The spread of artificial intelligence across business, defense, and security sectors has the pote... more The spread of artificial intelligence across business, defense, and security sectors has the potential to improve the speed of operations, provide new capabilities, and increase efficiencies. Along with the integration of AI comes an upsurge in risk and potential harm from AI accidents, misuse, and unexpected behavior. The growing concern about AI having unforeseen negative impacts on U.S. commercial, social, infrastructure, and national security highlights the need for AI assessment that can help reduce potential harm from AI and ensure that AI applications and technologies are safe and trustworthy. The Center for Security and Emerging Technology has published studies related to AI safety, accidents, and testing. Building on this work, CSET has launched a new line of research titled "AI Assessment" to investigate the development and adequacy of current AI assessment approaches, along with the availability and sufficiency of tools and resources for implementing them. Specifically, the research will: 1. Understand and contribute to the development and adoption of AI standards, testing procedures, best practices, regulation, auditing, and certification. 2. Characterize the wide variety of AI products, tools, services, data, and resources that influence AI assessment. 3. Understand the needs for additional infrastructure, academic research, tools, or budgetary resources to support demonstration and adoption. 4. Explore the global differences and similarities of AI assessment, standards, and testing practices among various sectors and government entities. There is no simple one-size-fits-all assessment approach that can be adequately applied to the diverse range of AI. AI systems have a wide variety of functionalities, capabilities, and outputs. They are also created using different tools, data types, and resources, adding to assessment diversity. A collection of approaches and processes are needed to cover a wide range of AI products, tools, services, and resources. Additionally, because the number and frequency of AI creation will greatly increase, resources need to include techniques and tools for scaling assessment, handling the variety and quantity of AI systems. With new AI innovations, assessment needs may change. This research will provide a foundation for assessment that can be adapted to future needs. It will also provide a better understanding of the current U.S. needs and capabilities for AI assessment, and support decisions on AI policy, resourcing, research, and national security.
The vibrational and magnetic properties of mechanically attrited nanocrystalline Ni3Fe powders we... more The vibrational and magnetic properties of mechanically attrited nanocrystalline Ni3Fe powders were studied. The as-milled Ni3Fe powders were annealed to create nanocrystalline samples with different grain sizes, RMS strains, and grain boundary atomic structures. The average grain size and RMS strain of the samples were measured using x-ray diffractometry and transmission electron microscopy. From inelastic neutron scattering experiments, the phonon density of states (DOS) of various as-milled and annealed Ni3Fe nanocrystalline powders were determined. At low energies (<15 meV), nanocrystalline samples compared to bulk Ni3Fe showed an enhancement in the phonon DOS that was proportional to the density of grain boundaries in the powders. A broadening of features in the phonon DOS was also observed for the smallest nanocrystals. The room temperature phonon DOS of nanocrystals with an average grain size of 6 nm and a large grain boundary volume fraction of 20%, was different from the...
Reflection electron energy loss spectroscopy at high electron energies is an analytic technique w... more Reflection electron energy loss spectroscopy at high electron energies is an analytic technique well-suited to compositional analysis at the monolayer level during molecular beam epitaxial growth. For submonolayer-thickness Ge films grown on (2 × 1)-reconstructed Si (001) ...
Epitaxial thin films of TiO2 and VO2 single layers and TiO2/VO2 multilayers were grown on (112̄0)... more Epitaxial thin films of TiO2 and VO2 single layers and TiO2/VO2 multilayers were grown on (112̄0) sapphire (α-Al2O3) substrates using the metalorganic chemical vapor deposition technique and were characterized using Raman scattering and four-circle x-ray diffractometry. X-ray diffraction results indicate that the films are high quality single crystal material with well defined growth plane and small in-plane and out-of-plane mosaic. Single-layer films are shown to obey the Raman selection rules of TiO2 and VO2 single crystals. The close adherence to the Raman selection rules indicates the high degree of orientation of the films, both parallel and perpendicular to the growth plane. Selection rule spectra of two and three layer TiO2/VO2 multilayers are dominated by the VO2 layers with only minimal signature of the TiO2 layers. Due to the low band gap of semiconducting vanadium dioxide, we attribute the strong signature of the VO2 layers to resonant enhancement of the VO2 Raman compone...
Real-world harms caused by the use of AI technologies are widespread. Tracking and analyzing them... more Real-world harms caused by the use of AI technologies are widespread. Tracking and analyzing them improves our understanding of the variety of harms and the circumstances that lead to their occurrence once AI systems are deployed. This report presents a standardized conceptual framework for defining, tracking, classifying, and understanding harms caused by AI. It lays out the key elements required for the identification of AI harm, their basic relational structure, and definitions without imposing a single interpretation of AI harm. The brief concludes with an example of how to apply and customize the framework while keeping its modular structure.
