Enforced Transparency: A Solution to Autonomous Weapons as Potentially Uncontrollable Weapons Similar to Bioweapons

2021 ◽  
pp. 219-236
Author(s):  
Armin Krishnan
Keyword(s):  
Artificial Intelligence ◽  
Deep Learning ◽  
Arms Control ◽  
Lessons Learned ◽  
Biological Weapons ◽  
Design Standards ◽  
International Regulation ◽  
Strategic Stability ◽  
Autonomous Weapons ◽  
Biological Weapons Convention

This chapter argues that in many respects the regulation of Autonomous Weapons Systems (AWS) presents a similar challenge to arms control as biological weapons do and that many lessons learned from the Biological Weapons Convention (BWC) could be applied to the control of AWS. AWS that utilize “deep learning” are potentially unpredictable and uncontrollable weapons. International regulation efforts for AWS should focus on the development of safety and design standards for artificial intelligence (AI), should put in place confidence-building measures for enhancing transparency and trust in AI R&D and related applications, and should aim for a ban of offensive AWS. Enforced international transparency in the development of AI could make AI better and safer, including in a military context, which would improve strategic stability.

9 Poison, Poisoned Weapons, Asphyxiating Gases, Biological and Chemical Weapons

2016 ◽  
Author(s):  
Boothby William H
Keyword(s):  
Synthetic Biology ◽  
Arms Control ◽  
Biological Weapon ◽  
Biological Weapons ◽  
Chemical Weapons ◽  
Novel Technologies ◽  
Chemical Agents ◽  
The Status ◽  
Biological Weapons Convention

Chapter 9 looks at a group of weapon technologies. The long-standing and customary prohibition of the use of poisons and of poisoned weapons is examined first. Then the discussion addresses efforts in 1899 to address the use of asphyxiating gases, pointing out that a prohibition on use was only achieved in 1925 with the adoption of the Geneva Protocol. While that protocol also addressed bacteriological methods of warfare, comprehensive arms control provision prohibiting all forms of biological weapon had to await the adoption in 1972 of the Biological Weapons Convention, whereas similar provision in relation to chemical weapons was not achieved until 1993. Both of these conventions are considered, and the status of the prohibition on use, and of related provisions, in both treaties is analysed. Novel technologies including incapacitating chemical agents, synthetic biology and the use of viruses are also considered.

Deliberate Disease: Biological Weapons, Threats, and Policy Responses

1993 ◽  
Vol 11 (4) ◽  
pp. 395-417 ◽  
Author(s):  
M I Chevrier
Keyword(s):  
Arms Control ◽  
Matrix Analysis ◽  
Biological Weapons ◽  
Policy Responses ◽  
The Military ◽  
Biological Weapons Convention ◽  
Control Regime

The arguments for and against the acquisition of biological and toxin weapons (BTW) are examined. A country's decision to acquire such weapons is analyzed by means of matrix analysis, separating the effects of three parameters: The offensive capability of the aggressor, the retaliatory capability of the target, and the military purpose(s) to which the weapons would be applied. The research identifies those circumstances wherein BTW are most likely to be used. The findings have implications for the type of arms control regime that should be implemented to minimize the probability that these weapons will be used, and to control their proliferation. Specifically, the author makes recommendations concerning proposals to promote compliance with the 1972 Biological Weapons Convention.

United Nations Biological Warfare Inspectors in Iraq: Implications for Biological Arms Control—One Canadian's Perspective

1995 ◽  
Vol 14 (2) ◽  
pp. 259-262 ◽  
Author(s):  
Allen A. St-Onge
Keyword(s):  
United Nations ◽  
Arms Control ◽  
Biological Weapons ◽  
Biological Warfare ◽  
Specific Element ◽  
Special Commission ◽  
Canadian Perspective ◽  
The United Nations ◽  
Biological Weapons Convention

