Mattermost announces AI-Enhanced Secure Collaboration Platform to enable both innovation and data control for government and technology organizations

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How AWS Partners are advancing generative AI for government, health care, and other public sector organizations

Secure and Compliant AI for Governments

The content filters that will serve as the first line of defense against extremist recruiting, misinformation and disinformation campaigns, and the spread of hate and encouragement of genocide can be rendered ineffective with AI attacks. A U.S. military transitioning to a new era of adversaries that are its technological equals or even superiors must develop and protect against this new weapon. Law enforcement, an industry that has perhaps fallen victim to technological upheaval like no other, risks its efforts at modernizing being undermined by the very technology it is looking at to solve its problems.

What is AI in governance?

AI governance is the ability to direct, manage and monitor the AI activities of an organization. This practice includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits.

By taking a proactive approach towards protecting personal information online while also advocating for stronger policies at a larger scale, citizens play a significant role in the creation of a safer digital environment for all. Furthermore, governments should invest in research and development initiatives targeted at enhancing cybersecurity capabilities. This includes funding academic institutions conducting cutting-edge research on encryption technologies or supporting startups developing innovative solutions to protect against potential vulnerabilities inherent in AI systems.

Using AI and Generative AI for cloud-based modernization of federal agencies

One of the key components of ensuring compliance with AI regulations is conducting security testing, such as red teaming. Red teaming is a form of adversarial model testing that attempts to identify undesirable behavior in an AI system, using methods such as prompt injection to expose the system’s latent biases. The EO focuses on developing guidelines, standards, and best practices for the safety and security of AI systems. Conversational AI is a sophisticated form of artificial intelligence designed to enable seamless interaction between humans and computers through voice or text.

Fourth, the rules, risk levels, and levels of protection measures should be defined in consultation with a great many relevantly-experienced experts. The simplest way to regulate AI would to prohibit everything, but it looks like this approach isn’t on the table yet. Therefore, all reasonable regulation attempts should follow the principle of “the greater the risk, the stricter the requirements”.

Evaluating the challenges and limitations of conversational AI in the public sector

This may lead to premature replacement of humans with algorithms in domains where the threats of attack or failure are severe yet unknown. This will hold particularly true for applications of AI to safety and national security. AI security compliance programs should be enforced for portions of both the public sectors. Further, because the government is turning to the private sector to develop its AI systems, compliance should be mandated as a precondition for companies selling AI systems to the government. Government applications for which truly no risk of attack exists, for example in situations where a successful attack would have no effect, can apply for a compliance waiver through a process that would review the circumstances and determine if a waiver is appropriate.

With care, transparency, and responsible leadership, conversational AI can unlock a brighter future where high-quality public services are profoundly more accessible, inclusive, and personalized for all. Redmond claims it has developed an architecture that enables government customers “to securely access the large language models in the commercial environment from Azure Government.” Access is made via REST APIs, a Python SDK, or Azure AI Studio, all without exposing government data to the public internet – or so says Microsoft. The AIOps teams at major tech companies such as Microsoft, Google, OpenAI, and Meta are already using red teaming to evaluate and improve the security of their AI systems.

Challenges

If classified or confidential information falls into the enemy’s hands, it could lead to a compromise of intelligence operations and expose the vulnerability of a country’s infrastructure. As innovation moves forward, the industry needs security standards for building and deploying AI responsibly. That’s why we introduced the Secure AI Framework (SAIF), a conceptual framework to secure AI systems. (a)  There is established, within the Executive Office of the President, the White House Artificial Intelligence Council (White House AI Council). The function of the White House AI Council is to coordinate the activities of agencies across the Federal Government to ensure the effective formulation, development, communication, industry engagement related to, and timely implementation of AI-related policies, including policies set forth in this order.

Secure and Compliant AI for Governments

For example, CrushBank’s AI Knowledge Management platform leverages watsonx to transform IT support, helping the company to streamline help desk operations with AI by arming its IT staff with better information. According to CrushBank, this has led to improved productivity and a decrease in time to resolution by 45%, ultimately enhancing the customer experience. Cory, a veteran of the United States Navy, brings his wealth of knowledge and experience in technology, data governance, security, and privacy legislation to the United States Federal Government, State Agencies, and enterprise businesses as an advocate for data driven organizations. Currently there are no broad-based regulations focusing on AI safety, and the first set of legislation by the European Union is yet to become law as lawmakers are yet to agree on several issues. Since producing frontier AI systems is harder than using them, diffusion significantly lowers the barriers to the misuse of frontier AI. AI system flaws and vulnerabilities are relatively easy to find and manipulate, yet they are much more difficult to guard against and fix than in the case of traditional software.

