Two upcoming documents will reveal how the US Navy should fight in a great power competition

Sur le même sujet

• 

  26 août 2024 | International, Aérospatial

  UK to build F-35-sized ‘silent hangar’ to test jamming, electronic war

  The anechoic hangar is due to open in 2026 and will be one of the biggest in Europe, far bigger than existing facilities in Britain.

• 

  3 décembre 2021 | International, Aérospatial

  Les critères européens de l'ESG mettent la pression sur les entreprises européennes de défense

  Les entreprises européennes du secteur de la défense font face à des difficultés venues des investisseurs mettant en avant leur « responsabilité sociale ». Ces derniers exigent notamment de ces entreprises une plus grande transparence dans la fabrication et la vente d'armes, dans le cadre de la montée en puissance des critères ESG (environnemental, social et de gouvernance). L'ASD (l'association pour "Aeronautics, Space, Defence and Security Industries" en Europe) a écrit à la Commission européenne, soulignant les contradictions entre la volonté de l'UE de renforcer ses capacités en matière de défense et les projets de propositions sur les critères ESG. Déjà, certaines banques et investisseurs coupent les liens avec l'industrie, a déclaré Alessandro Profumo, président de l'ASD et directeur général du groupe de défense italien Leonardo. Plusieurs grandes entreprises de défense européennes, dont le français Thales et le britannique BAE Systems, ont intensifié leurs efforts pour expliquer ce qu'elles font et souligner leurs contributions aux économies et à la sécurité nationale. D'autres cadres européens avertissent qu'un écart d'évaluation est en train de se creuser avec les États-Unis, où les industries de défense sont plus largement acceptées. En considérant l'industrie de la défense comme socialement nuisible, l'UE pourrait mettre en péril sa propre sécurité. Financial Times du 1er décembre

• 

  4 février 2019 | International, C4ISR

  DARPA: Building Trusted Human-Machine Partnerships

  A key ingredient in effective teams – whether athletic, business, or military – is trust, which is based in part on mutual understanding of team members' competence to fulfill assigned roles. When it comes to forming effective teams of humans and autonomous systems, humans need timely and accurate insights about their machine partners' skills, experience, and reliability to trust them in dynamic environments. At present, autonomous systems cannot provide real-time feedback when changing conditions such as weather or lighting cause their competency to fluctuate. The machines' lack of awareness of their own competence and their inability to communicate it to their human partners reduces trust and undermines team effectiveness. To help transform machines from simple tools to trusted partners, DARPA today announced the Competency-Aware Machine Learning (CAML) program. CAML aims to develop machine learning systems that continuously assess their own performance in time-critical, dynamic situations and communicate that information to human team-members in an easily understood format. “If the machine can say, ‘I do well in these conditions, but I don't have a lot of experience in those conditions,' that will allow a better human-machine teaming,” said Jiangying Zhou, a program manager in DARPA's Defense Sciences Office. “The partner then can make a more informed choice.” That dynamic would support a force-multiplying effect, since the human would know the capabilities of his or her machine partners at all times and could employ them efficiently and effectively. In contrast, Zhou noted the challenge with state-of-the-art autonomous systems, which cannot assess or communicate their competence in rapidly changing situations. “Under what conditions do you let the machine do its job? Under what conditions should you put supervision on it? Which assets, or combination of assets, are best for your task? These are the kinds of questions CAML systems would be able to answer,” she said. Using a simplified example involving autonomous car technology, Zhou described how valuable CAML technology could be to a rider trying to decide which of two self-driving vehicles would be better suited for driving at night in the rain. The first vehicle might communicate that at night in the rain it knows if it is seeing a person or an inanimate object with 90 percent accuracy, and that it has completed the task more than 1,000 times. The second vehicle might communicate that it can distinguish between a person and an inanimate object at night in the rain with 99 percent accuracy, but has performed the task less than 100 times. Equipped with this information, the rider could make an informed decision about which vehicle to use. DARPA has scheduled a pre-recorded webcast CAML Proposers Day for potential proposers on February 20, 2019. Details are available at: https://go.usa.gov/xE9aQ. The CAML program seeks expertise in machine learning, artificial intelligence, pattern recognition, knowledge representation and reasoning, autonomous system modeling, human-machine interface, and cognitive computing. To maximize the pool of innovative proposal concepts, DARPA strongly encourages participation by non-traditional proposers, including small businesses, academic and research institutions, and first-time Government contractors. DARPA anticipates posting a CAML Broad Agency Announcement solicitation to the Federal Business Opportunities website in mid-February 2019. https://www.darpa.mil/news-events/2019-01-31