Local Government Generative AI Policy Tips

Integrated audit modules and a Trust Portal make auditing, sharing with stakeholders and proving compliance easy. Managing controls and policies is inefficient due to rapid regulatory changes, the labor-intensive process of developing and implementing high-quality controls, and the lack of a unified system. This disorganization results in redundant efforts, poor adherence, compliance gaps, and difficult audits, primarily when outdated controls go unchecked. By utilizing 6clicks’ report generator, you can automate the creation of audit and assessment reports, saving significant time and reducing manual effort. Define audit report templates, everything from layout to style, integrate data sources and automate data retrieval, streamlining the entire audit report creation process and ensuring best practice and repeatability every time.

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. There’s a dire need to spread awareness and develop AI expertise among government workers. In June 2022, Bloomberg reported that AI expenditures of various governments like the US, UK, China, and Canada are increasing. Similarly, in March 2021, the Canadian government pledged over half a billion dollars to advance its AI initiatives.

Risk #2: Bias and Discrimination

Due to the overwhelming success of machine learning algorithms compared to other methods, many artificial intelligence systems today are based entirely on machine learning. As a result, the attacks and vulnerabilities described in this report affect both artificial intelligence and machine learning systems. The first component of this education should focus on informing stakeholders about the existence of AI attacks. This will enable potential users to make an informed risk/reward tradeoff regarding their level of AI adoption.

Learn about AI security and the rigorous measures Moveworks takes to ensure safe and responsible AI usage while also protecting enterprise IT ecosystems. The potential of conversational AI to transform operations, services, and society is astounding — but only if we dare to harness it. Overcoming these barriers requires an iterative, user-focused approach — piloting conversational AI where it shows the most promise first, then expanding use cases carefully as capabilities advance. But used properly, conversational AI can augment public services in many impactful ways.

Learn how the AWS Intelligence Initiative is providing new career paths for engineers

Although the reason for the dispute has not been made public, Reuters claims that it was triggered by staff writing to the board, warning that a new AI system being developed within the company could trigger a threat to humanity. Initiated by the World Economic Forum’s Unlocking Public Sector AI project, the guidelines were produced with insights from the World Economic Forum Centre for the Fourth Industrial Revolution and other government bodies and industry and academic stakeholders. Together, these challenges underline why regulating the development of frontier AI, although difficult, is urgently needed. In a recent survey of over 2,700 researchers who have published at top AI conferences, the median researcher placed a 50 percent chance that human-level machine intelligence—where unaided machines outperform humans on all tasks—will be achieved by 2047. “Recent state of the art AI models are too powerful, and too significant, to let them develop without democratic oversight,” said Yoshua Bengio, one of the three people known as the godfather of AI.

While this data can be incredibly valuable for making informed decisions and protecting national security, it also presents significant challenges in terms of management and protection against cyberattacks. The Secretary shall undertake this work using existing solutions where possible, and shall develop these tools and AI testbeds to be capable of assessing near-term extrapolations of AI systems’ capabilities. At a minimum, the Secretary shall develop tools to evaluate AI capabilities to generate outputs that may represent nuclear, nonproliferation, biological, chemical, critical infrastructure, and energy-security threats or hazards.

Public-Private Cooperation: The Solution?

Additionally, the EO addresses the importance of ensuring fair competition in AI markets. Agency heads are tasked with utilizing their authority to promote competition and prevent anti-competitive practices. The move reflects the initiations on the AI front as taken by other global leaders, such as China and the European Union, as they set out guidelines on regulating Artificial Intelligence. Provide end-to-end visibility by connecting leading Agile and DevOps solutions across the Agency’s development and software delivery disciplines. 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.

• This section acknowledges that one of the risks of AI development is the further deterioration of the privacy of individuals around their data.
• Further, developers can’t simply bolt on safety features after the fact; the model’s potential for harm must be considered at the development stage.
• Moreover, the authorities say they will use the software to identify undeclared patios, gazebos, and home extensions.
• Further, unlike many other cyberattacks in which a large-scale theft of information or system shutdown makes detection evident, attacks on content filters will not set off any alarms.
• 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.
• However, both governments and individuals alike need to remain vigilant and flexible as new threats emerge in this rapidly evolving landscape of governance powered by AI.

A secure cloud fabric can also help government agencies to optimize their data management practices by enabling them to easily move data between different cloud environments, regardless of whether they are hosted on public or private clouds. This can help agencies to take advantage of the unique capabilities of different cloud providers, while still maintaining a unified view of their data. With these capabilities, they are able to create massive data lakes and ingest data sources from many different sources. 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.

Conversational AI use cases for security and compliance

The guidelines include contributions from OpenAI, the company which last week temporarily sacked its CEO over alleged security concerns. Here, the AI applications currently being used by the Dutch government are listed, with 109 registries currently. Applications can be filtered by government branch, and the database provides detail on the type of algorithm being used, whether it is currently actively used, and the policy area it is used for. Information about monitoring, human intervention, risks, and performance standards are also provided, increasing transparency of AI usage by the Dutch government. Citing guidance from the Government Digital Service (GDS) and Office for Artificial Intelligence (OAI), the publication provides four resources on assessing, planning, and managing AI in the public sector.