The spread of artificial intelligence across business, defense, and security sectors has the pote... more The spread of artificial intelligence across business, defense, and security sectors has the potential to improve the speed of operations, provide new capabilities, and increase efficiencies. Along with the integration of AI comes an upsurge in risk and potential harm from AI accidents, misuse, and unexpected behavior. The growing concern about AI having unforeseen negative impacts on U.S. commercial, social, infrastructure, and national security highlights the need for AI assessment that can help reduce potential harm from AI and ensure that AI applications and technologies are safe and trustworthy. The Center for Security and Emerging Technology has published studies related to AI safety, accidents, and testing. Building on this work, CSET has launched a new line of research titled "AI Assessment" to investigate the development and adequacy of current AI assessment approaches, along with the availability and sufficiency of tools and resources for implementing them. Specifically, the research will: 1. Understand and contribute to the development and adoption of AI standards, testing procedures, best practices, regulation, auditing, and certification. 2. Characterize the wide variety of AI products, tools, services, data, and resources that influence AI assessment. 3. Understand the needs for additional infrastructure, academic research, tools, or budgetary resources to support demonstration and adoption. 4. Explore the global differences and similarities of AI assessment, standards, and testing practices among various sectors and government entities. There is no simple one-size-fits-all assessment approach that can be adequately applied to the diverse range of AI. AI systems have a wide variety of functionalities, capabilities, and outputs. They are also created using different tools, data types, and resources, adding to assessment diversity. A collection of approaches and processes are needed to cover a wide range of AI products, tools, services, and resources. Additionally, because the number and frequency of AI creation will greatly increase, resources need to include techniques and tools for scaling assessment, handling the variety and quantity of AI systems. With new AI innovations, assessment needs may change. This research will provide a foundation for assessment that can be adapted to future needs. It will also provide a better understanding of the current U.S. needs and capabilities for AI assessment, and support decisions on AI policy, resourcing, research, and national security.
The vibrational and magnetic properties of mechanically attrited nanocrystalline Ni3Fe powders we... more The vibrational and magnetic properties of mechanically attrited nanocrystalline Ni3Fe powders were studied. The as-milled Ni3Fe powders were annealed to create nanocrystalline samples with different grain sizes, RMS strains, and grain boundary atomic structures. The average grain size and RMS strain of the samples were measured using x-ray diffractometry and transmission electron microscopy. From inelastic neutron scattering experiments, the phonon density of states (DOS) of various as-milled and annealed Ni3Fe nanocrystalline powders were determined. At low energies (<15 meV), nanocrystalline samples compared to bulk Ni3Fe showed an enhancement in the phonon DOS that was proportional to the density of grain boundaries in the powders. A broadening of features in the phonon DOS was also observed for the smallest nanocrystals. The room temperature phonon DOS of nanocrystals with an average grain size of 6 nm and a large grain boundary volume fraction of 20%, was different from the...
Reflection electron energy loss spectroscopy at high electron energies is an analytic technique w... more Reflection electron energy loss spectroscopy at high electron energies is an analytic technique well-suited to compositional analysis at the monolayer level during molecular beam epitaxial growth. For submonolayer-thickness Ge films grown on (2 × 1)-reconstructed Si (001) ...
Epitaxial thin films of TiO2 and VO2 single layers and TiO2/VO2 multilayers were grown on (112̄0)... more Epitaxial thin films of TiO2 and VO2 single layers and TiO2/VO2 multilayers were grown on (112̄0) sapphire (α-Al2O3) substrates using the metalorganic chemical vapor deposition technique and were characterized using Raman scattering and four-circle x-ray diffractometry. X-ray diffraction results indicate that the films are high quality single crystal material with well defined growth plane and small in-plane and out-of-plane mosaic. Single-layer films are shown to obey the Raman selection rules of TiO2 and VO2 single crystals. The close adherence to the Raman selection rules indicates the high degree of orientation of the films, both parallel and perpendicular to the growth plane. Selection rule spectra of two and three layer TiO2/VO2 multilayers are dominated by the VO2 layers with only minimal signature of the TiO2 layers. Due to the low band gap of semiconducting vanadium dioxide, we attribute the strong signature of the VO2 layers to resonant enhancement of the VO2 Raman compone...
Real-world harms caused by the use of AI technologies are widespread. Tracking and analyzing them... more Real-world harms caused by the use of AI technologies are widespread. Tracking and analyzing them improves our understanding of the variety of harms and the circumstances that lead to their occurrence once AI systems are deployed. This report presents a standardized conceptual framework for defining, tracking, classifying, and understanding harms caused by AI. It lays out the key elements required for the identification of AI harm, their basic relational structure, and definitions without imposing a single interpretation of AI harm. The brief concludes with an example of how to apply and customize the framework while keeping its modular structure.
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Papers by Heather Frase