Bias Against 93 Stigmatized Groups in Masked Language Models and Downstream Sentiment Classification Tasks
Year: 2023
Type: conference-paper
Abstract: Warning: The content of this paper may be upsetting or triggering.
Authors: Katelyn Mei, Sonia Fereidooni, Aylin Caliskan
Institution: University of Washington
Language: English
Subfield: Safety Research
Field: Social Sciences
Domain: Social Sciences
SDG: Reduced inequalities
Open Access status: hybrid
Awards: EXPLOITING ALTERNATE COMPUTING TECHNOLOGIES II
THEISS RESEARCH
PURPOSE: THIS PROPOSAL SEEKS TO MAKE ADVANCES IN TWO SEPARATE AREAS OF EMERGING COMPUTING TECHNOLOGY: QUANTUM INFORMATION SCIENCE AND NEUROMORPHIC COMPUTING. FOR THE FORMER, WORK WILL FOCUS ON THE DEVELOPMENT AND ASSESSMENT OF QUANTUM COMMUNICATION SYSTEMS AND APPLICATIONS. FOR THE LATTER, THE GOAL IS TO IDENTIFY PROMISING APPLICATIONS AND DEVELOP TRAINING METHODS FOR SPIKING NEURAL NETWORKS, AN ALTERNATIVE COMPUTATIONAL SYSTEM LOOSELY INSPIRED BY OUR UNDERSTANDING OF HOW THE HUMAN BRAIN WORKS
ACTIVITIES TO BE PERFORMED: COLLABORATION WITH THE EUROPEAN TELECOMMUNICATIONS STANDARDS INSTITUTE WILL BE UNDERTAKEN TO HELP CLARIFY THE VITAL LINKAGE BETWEEN SECURITY PROOFS FOR IDEALIZED QUANTUM CRYPTOGRAPHIC KEY DISTRIBUTION (QKD) SYSTEMS AND THE CHALLENGES OF REAL SYSTEMS BUILD FROM IMPERFECT COMPONENTS. THE PI WILL ALSO APPLY HIS VAST EXPERIENCE IN DEVELOPING QKD HARDWARE TO THE DEVELOPMENT OF AN EXPERIMENTAL QUANTUM NETWORK IN COLLABORATION WITH NIST SCIENTISTS. FINALLY, IMPROVED METHODS TO TRAIN ARTIFICIAL NEURAL NETWORKS (NN) WILL BE STUDIED, AND THE IMPLEMENTATION OF NN APPLICATIONS AND BENCHMARKS THAT MAP WELL TO SCALABLE, LOW ENERGY NN PLATFORMS SUCH AS THE SUPERCONDUCTING OPTOELECTRONICS NETWORK (SOEN) UNDER STUDY AT NIST WILL BE DEVELOPED.
EXPECTED OUTCOMES: THE FUNDAMENTAL RESEARCH SUPPORTED BY THIS GRANT WILL CONTRIBUTE TO THE BODY OF KNOWLEDGE NEEDED FOR THE DEVELOPMENT OF PRACTICAL AND RELIABLE SYSTEMS AND APPLICATIONS OF QUANTUM NETWORKS AND SPIKING NEURAL NETWORKS. THE RESULTS OF THIS WORK WILL BE PUBLISHED IN THE OPEN SCIENTIFIC LITERATURE.
INTENDED BENEFICIARIES: THE WORK PROPOSED HERE WILL PROVIDE THE NIST WITH A DEEPER UNDERSTANDING OF THE STATE-OF-THE-ART IN POTENTIAL NEW COMPUTING TECHNOLOGIES, ALLOWING IT TO ANTICIPATE NEEDED MEASUREMENT TECHNIQUES AND TOOLS TO ENABLE DOWNSTREAM COMMERCIALIZATION. WHEN FULLY REALIZED, QUANTUM NETWORKS COULD PROVIDE NEW MEANS OF SECURE INFORMATION EXCHANGE, A WAY TO SCALE CURRENT TODAY?S SMALL QUANTUM COMPONENTS INTO A LARGE, DISTRIBUTED COMPUTING SYSTEM, AS WELL AS TO DEVELOP NEW HIGHLY SENSITIVE SENSING CAPABILITIES. NEUROMORPHIC DEVICES, SUCH AS THE ARTIFICIAL NEURAL NETWORKS TO BE STUDIED HERE, COULD PROVIDE VERY HIGH-SPEED PROCESSING FOR CERTAIN APPLICATIONS WITH VERY LOW POWER REQUIREMENTS, WHICH IS A LIMITING FACTOR IN SCALING UP CONVENTIONAL COMPUTING DEVICES.
SUBRECIPIENT ACTIVITIES: THERE ARE NO PLANNED SUBAWARDS., G5525990829
OpenAlex ID: W4380319657