Benefits of Conversational AI in Government
I’ve been banging on about the serious risks inherent in the Internet of Things and about vulnerabilities in industrial equipment for over a decade already, while documents like the EU Cyber Resilience Act first appeared (as drafts!) only last year. AI relies on sets of rules called algorithms that give the system instructions or guidelines for completing tasks and uncovering information. (iii) ensure that such efforts are guided by principles set out in the NIST AI Risk Management Framework and United States Government National Standards Strategy for Critical and Emerging Technology.
We can tailor our technology to suit your needs - simply book a call with us to explore the various options available for simplifying content creation. 3 min read - The new LSM is our most accurate speech model yet, outperforming OpenAI’s Whisper model on short-form English use cases. "Governments should also mandate that companies are legally liable for harms from their frontier AI systems that can be reasonably foreseen and prevented," according to the paper written by three Turing Award winners, a Nobel laureate, and more than a dozen top AI academics. Fox Rothschild LLP is a national law firm of 1000 attorneys in offices throughout the United States. We’ve been serving clients for more than a century, and we’ve been climbing the ranks of the nation’s largest firms for many years, according to both The Am Law 100 and The National Law Journal.
Data privacy and security in an AI-driven government
Microsoft 365 Copilot for government is also expected to roll out during the summer of 2024, giving access to a “transformational AI assistant in GCC, bringing generative AI to our comprehensive productivity suite for a host of government users,” according to the blog post. By combining AI-Media’s LEXI automatic captions with our Alta IP encoder, the broadcaster simplified these complex demands with a scalable end-to-end live captioning solution. While iCap Alta ensured seamless caption delivery with next-gen workflows that saved time and reduced costs. AvePoint provides the most advanced platform to optimize SaaS operations and secure collaboration. More than 17,000 customers worldwide rely on our solutions to make them more productive, compliant and secure.
- To forestall these issues, governments have begun putting in place regulations geared at ensuring data privacy and security across different cultures.
- One recent study found that the safety filters in one of Meta’s open-sourced models could be removed with less than $200 worth of technical resources.
- These reviews should be formal, identify emerging ways data can be weaponized against systems, and be used to shape data collection and use practices.
- This is because if the algorithm sees enough examples in all of the different ways the target naturally appears, it will learn to recognize all the patterns needed to perform its job well.
- This option has a significantly lower initial investment and ongoing expenses compared to building an in-house solution.
As a result, there is a need to rapidly understand how a compromise of one asset or system affects other systems. Determine how AI attacks are most likely to be used, and craft response plans for these scenarios. Regardless of the methods used, once a system operator is aware that an intrusion has occurred that may compromise the system or that an attack is being formulated, the operator must immediately switch into mitigation mode.
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As such, policymakers must be ready to address both scenarios, as each will require different interventions. Together, these challenges are an especially worrisome point given the current climate in which police departments are on the front lines of fighting terrorism. A technological system that is fragmented and not properly handled may disadvantage police forces in the face of advanced adversaries. This situation may call for additional coordination from sources such as DHS to unify purchasing and security standards. By removing foreign assets that are dangerous, illegal, or against the terms-of-service of a particular application, they keep platforms healthy and root out infections.
Why is artificial intelligence important in national security?
Advances in AI will affect national security by driving change in three areas: military superiority, information superiority, and economic superiority. For military superiority, progress in AI will both enable new capabilities and make existing capabilities affordable to a broader range of actors.
U.S. policy may therefore warrant treating the same exact attack/“attack” differently depending on context. A kidnapper wearing these glasses at a gas station to evade detection by a police force applying AI to find the suspect from thousands of video streams poses a threat to societal safety. A Uighur Muslim wearing these glasses to evade detection by Chinese government officials represents the protection of religious freedom. Finally, the military faces the challenge that AI attacks will be difficult, if not impossible, to detect in battle conditions. This is because a hack of these systems to obtain information to formulate an attack would not by itself necessarily trigger a notification, especially in the case where an attacker is only interested in reconnaissance aimed at learning the datasets or types of tools being used. Further, once adversaries develop an attack, they may exercise extreme caution in their application of it in order to not arouse suspicion and to avoid letting their opponent know that its systems have been compromised.
How viAct aids Public Sector Services?
This effectively poisons the data from the start, rather than changing an otherwise valid dataset as shown in the example above. While physical attacks are easiest to think of in terms of objects, including stop signs, fire trucks, glasses, and even humans, they are also applicable to other physical phenomena, such as sound. For example, attacks have been shown on voice controlled digital assistants, where a sound has been used to trigger action from the digital assistant.16 Alterations are made directly to or placed on top of these targets in order to craft an attack. Given enough data, the patterns learned in this manner are of such high quality that they can even outperform humans on many tasks. This is because if the algorithm sees enough examples in all of the different ways the target naturally appears, it will learn to recognize all the patterns needed to perform its job well.
