Artificial Intelligence (AI) is the buzz word now, everyone everywhere in every business is talking about it. While AI offers a treasure trove of capabilities – from chatbots and image generation to intelligent automation – it’s crucial to acknowledge the potential dangers lurking beneath the surface. The public and private sectors are investing significantly in the development of AI, as the market for the technology is expanding. A Deltek Federal Artificial Intelligence Landscape report states that between 2020 and 2022, federal funding on AI increased by 36%, with a primary emphasis on research and development.[i]
The value of artificial intelligence (AI) is expected to grow up to nearly $2 Trillion by 2030.[ii]
Nevertheless, cybersecurity experts continue to exercise caution despite this quick adoption of AI. Their main concerns, according to a study conducted in 2023, were shortage of experienced staff (40%) to manage and secure these complex systems, data privacy and security (45%), and AI efficacy (43%). Therefore, securing technology in addition to innovation will be essential to realizing its full potential and reducing any hazards.[iii]
Security Considerations for AI
Security is rapidly changing due to AI. AI improves security by enhancing threat detection, response capabilities, and overall cybersecurity measures by advanced threat detection real-time monitoring, analyzing data for unusual patterns and behaviors, and enabling early threat detection. In support of this trend, a recent study of federal cybersecurity officials found that 64% of them already utilize AI/ML for user activity analysis and 63% use it for proactive threat hunting and automated threat detection.[iv]
Government agencies that adopt AI technology can improve their security posture, increase efficiency, and foster innovation. However, due to its high potential threat actors are also exploiting this new technology. Although agencies can leverage AI to strengthen their cyber defenses, to stay safe and compliant, they must also constantly monitor emerging risks and follow changing governance norms. Below are the security considerations when implementing AI:
- Data breaches and Privacy Violations – The data used to train AI models can be sensitive. Breaches or unauthorized access can compromise privacy and lead to misuse. Robust data security practices are essential, including data quality, integrity, encryption, access control, and data governance compliance.
- Algorithm Transparency and Accountability – Complex AI models can be opaque, posing risks of bias and errors. Ensuring transparency is crucial for fairness and accountability. U.S. Government Accountability Office’s (GAO) AI Accountability Framework helps Congress address AI complexities, focusing on governance, data, performance, and monitoring to ensure responsible AI use by federal agencies and other entities.[v]
- Bias in AI Models – Biases in AI models can arise not only from training data but also from the design and deployment processes. Training data may contain inherent biases, and these can be amplified by the algorithms used to process the data. Agencies can mitigate these biases by employing diverse and representative datasets, regularly auditing models for fairness, and incorporating ethical guidelines into the development process. Continuous monitoring and updating of both data and algorithms are essential to address emerging biases and ensure equitable outcomes. Ongoing efforts should also include transparent reporting and stakeholder engagement to maintain fairness and accountability.
- Adversarial attacks: Adversarial attacks involve minor adjustments to input data by malicious actors to manipulate AI models and lead to incorrect conclusions, necessitating robust models and detection methods. A specific type of adversarial attack, known as prompt injection, involves malicious inputs disguised as legitimate prompts to exploit AI models, particularly large language models (LLMs). Attackers can cause models to leak sensitive data, spread misinformation, or execute harmful actions. Mitigation strategies include implementing filters, applying least privilege principles, and involving human oversight to verify outputs.
- Model Security: Model interpretability, vulnerability management, and secure coding techniques are essential. Complete validation, anomaly identification, and proactive error management should all be done. Signing procedures serve as a means of ensuring the integrity of outsourced models, protecting AI systems, and preserving stability.
- Secure AI Development, Testing, and Deployment– By adding security at every stage of the AI lifecycle, you can guarantee safe AI development and implementation. Use reliable data management, secure infrastructure, and secure coding techniques while training and executing models. Conduct thorough testing, including model validation and anomaly detection, to identify vulnerabilities. Continuous vulnerability and anomaly monitoring is critical for addressing possible security threats and maintaining system integrity.
- Employee Training and Awareness – Ensure employees are thoroughly trained on AI security practices. Educate them on company policies, responsible AI use, intellectual property management, secure AI implementation, and business continuity. Continuous awareness and training are vital for maintaining a healthy security posture and mitigating risks associated with AI usage
In a 2023 survey of cybersecurity professionals, over 70% highlighted AI programming and development as the most crucial future skills in AI cybersecurity. Security management followed closely at 67%, while 64% emphasized the importance of ethics and responsible use of AI.[vi]
Regulatory Laws and Policy Frameworks to Ensure Ethical Use of AI
When it comes to AI governance, policy frameworks, and regulatory legislation are the cornerstones that guarantee the ethical application of AI. Examining the current environment, we must talk about the rules that are in place as well as any future that might affect AI security in the federal government. Maintaining integrity and confidence in AI systems requires highlighting how important it is to follow these rules.
In 2023, significant strides were made in establishing frameworks governing AI usage within the federal government. The White House unveiled the Blueprint for an AI Bill of Rights, which lays out five tenets to protect American citizens from hazards associated with AI. These guidelines cover the providing of notice and explanation, safeguarding against algorithmic prejudice, maintaining data privacy, ensuring safe and efficient systems, and considering fallback and human alternatives. [vii]
President Biden’s Executive Order dated October 30, 2023, confirmed the government’s commitment to AI regulation. This order lays out bold goals to properly manage the risks associated with AI, preserve privacy, respect equity and civil rights, strengthen consumer and worker safeguards, encourage competition and innovation, and establish American leadership in the field of AI worldwide. Despite receiving praise for its all-encompassing approach, the executive order has sparked discussions about how to implement it and if it can be enforced, which marks the start of a more involved regulatory process.[viii]
In alignment with these efforts, the Department of Defense (DoD) unveiled the establishment of Task Force Lima, dedicated to harnessing the potential of generative AI technologies responsibly. Task Force Lima’s mandate encompasses the analysis, integration, and strategic deployment of generative AI tools, such as large language models (LLMs), across the DoD. By ensuring the synchronization and utilization of these capabilities, the DoD endeavors to maintain technological supremacy while safeguarding national security interests.[ix]
Furthermore, programs like as the NIST AI Risk Management Framework offer priceless direction for integrating reliability factors into the conception, creation, implementation, and assessment of AI systems, services, and goods. Stakeholders can confidently traverse the challenging landscape of AI governance by abiding by such frameworks and laws, ensuring that technology breakthroughs balance potential hazards with the societal objectives they serve.[x]
Secure the Future and Wield Wisely with AI
Artificial intelligence is a dynamic force that is always expanding in terms of its potential applications and social impact. Reputable AI projects recognize the potential impact AI may have on people and society and work to properly harness its power for good. But as AI advances, there are drawbacks as well, especially in cybersecurity. Cyber dangers are made easier by it, but it also provides answers. To counteract emerging cyberthreats, organizations need to prioritize cybersecurity and implement state-of-the-art AI technologies.
Securing deployment environments, checking the origins of AI models, making sure that architectures are strong, and imposing strict access controls are important procedures. Ignoring these precautions runs the danger of serious repercussions, such as cascading effects and model corruption. Navigating the disruptive world of artificial intelligence requires proactive security measures. NetImpact’s AI.Impact® services stands at the forefront of innovation and help government design, develop and deploy safe, secure and responsible AI aligned with agency strategy and mandates.
Learn how we harness the power of artificial intelligence to tackle complex challenges, streamline operations, and boost productivity without compromising secure and responsible practices.
