Attacking Artificial Intelligence: AIs Security Vulnerability and What Policymakers Can Do About It Belfer Center for Science and International Affairs

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Secure and Compliant AI for Governments

Collibra AI Governance isn’t just about mitigating risks and ensuring compliance; it also helps maximize the return on investment (ROI) for AI initiatives. By providing a structured approach to managing AI data assets and processes, organizations can optimize their AI models for better performance and efficiency. AI Governance enables the organization to identify and eliminate redundant or irrelevant data, reducing data storage costs. It also streamlines data integration, reducing data silos and enhancing collaboration across teams. Collibra AI Governance has emerged as a critical component for ensuring responsible and effective AI implementations, from the start of these initiatives and throughout their lifecycle.

Mitigating the risks means improving your AI literacy – and you must be ready to get your hands dirty. You need to understand how it functions and test it, then educate people on how to use it and how not to use it to ensure your workforce can safely use it. If organizations aren’t mindful of these challenges, it will affect real people involved in data-driven decisions derived from these results. The average age of senators is the highest it has ever been, and in many public Congressional hearings on technology, some of the most ridiculous questions you can imagine have been asked. There is legitimate concern that many of the most powerful people in government do not fundamentally understand how AI and the Internet work, which creates doubt that they are up to the task of actually regulating it. With more AI-generated content created by the day, it’s becoming more challenging for the general public to discern between what is real and what is not.


My Administration will engage with international allies and partners in developing a framework to manage AI’s risks, unlock AI’s potential for good, and promote common approaches to shared challenges. The unfettered building of artificial intelligence into these critical aspects of society is weaving a fabric of future vulnerability. Policymakers must begin addressing this issue today to protect against these dangers by creating AI security compliance programs. These programs will create a set of best practices that will ensure AI users are taking the proper precautionary steps to protect themselves from attack. In high-risk application areas of AI, such as government and critical industry use of AI, compliance can be mandatory and enforced by the appropriate regulatory bodies. In low-risk application areas of AI, compliance can be optional in order to not stifle innovation in this rapidly changing field.

How can AI be secure?

Sophisticated AI cybersecurity tools have the capability to compute and analyze large sets of data allowing them to develop activity patterns that indicate potential malicious behavior. In this sense, AI emulates the threat-detection aptitude of its human counterparts.

As discussed in the mitigation stage compliance requirements below, system operators should have a predetermined plan that specifies exactly the actions that should be taken in the case of system compromise, and put the plan into action immediately. This implementation decision should state how much AI should be used within an application, ranging from full use, through limited use with human oversight, to no use. This spectrum affirms that vulnerability to attacks does not necessarily mean that a particular application is ill-suited for AI. Instead, suitability should be measured by the informed results of the suitability test, especially the questions regarding the consequences of an attack and the availability of other options.

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As is the case with other compliance efforts, a company that demonstrates that it made a good faith effort to reach an informed decision via a suitability test may face more lenient consequences from regulators in the case of attacks than those that disregarded the tests. In terms of implementing these suitability tests, regulators should play a supportive role. In areas requiring more regulatory oversight, regulators should write domain specific tests and evaluation metrics to be used. In areas requiring less regulatory oversight, they should write general guidelines to be followed. Beyond this, regulators should provide advice and counsel where needed, both in helping entities answer the questions that make up the tests as well as in forming a final implementation decision.

Researchers have also regularly induced or discovered new capabilities after model training through techniques including fine tuning, tool use, and prompt engineering. Therefore, dangerous capabilities could arise unpredictably and—absent requirements to do intensive testing and evaluation pre- and post-deployment—could remain undetected and unaddressed until it is too late to avoid severe harm. And artificial intelligence today presents seismic unknowns that we would be wise to ponder.

In the future, AI will continue to automate processes and improve detection for fraud and security risks, making it easier for businesses to stay in compliance with regulations and keep important data secure. But, looking to use artificial intelligence must take care to implement it responsibly and ethically. In the next decades, we will see the rise of AI especially in industries that rely extensively on personal data like healthcare and finance.

Secure and Compliant AI for Governments

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How can AI improve the economy?

AI has redefined aspects of economics and finance, enabling complete information, reduced margins of error and better market outcome predictions. In economics, price is often set based on aggregate demand and supply. However, AI systems can enable specific individual prices based on different price elasticities.

Why is AI governance needed?

AI governance is needed in this digital technologies era for several reasons: Ethical concerns: AI technologies have the potential to impact individuals and society in significant ways, such as privacy violations, discrimination, and safety risks.

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