The principles (with my translation) are:

1. Public trust in AI. The government must promote reliable, robust, and trustworthy AI applications.
2. Public participation. The public should have a chance to provide feedback in all stages of the rule-making process.
3. Scientific integrity and information quality. Policy decisions should be based on science. 
4. Risk assessment and management. Agencies should decide which risks are and aren’t acceptable.
5. Benefits and costs. Agencies should weigh the societal impacts of all proposed regulations.
6. Flexibility. Any approach should be able to adapt to rapid changes and updates to AI applications.
7. Fairness and nondiscrimination. Agencies should make sure AI systems don’t discriminate illegally.
8. Disclosure and transparency. The public will trust AI only if it knows when and how it is being used.
9. Safety and security. Agencies should keep all data used by AI systems safe and secure.
10. Interagency coordination. Agencies should talk to one another to be consistent and predictable in AI-related policies.

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Artificial intelligence (AI) is a rapidly growing field of technology with potentially significant implications for national security. As such, the U.S. Department of Defense (DOD) and other nations are developing AI applications for a range of military functions. AI research is underway in the fields of intelligence collection and analysis, logistics, cyber operations, information operations, command and control, and in a variety of semiautonomous and autonomous vehicles. Already, AI has been incorporated into military operations in Iraq and Syria. Congressional action has the potential to shape the technology’s development further, with budgetary and legislative decisions influencing the growth of military applications as well as the pace of their adoption.

AI technologies present unique challenges for military integration, particularly because the bulk of AI development is happening in the commercial sector. Although AI is not unique in this regard, the defense acquisition process may need to be adapted for acquiring emerging technologies like AI. In addition, many commercial AI applications must undergo significant modification prior to being functional for the military. A number of cultural issues also challenge AI acquisition, as some commercial AI companies are averse to partnering with DOD due to ethical concerns, and even within the department, there can be resistance to incorporating AI technology into existing weapons systems and processes. Read More

There are four major findings about operations critical to the effectiveness and success of future of intelligence operations in 2035-2050 and beyond. The findings apply broadly not only to military intelligence, but the greater Intelligence Community (IC), the DoD, and by default to several other elements of our federal national security framework. However, realizing the Future Intelligence CONOPS 2035-2050 projection assumes addressing the findings. If not, it highly probable intelligence operations will continue to mimic the current reactive posture of today.

The four findings:

— The IC and DoD, created in 1947, continue to function in a primarily reactive posture, using the industrial age processes of the era in which they were created.
— Information & democratization of technology has changed the character of warfare.
— 2018 National Security and Defense Security Strategies address the new character of warfare.
— Immediate investments are required to enable the success and effectiveness of future intelligence operations in 2035-2050 and beyond. Read More

#dod, #ic