Artificial Intelligence and Machine Learning

Artificial Intelligence (AI), machine learning (ML) deep learning and data analytics are already impacting the security, public and private sectors. For example, the National Geospatial-Intelligence Agency (NGA) is one of the biggest generators of data in the Intelligence Community (IC). The volumes of data being collected and processed are increasing exponentially from a constant steam of satellite, drone and open source imagery collection sources. NGA plans to integrate AI to comb through this intelligence data and apply heavy advanced machine learning algorithms. What had taken many weeks to process could be accomplished in hours and minutes. AI is poised to become vital to NGA as new mission requirements become more complex.

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The IC has high aspirations for AI and digital transformation to save time and money, boost operational efficiency, improve key processes and increase productivity. This interaction of human and machine will be a game changer as new AI tools complement people skills.

Despite these digital ambitions there are implications. AI machines learn with human guidance with no immediate prospect of surpassing the human ability to process and respond to new and unexpected scenarios. This new technology is very capable of delivering great benefits and reducing risk, but the IC faces multiple challenges needed to adopt future innovation and transformation. These challenges should be addressed through:Artificial Intelligence and Machine Learning

• Provide IC leadership transformation guidance and policy direction in budget planning, resource management, personnel alignment, and establishing day-to-day priorities.
• Expand partnerships with private industry who lead in developing these new technologies, able to provide technical expertise, and increase research and development collaboration. Most AI research advances occurs in the private sector and academia.
• Manage the IC workforce to develop technical skills, incorporate new training, and form new teaming partnerships to access talent.
• Create a culture of change that embraces collaboration between the IT and analytical/collection sectors to improve speed and agility.
• Develop AI security processes to counter evolving threats such as misclassifying data, trojans and model inversion. Breaches can provide adversaries with sensitive and insights.
• Establish trust in AI technologies and manage expectations to ensure they align with the IC’s mission, core values and ethical principles so humans remain responsible for oversight and strategic thinking.

You are an intelligence staff officer in the Office of the Director of National Intelligence and tasked to write a paper on the integration of AI, ML, deep learning and data analytics throughout the IC. Address at least three of the six listed challenges providing background, issues and recommendations.

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Format your paper is to provide the fundamentals:
• APA format cover page: Include the title of the paper, your name, class title, and date of submission.
• Introduction: Make an introductory abstract about the subject of your paper. Provide the specific issues being addressed.
• Text: State your position and address the fundamental issues that support your challenges.
• Conclusion: Provide a focused, concise conclusion based on your analysis and logical findings.
• References: Provide references on a separate page with complete citations in accordance with the APA style manual.

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