For customers, AI can help detect and prevent fraud by analyzing records and transactions to learn normal behaviors and detecting outliers. To strike a balance between reaping the benefits of AI technology and protecting individuals’ privacy rights, governments need to seriously prioritize data privacy and security measures. This involves not only complying with existing laws but also enacting new regulations that specifically support a government system driven by AI. As governments around the world embrace artificial intelligence (AI) to enhance their operations and services, it is important to look into the challenges surrounding data privacy and security. While AI offers numerous benefits, such as improved efficiency and decision-making, it also raises legitimate worries about the protection of personal information. For proper enforcement of these laws, governments have put in place regulatory bodies saddled with overseeing compliance.
What You Need to Know About CMMC 2.0 Compliance
In the context of other consumer applications, this may fall to other agencies such as the FTC. Although law enforcement and the military share many similar AI applications, the law enforcement community faces its own unique set of challenges in securing against AI attacks. First, law enforcement AI systems will largely be off-the-shelf purchases from different private companies. Unlike the military, most law enforcement organizations are small and lack the resources needed to scope, let alone build, these AI systems, and will therefore likely rely on a patchwork of different private providers. Private companies have already shown an ineptitude to properly address known and easily addressed security vulnerabilities, let alone an emerging and difficult vulnerability such as AI attacks.
For instance, Booz Allen identified that common cyber defense tools do not detect intrusion until 200 days after. In summary, AI in government enables authorities to enforce policies that result in better infrastructure monitoring to fight tax evasion and unlawful property changes. Manual administration is challenging and often proves insufficient in identifying land developments. For instance, during the pandemic, AI impacted the detection and control of the COVID-19 virus. World Health Organization (WHO) estimates that 1.3 million people die in road crashes yearly. By effectively applying AI in transportation, governments can significantly reduce road safety issues.
Part II: Impacted Systems
Thanks to large language models like GPT-4, not only is there more AI-generated content – it is also increasingly hard to distinguish from human-generated content. To mitigate the creation of fake news, deep fakes, and the like, regulators in the US and EU are planning to create mechanisms to help end users distinguish the origin of content. While there's no law yet, the recent executive order in the U.S. requires the Department of Commerce to issue guidance on tools and best practices for identifying AI-generated synthetic content. Furthermore, it includes efforts to enhance training programs in high-performance computing, provide intellectual property (IP) and patent guidance for AI-related inventions, and mitigate AI-related IP risks. It prioritizes responsible AI innovation in healthcare, hosts AI Tech Sprint competitions for veterans' healthcare, explores AI's role in strengthening climate resilience, and mandates a report on AI's potential role in scientific research. As government organizations pursue digital transformation, technologies like conversational AI will be critical to optimizing operational costs and delivering seamless citizen services.
We also recently announced IBM and VMware are pairing VMware Cloud Foundation, Red Hat OpenShift and the IBM watsonx AI and data platform. This combination will enable enterprises to access IBM watsonx in private, on-premises Infrastructure as a Service (IaaS) environments as well as hybrid cloud with watsonx SaaS offerings on IBM Cloud. Additionally, clients can optionally use IBM Cloud Satellite to automate and simplify deployment and day two operations of their VMware Private AI with OpenShift environments. Bret Bailine is a seasoned field sales engineer bringing value to public and private sector organizations with Enterprise scale platforms.
Data scientists, contractors and collaborators can access on-demand compute infrastructure and commercial and open source data, tools, models, and projects—across any on-prem, GovCloud and hybrid/multi-cloud environments. With Domino, agencies can improve collaboration and governance, while establishing AI standards and best practices that accelerate their missions. While governments bear significant responsibility in protecting citizens’ data within an AI-driven government framework, individuals also play a vital role in protecting their information. Citizens need to be more conscious of their rights regarding their personal data’s collection, storage, usage, and disposal by government entities. By staying informed about relevant policies and taking proactive measures like regularly reviewing permissions granted for accessing personal information or using encryption tools when transmitting sensitive data online users can take control over their digital footprint.
How would you define the safe secure and reliable AI?
Safe and secure
To be trustworthy, AI must be protected from cybersecurity risks that might lead to physical and/or digital harm. Although safety and security are clearly important for all computer systems, they are especially crucial for AI due to AI's large and increasing role and impact on real-world activities.
For example, it states that people should not face discrimination based on the decision of an algorithm or an AI. The framework also asserts that people should know if an AI is being used to generate a decision. So, if someone is being considered for a loan, the bank they are applying to should disclose whether a human or an AI will make the final decision. And if an AI is doing it, people should be able to request to opt out of that process and instead have their application looked at by real people.
The model owners would also need to disclose any copyrighted materials that went into the model’s creation, and would also be prevented from generating illegal content. A secure cloud fabric provides secure, private multi-cloud connectivity through software-defined circuits. Anderson explained agencies aren’t getting their own private cloud, but rather access to existing commercial cloud providers.
Read more about Secure and Compliant AI for Governments here.
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.
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.