How viable is international arms control for military artificial intelligence? Three lessons from nuclear weapons

Many observers anticipate “arms races” between states seeking to deploy artificial intelligence (AI) in diverse military applications, some of which raise concerns on ethical and legal grounds, or from the perspective of strategic stability or accident risk. How viable are arms control regimes for military AI? This article draws a parallel with the experience in controlling nuclear weapons, to examine the opportunities and pitfalls of efforts to prevent, channel, or contain the militarization of AI. It applies three analytical lenses to argue that (1) norm institutionalization can counter or slow proliferation; (2) organized “epistemic communities” of experts can effectively catalyze arms control; (3) many military AI applications will remain susceptible to “normal accidents,” such that assurances of “meaningful human control” are largely inadequate. I conclude that while there are key differences, understanding these lessons remains essential to those seeking to pursue or study the next chapter in global arms control.     

The Bush War to Save the Rhino: Improving Counter-poaching Through Intelligence

The rhino is going extinct due to poaching at a rate which far outstrips current law enforcement or conservation efforts to halt their decline. A critical aspect of counter-poaching failures to date is an inaccurate view of the nature of poaching as a crime. Rather than demand-side efforts, attacking elusive smuggling networks or expensive technical solutions like drones, this article notes how a quasi-military tactical approach of ‘combat tracking’ offers the best way to protect the species. Based on wide ranging interviews and fieldwork across dozens of parks in southern Africa, it demonstrates how the current restricted range of the rhino, and the rarity of skilled poachers, makes a tactical solution the most effective to date.     

边防部队思想政治教育“生态”变化及其对策

新时期，公安边防部队思想政治教育所处的“生态”发生了巨大变化，部队传统的“单向”、重任务轻效果、经验型、“单打一”的思想政治教育模式，已经不能完全满足部队建设发展的需要。进一步改进部队思想政治教育的方式方法，建立符合新时期公安边防部队实际需要的思想政治教育新模式，对进一步发挥部队思想政治教育实效性具有重要意义。     

基于混合算法的局部路径规划

人工势场法是一种常用的具有算法简单和便于实时控制的局部路径规划方法,但存在容易产生局部极小值的问题。基于模糊逻辑的局部路径规划法具有环境适应性强等优点,它在连续论域内采用模糊路径规划时,计算量比较大。提出了一种将人工势场法和模糊逻辑法相结合进行局部路径规划的混合算法。具体方法是在一般情况下采用人工势场法进行局部路径规划,当产生局部极小值时,采用模糊逻辑法进行局部路径规划。仿真结果表明,该方法能有效地解决局部极小值问题,给智能车规划出光滑的路径。