Companies Covered

It guides visitors around the website, answers basic questions, and redirects to a human correspondent when needed. They provide a comprehensive knowledge base for citizens with multilingual support and collect citizen feedback on a large scale. Plot the best routes for your training data with 8 workflow stages to arrange, connect, and loop any way you need.

  • Since producing frontier AI systems is harder than using them, diffusion significantly lowers the barriers to the misuse of frontier AI.
  • My Administration places the highest urgency on governing the development and use of AI safely and responsibly, and is therefore advancing a coordinated, Federal Government-wide approach to doing so.
  • Cory, a veteran of the United States Navy, brings his wealth of knowledge and experience in technology, data governance, security, and privacy legislation to the United States Federal Government, State Agencies, and enterprise businesses as an advocate for data driven organizations.
  • Much like the case with content filtering, the law enforcement community views the new generation of AI-enabled tools as necessary to keep pace with their expanding technological purview.

IDC foresees AI as an increasingly critical factor impacting security operations across forms of government. Deepset has long been committed to helping organizations navigate the evolving AI regulatory landscape. We’re SOC 2 Type 2 certified, but our commitment to ensuring our organization and those we serve meet evolving AI compliance guidelines doesn’t stop there. Our LLM platform for AI teams, deepset Cloud, is built with the highest security standards in mind. While the EU AI Act is not yet an active law, organizations working on new AI use cases should be aware of it as they develop their own AI systems, and build future-proof processes that ensure the traceability and documentation of systems created today.

While the regular image would be classified correctly by the AI system as a “panda”, the attack object is incorrectly classified as a “monkey”. However, because the attack pattern makes such small changes, to the human eye, the attack image looks identical to the original regular image. Unlike traditional cyberattacks that are caused by “bugs” or human mistakes in code, AI attacks are enabled by inherent limitations in the underlying AI algorithms that currently cannot be fixed. Further, AI attacks fundamentally expand the set of entities that can be used to execute cyberattacks. For the first time, physical objects can be now used for cyberattacks (e.g., an AI attack can transform a stop sign into a green light in the eyes of a self-driving car by simply placing a few pieces of tape on the stop sign itself). Data can also be weaponized in new ways using these attacks, requiring changes in the way data is collected, stored, and used.

Secure and Compliant AI for Governments

The lack of transparency in the drafting process raises concerns about the impact and effectiveness of the regulations that will emerge. V7’s image annotation and video annotaion tools help government organizations manage high-quality transportation datasets. As a result, agencies can train robust traffic models with advanced monitoring capabilities. Whether a strict approach to AI development like in the European model, a lighter set of guidelines like those currently used in the United States, or self-regulation by the companies which are programming and crafting new AIs, it’s clear that some form of regulation or guidance is probably needed. Even the developers working on AI projects acknowledge that the technology could prove dangerous under certain circumstances, especially as it continues to advance and improve its capabilities over the next few years.

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We asked Microsoft for clarification on how it would retain AI prompt and completion data from government users, but a spokesperson only referred us back to the company’s original announcement without any direct answers to our questions. “Only the queries submitted to the Azure OpenAI Service transit into the Azure OpenAI model in the commercial environment,” Microsoft promised, adding that “Azure Government peers directly with the commercial Microsoft Azure network and doesn’t peer directly with the public internet or the Microsoft corporate network.” You can contribute code or issues, discover documentation, and get started with AI security with our Apache 2.0 licensed Open Source projects. We were named one of the best early stage companies of 2023 in Fortune’s annual list of 60 best cyber companies. Provide end-to-end visibility by connecting leading Agile and DevOps solutions across the Agency’s development and software delivery disciplines. Don’t miss our previous installments, including the Sept. 20 London Summit special edition and the Sept. 29 edition on the industry impact of Cisco’s Splunk acquisition.