My contribution differs in several aspects from the others in this symposium. To begin, instead of addressing a specific element of future Biological Weapons Convention (BWC) verification operations, I have been asked for my unique “Canadian” perspective on the United Nations Special Commission (UNSCOM) inspections in which I have participated, and some of the lessons that I have come away with after having been a member of four inspections in 1994 and 1995.

scholarly journals New Technologies & Strategic Stability

Daedalus ◽  
2020 ◽  
Vol 149 (2) ◽  
pp. 150-170
Author(s):  
Christopher F. Chyba
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
New Technologies ◽  
Arms Control ◽  
Direct Impact ◽  
Weapon Systems ◽  
Major Powers ◽  
Strategic Stability ◽  
Enabling Technologies ◽  
And Diffusion

A variety of new technologies, ranging from broad enabling technologies to specific weapon systems, may threaten or enhance strategic stability. In this essay, I analyze a technology's potential to significantly affect stability along three axes: the pace of advances in, and diffusion of, this technology; the technology's implications for deterrence and defense; and the technology's potential for direct impact on crisis decision-making. I apply this framework to examples including hypersonic weapons, antisatellite weapons, artificial intelligence, and persistent overhead monitoring. Formal arms control to contain dangers posed by some of these seems technically possible, though currently politically difficult to achieve. Others, particularly enabling technologies, resist arms control based on effective verification. The major powers will therefore instead have to find other ways to cope with these technologies and their implications. These options should include exchanges with potential adversaries so that pathways to nuclear escalation, and possible mitigating steps, can be identified and discussed.

Developing an Artificial Intelligence Project in your Radiology Department

2020 ◽  
Vol 2 ◽  
pp. 58-61 ◽  
Author(s):  
Syed Junaid ◽  
Asad Saeed ◽  
Zeili Yang ◽  
Thomas Micic ◽  
Rajesh Botchu
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Health Care ◽  
Deep Learning ◽  
Learning Algorithms ◽  
Radiology Department ◽  
Short Article ◽  
Computing Power ◽  
Road Map ◽  
Key Concepts

The advances in deep learning algorithms, exponential computing power, and availability of digital patient data like never before have led to the wave of interest and investment in artificial intelligence in health care. No radiology conference is complete without a substantial dedication to AI. Many radiology departments are keen to get involved but are unsure of where and how to begin. This short article provides a simple road map to aid departments to get involved with the technology, demystify key concepts, and pique an interest in the field. We have broken down the journey into seven steps; problem, team, data, kit, neural network, validation, and governance.

Virtual Screening Meets Deep Learning

2018 ◽  
Vol 15 (1) ◽  
pp. 6-28 ◽  
Author(s):  
Javier Pérez-Sianes ◽  
Horacio Pérez-Sánchez ◽  
Fernando Díaz
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Deep Learning ◽  
Virtual Screening ◽  
Great Increase ◽  
New Drugs ◽  
Learning Approach ◽  
Screening Strategies ◽  
Computer Aided ◽  
Recent Developments

Background: Automated compound testing is currently the de facto standard method for drug screening, but it has not brought the great increase in the number of new drugs that was expected. Computer- aided compounds search, known as Virtual Screening, has shown the benefits to this field as a complement or even alternative to the robotic drug discovery. There are different methods and approaches to address this problem and most of them are often included in one of the main screening strategies. Machine learning, however, has established itself as a virtual screening methodology in its own right and it may grow in popularity with the new trends on artificial intelligence. Objective: This paper will attempt to provide a comprehensive and structured review that collects the most important proposals made so far in this area of research. Particular attention is given to some recent developments carried out in the machine learning field: the deep learning approach, which is pointed out as a future key player in the virtual screening landscape.

scholarly journals An overview of artificial intelligence/deep learning

Pathology ◽  
2021 ◽  
Vol 53 ◽  
pp. S6
Author(s):  
Jack Garland ◽  
Mindy Hu ◽  
Kilak Kesha ◽  
Charley Glenn ◽  
Michael Duffy ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Deep Learning
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