Oregon Establishes State Government AI Advisory Council Privacy Compliance & Data Security
At Securiti, our mission is to enable enterprises to safely harness the incredible power of data and the cloud by controlling the complex security, privacy and compliance risks. Additionally, the EO emphasizes prioritizing resources for AI-related education and workforce development through existing programs and collaboration with agencies to build a diverse AI-ready workforce. Government organizations can either choose to lag behind as the world races towards an AI-powered future, or boldly lead the charge. These examples demonstrate conversational AI’s immense potential to help agencies cut costs, strengthen operations, and further their mission results for the public good. With strategic adoption, more responsive, effective, and innovative government is within reach. These documents are a concrete example of different tools used by government entities to help determine both eligibility for public benefits and to inform enforcement resources.
If it does, it will affect all entities working with AI within the European Union, not just their government agencies. The proposed regulations were put forward as part of the Artificial Intelligence Act, which was first introduced in April 2021. Government regulations that accelerate adoption of open source AI promises numerous benefits, including greater transparency, trust, and public oversight of algorithms. But challenges remain around privacy, security and sustainable maintenance of open source AI projects. Regulation is essential for managing the complex ethical and safety challenges of AI, yet it’s equally critical to promote a regulatory environment that spurs innovation and upholds the democratic nature of AI development. The executive order’s ambition is commendable and generally well-directed, but it still falls short in ways that may benefit incumbents disproportionately.
USAID warned employees not to share private data on ChatGPT, memo shows
Researchers have shown that attacks crafted using these “copy models” are easily transferable to the originally targeted models.23 As was the case with models, there are a number of common scenarios in which the attacker would have access to the dataset. Like models themselves, datasets are made widely available https://www.metadialog.com/governments/ as part of the open source movement, or could similarly be obtained by hacking the system storing this dataset. In an even more restrictive setting where the dataset is not available, attackers could compile their own similar dataset, and use this similar dataset to build a “copy model” instead.
9 Eykholt, Kevin, et al. “Robust physical-world attacks on deep learning visual classification.” Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 7 Eykholt, Kevin, et al. “Robust physical-world attacks on deep learning visual classification.” Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 1 Eykholt, Kevin, et al. “Robust physical-world attacks on deep learning visual classification.” Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. The world has learned a number of painful lessons from the unencumbered and reckless enthusiasm with which technologies with serious vulnerabilities have been deployed. Social networks have been named as an aide to genocide in Myanmar and the instrument of democratic disruption in the world’s foremost democracy.
Security
The TRiSM tools do that by exposing the datasets used to train the AI models to look for bias, monitoring AI responses to ensure that they are compliant with existing regulations or guidelines, or they can help to train the AI to act appropriately. Organizations can harness the power of AI to help keep data secure and bring systems into compliance with government and industry standards. Any industry that involves labor-intensive documentation like healthcare, insurance, finance, and legal is a suitable candidate for artificial intelligence. Without AI systems, human beings are in charge of these transactions, which means the process takes a long time and is susceptible to human error. It increases security by decreasing the chance of humans leaking confidential information thereby increasing compliance by ensuring high standards of privacy and quality.
The technology giant’s network is one of the largest in the world and made up of more than 250,000 km of lit fiber optic and undersea cable systems. New AI guidelines authored by CISA and the UK’s NCSC stress the importance of secure design, development, deployment, and… But although it will lead to massive opportunities, this technology is an area that needs clear and significant regulation. The executive order from the Biden administration is the first meaningful step, although one that is very much a work in progress. As AI continues to make headlines, Microsoft is introducing more AI services for commercial and government clouds. Organizations can expect the same things coming out to the commercial space to eventually make their way into government.
But the technology also poses new challenges and risks for government agencies and the public at large. This paper highlights the ways in which state and local government can take advantage of generative AI while using it responsibly. (No) thanks to marketing departments, the term’s been used for lots of things — from the cutting-edge generative models like GPT-4, to the simplest machine-learning systems, including some that have been around for decades. All of those familiar technologies are based on machine learning (ML) algorithms, aka “AI”. Plus, the emerging group of AI TRiSM — standing for trust, risk and security management — tools are just now being deployed, and could be used to help companies self-regulate AIs.
Why do we need AI governance?
The rationale behind responsible AI governance is to ensure that automated systems including machine learning (ML) / deep learning (DL) technologies, are supporting individuals and organizations in achieving their long terms objectives, whist safeguarding the interests of all stakeholders.
What is the Defense Production Act AI?
AI Acquisition and Invocation of the Defense Production Act
14110 invokes the Defense Production Act (DPA), which gives the President sweeping authorities to compel or incentivize industry in the interest of national security.
Where is AI used in defence?
One of the most notable ways militaries are utilising AI is the development of autonomous weapons and vehicle systems. AI-powered crewless aerial vehicles (UAVs), ground vehicles and submarines are employed for reconnaissance, surveillance and combat operations and will take on a growing role in the future.