Further, given the success of learning, which often captures patterns and relations that could not be designed manually by human model designers, many if not most systems will rely heavily on learned features, and be vulnerable to attacks. While these security steps will be a necessary component of defending against AI attacks, they do not come without cost. From a societal standpoint, one point of contention is that some of these security precautions will require a trade-off against other important considerations, such as ensuring that AI systems are fair, unbiased, and trustworthy.

This makes it difficult to scale content production while maintaining high standards in clear communication.Implementing generative AI helps teams address these challenges. By automating parts of your content creation process, you can streamline workflows, reduce manual effort, and accelerate content production.This leads to time and cost saving, increased productivity, and enhanced engagement. The guidelines also warn against choosing more complex models that might be more difficult to secure. “There may be benefits https://www.metadialog.com/governments/ to using simpler, more transparent models over large and complex ones which are more difficult to interpret,” the document states. Although they don’t place any new mandatory requirements on the developers of AI systems, they set out a broad range of principles that companies should follow. The views expressed at, or through, this site are those of the individual authors writing in their individual capacities only – not those of their respective employers, Holistic AI, or committee/task force as a whole.

Despite the popular warnings of sentient robots and superhuman artificial intelligence that grow more difficult to avoid with each passing day, artificial intelligence as it is today possesses no knowledge, no thought, and no intelligence. In the future, technical advancements may one day help us to better understand how machines can learn, and even learn how to embed these important qualities in technology. Once AI Security Compliance programs are implemented, regulators should decide in what ways entities will be held responsible for meeting compliance requirements, and clearly communicate these principles with their constituents. Informed AI users in critical areas should be held responsible for acting in good faith and taking appropriate measure to protect against AI attacks. Stakeholders must determine how AI attacks are likely to be used against their AI system, and then craft response plans for mitigating their effect. In determining what attacks are most likely, stakeholders should look to existing threats and see how AI attacks can be used by adversaries to accomplish a similar goal.

Entities may wish to conduct “red teaming” exercises and consultations with law enforcement, academics, and think tanks in order to understand what damage may be incurred from a successful attack against an AI system. In traditional cyber weaponization, a tension exists between 1) notifying the system operator to allow for patching, and 2) keeping the vulnerability a secret in order to exploit it. This tension is based on the fact that if one party discovers a vulnerability, it is likely that another, possibly hostile, party will do so as well.

(x)  The term “Open RAN” means the Open Radio Access Network approach to telecommunications-network standardization adopted by the O-RAN Alliance, Third Generation Partnership Project, or any similar set of published open standards for multi-vendor network equipment interoperability. (o)  The terms “foreign reseller” and “foreign reseller of United States Infrastructure as a Service Products” mean a foreign person who has established an Infrastructure as a Service Account to provide Infrastructure as a Service Products subsequently, in whole or in part, to a third party. (n)  The term “foreign person” has the meaning set forth in section 5(c) of Executive Order of January 19, 2021 (Taking Additional Steps To Address the National Emergency With Respect to Significant Malicious Cyber-Enabled Activities).

Besides, a more severe repercussion of data breaches is the loss of public trust in the government’s ability to protect their privacy. The feeling that their data is not secure may make citizens hesitate to make use of government services or provide required information for public programs. International cooperation also contributes to resolving global challenges that are related to data privacy and security in the context of an AI-driven government. Countries need to collaborate to ensure common standards and best practices that protect citizens’ data across different user spaces.

The president calls on Congress to better protect Americans’ privacy, including from the risks posed by generative AI, and to pass bipartisan data privacy legislation to protect all Americans, with a special focus on kids. Congress also prioritizes federal agencies’ support for accelerating the development and use of privacy-preserving research. The executive orders (EO) are official documents, numbered consecutively, through which the President of the US manages the operations of the Federal Government. An executive order is a signed, written, and published directive from the President of the US to the Federal Government.

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. Artificial intelligence companies and governments should allocate at least one third of their AI research and development funding to ensuring the safety and ethical use of the systems, top AI researchers said in a paper on Tuesday. And artificial intelligence today presents seismic unknowns that we would be wise to ponder. Artificial intelligence, like Frankenstein’s monster, may appear human, but is decidedly not.

The outcome of these reviews should be written policies governing how any data used in building an AI system is collected and shared. Second, the proliferation of powerful yet cheap computing hardware means almost everyone has the power to run these algorithms on their laptops or gaming computers. While this is expected in military contexts opposite an adversary with modern technical capabilities, it does have significant bearing on the ability for non-state actors and rogue individuals to execute AI attacks. In conjunction with apps that could be made to allow for the automation of AI attack crafting, the availability of cheap computing hardware removes the last barrier from successful and easy execution of these AI attacks. An Uber self-driving car struck and killed a pedestrian in Tempe, Arizona when the on-board AI system failed to detect a human in the road.52 While it is unclear if the particular pattern of this pedestrian is what caused the failure, the failure manifested itself in the exact same manner in which an AI attack on the system would. This real-world example is a terrifying harbinger of the ability for adversaries who are deliberately trying to find attack patterns to find success.