ours, and toxicity datasets that provide a baseline model for predictions for a range of targets related to human health are readily available.

The genie is out of the medicine bottle when it comes to repurposing our machine learning. We must now ask: what are the implications? Our own commercial tools, as well as open-source software tools and many datasets that populate public databases, are available with no oversight. If the threat of harm, or actual harm, occurs with ties back to machine learning, what impact will this have on how this technology is perceived? Will hype in the press on AI-designed drugs suddenly flip to concern about AI-designed toxins, public shaming and decreased investment in these technologies? As a field, we should open a conversation on this topic. The reputational risk is substantial: it only takes one bad apple, such as an adversarial state or other actor looking for a technological edge, to cause actual harm by taking what we have vaguely described to the next logical step. How do we prevent this? Can we lock away all the tools and throw away the key? Do we monitor software downloads or restrict sales to certain groups?

Excerpts from Fabio Urbina et al, Dual use of artificial-intelligence-powered drug discovery, Nature Machine Intelligence (2022)

A Worldwide Web that Kills with Success

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Doubts are growing about the satellites, warships and other big pieces of hardware involved in the command and control of America’s military might. For the past couple of decades the country’s generals and admirals have focused their attention on defeating various forms of irregular warfare. For this, these castles in the sky and at sea have worked well. In the meantime, however, America’s rivals have been upgrading their regular forces—including weapons that can destroy such nodes of power. Both China and Russia have successfully blown up orbiting satellites. And both have developed, or are developing, sophisticated long-range anti-aircraft and anti-ship missiles.

As a result, America is trying to devise a different approach to C2, as command and control is known in military jargon. The Department of Defense has dubbed this idea “Joint All-Domain Command and Control”, or JADC2. It aims to eliminate vulnerable nodes in the system (e.g., satellites) by multiplying the number of peer-to-peer data links that connect pieces of military hardware directly to one another, rather than via a control center that might be eliminated by a single, well-aimed missile.

The goal, officials say, is to create a network that links “every sensor and every shooter”. When complete, this will encompass sensors as small as soldiers’ night-vision gear and sonar buoys drifting at sea, and shooters as potent as ground-based artillery and aerial drones armed with Hellfire missiles.

One likely beneficiary of the jadc2 approach is Anduril Industries, a Californian firm…Its products include small spy helicopter drones; radar, infrared and optical systems constructed as solar-powered towers; and paperback-sized ground sensors that can be disguised as rocks…

Sensors come in still-more-diverse forms than Anduril’s, though. An autonomous doglike robot made by Ghost Robotics of Philadelphia offers a hint of things to come. In addition to infrared and video systems, this quadruped, dubbed v60 q-ugv, can be equipped with acoustic sensors (to recognise, among other things, animal and human footsteps), a millimetre-wave scanner (to see through walls) and “sniffers” that identify radiation, chemicals and electromagnetic signals. Thanks to navigation systems developed for self-driving cars, v60 q-ugv can scamper across rough terrain, climb stairs and hide from people. In a test by the air force this robot was able to spot a mobile missile launcher and pass its location on directly to an artillery team…

Applying Artificial Intelligence (AI) to more C2 processes should cut the time required to hit a target. In a demonstration in September 2020, army artillery controlled by AI and fed instructions by air-force sensors shot down a cruise missile in a response described as “blistering”…

There are, however, numerous obstacles to the success of all this. For a start, developing unhackable software for the purpose will be hard. Legions of machines containing proprietary and classified technologies, new and old, will have to be connected seamlessly, often without adding antennae or other equipment that would spoil their stealthiness…America’s technologists must, then, link the country’s military equipment into a “kill web” so robust that attempts to cripple it will amount to “trying to pop a balloon with one finger”, as Timothy Grayson, head of strategic technologies at DARPA, the defense department’s main research agency, puts it…

Excerpts from The future of armed conflict: Warfare’s worldwide web, Economist,  Jan. 9, 2021

Algorithms as Weapons –Tracking,Targeting Nuclear Weapons

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New and unproved technologies—this time computer systems capable of performing superhuman tasks using machine learning and other forms of artificial intelligence (AI)—threaten to destabilise the global “strategic balance”, by seeming to offer ways to launch a knockout blow against a nuclear-armed adversary, without triggering an all-out war.

A report issued in November by America’s National Security Commission on Artificial Intelligence, a body created by Congress and chaired by Eric Schmidt, a former boss of Google, and Robert Work, who was deputy defence secretary from 2014-17, ponders how AI systems may reshape global balances of power, as dramatically as electricity changed warfare and society in the 19th century. Notably, it focuses on the ability of AI to “find the needle in the haystack”, by spotting patterns and anomalies in vast pools of data…In a military context, it may one day find the stealthiest nuclear-armed submarines, wherever they lurk. The commission is blunt. Nuclear deterrence could be undermined if AI-equipped systems succeed in tracking and targeting previously invulnerable military assets. That in turn could increase incentives for states, in a crisis, to launch a devastating pre-emptive strike. China’s rise as an AI power represents the most complex strategic challenge that America faces, the commission adds, because the two rivals’ tech sectors are so entangled by commercial, academic and investment ties.

Some Chinese officials sound gung-ho about AI as a path to prosperity and development, with few qualms about privacy or lost jobs. Still, other Chinese fret about AI that might put winning a war ahead of global stability, like some game-playing doomsday machine. Chinese officials have studied initiatives such as the “Digital Geneva Convention” drafted by Microsoft, a technology giant. This would require states to forswear cyber-attacks on such critical infrastructure as power grids, hospitals and international financial systems.  AI would make it easier to locate and exploit vulnerabilities in these…

One obstacle is physical. Warheads or missile defences can be counted by weapons inspectors. In contrast, rival powers cannot safely show off their most potent algorithms, or even describe AI capabilities in a verifiable way….Westerners worry especially about so-called “black box” algorithms, powerful systems that generate seemingly accurate results but whose reasoning is a mystery even to their designers.

Excerpts from Chaguan: The Digital Divide, Economist, Jan 18, 2019