  • Countries like China and other oppressive regimes use AI as a way to track, control, and intimidate their citizens.
  • But for policymakers and stakeholders alike, the first step towards realizing this security begins with understanding the problem, which we turn our attention to now.
  • We’ll cover everything from critical use cases to challenges to workforce implications.
  • Protect the assets that can be used to craft AI attacks, such as datasets and models, and improve the cybersecurity of the systems on which these assets are stored.

For ultimate caption security, you can combine Encoder Pro with LEXI Local, which delivers live automatic captions on-premises and off the cloud. This provides elevated security and greater control over your data, without compromising the quality of your captions. Pair LEXI Local with our Encoder Pro SDI encoder for a reliable, low-latency captioning solution that’s trusted by government agencies worldwide. In Microsoft, there’s a service called Azure Open AI on your data, and some government agencies have connected that their own SharePoint repositories to begin to perform some of the capabilities you would expect Copilot to have with their data. This allows organizations to experiment and learn how Copilot works and raises questions about how it can revolutionize government tenants.

Secure and Compliant AI for Governments

In this case, care must be taken that adversaries cannot access or manipulate the models stored on systems over which they otherwise have full control. Implementation stage compliance requirements focus on ensuring stakeholders are taking proper precautionary steps as they build and deploy their AI systems. This includes securing assets that can be used to launch AI attacks, and improving detection systems that can warn when attacks are being formulated. As such, when writing data sharing policies, AI users must challenge these established norms, consider the risks posed by data sharing, and shape data sharing policies accordingly. Without this, constituent parties may not realize the strategic importance data provides to attackers, and therefore may not take the steps necessary to protect it in the absence of explicit policy.

Secure and Compliant AI for Governments

In edge computing, rather than sending data to a centralized cloud infrastructure for processing, the data and AI algorithms are stored and run directly on the devices deployed in the field. The DoD has made the development of “edge computing” a priority, as the bandwidth needed to support a cloud-based AI paradigm is unlikely to be available in battlefield environments.38 This reality will require these systems to be treated with care. Just as the military recognizes the threat created when a plane, drone, or weapon system is captured by an enemy, these AI systems must be recognized and treated as a member of this same protected class so that the systems are not compromised if captured by an enemy. We now turn our attention to which systems and segments of society are most likely to be impacted by AI attacks. AI systems are already integrated into many facets of society, and increasingly so every day. For industry and policy makers, the five most pressing vulnerable areas are content filters, military systems, law enforcement systems, traditionally human-based tasks being replaced with AI, and civil society.

How is AI used in the Defence industry?

An AI-enabled defensive approach allows cyber teams to stay ahead of the threat as machine learning (ML) technology improves the speed and efficacy of both threat detection and response, providing greater protection.

(C)  implications for workers of employers’ AI-related collection and use of data about them, including transparency, engagement, management, and activity protected under worker-protection laws. (C)  launching an initiative to create guidance and benchmarks for evaluating and auditing AI capabilities, with a focus on capabilities through which AI could cause harm, such as in the areas of cybersecurity and biosecurity. (v)  The term “national security system” has the meaning set forth in 44 U.S.C. 3552(b)(6).

Uncle Sam threatens AI with its nastiest weapon: An audit – The Register

Uncle Sam threatens AI with its nastiest weapon: An audit.

Posted: Tue, 11 Apr 2023 07:00:00 GMT [source]

While AI has the potential to be used for increased security and compliance, there are also concerns that AI could be used to fuel security breaches and expose private information. Reactive AI is an early form of AI that doesn’t have a “memory.” When a specific input is fed through the algorithm, the output will always be the same. It can process large volumes of data but doesn’t take into account factors like historical data. In addition, IT leaders benefit from Domino, with a single platform that delivers self-service access to tools and infrastructure that are secure and compliant. Model management lacks standardization and governance guardrails, and a lack of model monitoring results in model drift, and risk.

Secure and Compliant AI for Governments

Read more about Secure and Compliant AI for Governments here.

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.

How AI can be used in government?

The federal government is leveraging AI to better serve the public across a wide array of use cases, including in healthcare, transportation, the environment, and benefits delivery. The federal government is also establishing strong guardrails to ensure its use of AI keeps people safe and doesn't violate their rights.

What is the executive order on safe secure and trustworthy development and use of artificial intelligence?

14110 on Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence. It establishes a government-wide effort to guide responsible artificial intelligence (AI) development and deployment through federal agency leadership, regulation of industry, and engagement with international partners.

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