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NEC Corporation of America

1820 North Fort Myer Drive, Suite 400

Arlington, VA 22209

September 15, 2021

BY ELECTRONIC MAIL

Mr. Mark Przybocki

Division Chief, Information Access Division

U.S. National Institute of Standards and Technology, MS 20899

100 Bureau Drive

Gaithersburg, MD 20899

Re: Docket No. 210726-0151: NEC Corporation of America Comments on the National 

Institute of Standards and Technology’s Proposed AI Risk Management 

Framework

Mr. Przybocki:

NEC Corporation of America (“NEC”) is pleased to submit comments in response to the 

Request for Information (“RFI”) regarding the Artificial Intelligence Risk Management 

Framework (AI RMF) that the National Institute of Standards and Technology (NIST) is 

developing.

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 Specifically, NIST is seeking information on “how individuals, groups and 

organizations involved with designing, developing, using, or evaluating AI systems might be 

better able to address the full scope of AI risk and how a framework for managing AI risks might 

be constructed.”

As a key member of the information technology industry and a major global supplier of 

biometric technologies and other AI solutions, NEC appreciates NIST’s consensus-driven, 

transparent approach to building a flexible, adaptable, and understandable framework for 

mitigating the risks that AI technologies can pose throughout their lifecycles. NEC recognizes 

that AI technologies, which frequently provide significant benefits to individuals and societies

around the world, can sometimes perpetuate harmful biases and discrimination and pose risks to 

individual privacy and other civil and human rights. We are committed to building digital trust 

by producing AI solutions that are reliable, secure, and supportive of human rights and social 

justice, and we support NIST’s efforts to develop its AI RMF and advance broader trustworthy 

AI. 

We respectfully submit these comments to share information pertaining to several topics 

in the RFI, including:

• How organizations currently define and manage characteristics and principles of AI 

trustworthiness; 

• The integration of AI risk management into broader enterprise risk management;

• Existing standards, frameworks, models, methodologies, tools, guidelines, best practices, 

and principles to identify, assess, prioritize, mitigate, or communicate AI risk; 

 1 See National Institute of Standards and Technology, Artificial Intelligence Risk Management 

Framework, 86 FR 40810, Docket No. 210726-0151 (rel. July 29, 2021) (“Public Notice”), .
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• How organizations take into account benefits and issues related to inclusiveness in AI; 

and 

• How to structure NIST’s AI RMF in order to help achieve the desired goals.

I. Overview of NEC and Our AI Solutions

Headquartered in Irving, Texas, NEC (https://www.necam.com/) is a subsidiary of NEC 

Corporation, a global technology firm with $28 billion in annual revenue, a presence in over 160 

countries and regions, and more than 110,000 employees worldwide. NEC Corporation has had 

a presence in the United States since 1963, and, today, our major U.S. offices span sixteen states 

and employ over 2,000 people. One of the world’s top patent-producing companies, NEC 

Corporation combines advanced technologies, services, knowledge, and its 120 years of 

operating experience to help promote safety, security, fairness, and efficiency and build a more 

sustainable world in which all people have the opportunity to reach their full potential. 

NEC delivers one of the industry’s strongest and most innovative portfolios of 

biometrics, security, analytics, and information and communications technology (ICT) solutions 

for enhanced customer experience, safety, and productivity. NEC National Security Systems 

(NSS) launched in 2020 as a wholly owned subsidiary of NEC Corporation of America and will 

operate under an anticipated Special Security Agreement (SSA) with the U.S. Government as a 

FOCI-mitigated entity. NEC NSS provides U.S. Government customers with access control, 

identity verification, scene processing, advanced analytics, fiber optic sensing, border control, 

and transportation security solutions. Throughout the United States and around the world, NEC

also implements, deploys, and supports large-scale information technology, communications, 

and AI solution integrations that perform mission-critical services for commercial customers, 

state and local law enforcement agencies, and other public-sector customers.

Below, we describe applications that incorporate several of our AI technologies, 

including System Invariant Analysis Technology (SIAT), RAPID Machine Learning (RapidML), 

Heterogeneous Mixture Learning (HML), and biometric technologies.

A. System Invariant Analysis Technology

Early failure detection is challenging with conventional threshold monitoring, but SIAT

helps prevent system failures, improve system availability, and reduce maintenance costs. SIAT 

is an analytics engine that gathers and analyzes sensor data from buildings, factories, power 

plants, bridges, tunnels, and other infrastructure and machine environments. Leveraging the 

power of white-box AI, NEC’s SIAT solutions facilitate predictive maintenance by monitoring 

invariant relationships among sensors and detecting anomalies that could signal an impending 

malfunction. Monitoring performance of individual machines can also help engineers model 

broader system operations, which can make planning overall machine operations more efficient 

and effective.

Among our most notable SIAT deployments is NASA’s use of SIAT in the Orion 

spacecraft building and testing processes. During the Orion capsule thermal vacuum testing, 

SIAT helped process data from nearly 150,000 spacecraft sensors and produce an exhaustive, 

holistic, analytical model that incorporated over 22 billion data relationships and helped model 

nominal operations and detect irregularities.
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In the future, NEC aims to expand the use of SIAT from servers to edge and embedded 

computing platforms. We are also working to incorporate SIAT into post-flight aircraft 

inspections, satellite ground stations, and reusable rocket systems.

B. RAPID Machine Learning

NEC’s RapidML is a high-speed deep learning technology that enables high-precision 

image classification and matching by automatically extracting data features, such as images, text, 

and numbers, and analyzing those features in a manner that reduces manual analysis 

requirements. RapidML can help facilitate faster and more accurate manufacturing defect 

inspection by recognizing a wider variety of defects than conventional machine vision 

techniques. Because RapidML can detect defects on diverse surfaces, it is highly adaptive and 

useful in a range of manufacturing industries.

C. Heterogeneous Mixture Learning

NEC’s HML learns multiple relationships in big data, automatically discovers useful 

patterns and regularities, and makes predictions by selecting the appropriate pattern for the 

situation. Compared to other machine learning technologies that often take just a single pattern 

into account, HML’s use of multiple patterns enables higher-precision predictions in dynamically 

changing environments. Moreover, our white-box AI approach helps make these predictions 

explainable. By making more precise, explainable predictions, HML technologies can help 

improve demand forecasting, thereby improving production and distribution efficiency and 

reducing shortages and waste.

D. Biometric Technologies

NEC’s biometric technologies help identify individuals and/or analyze individuals’

characteristics based on their physical attributes, such as their faces, irises, fingerprints, palm 

prints, voices, gaits, or body temperatures. We have invested significant resources in research 

and development, and our state-of-the-art AI/ML technology has helped us provide a variety of 

customers with biometric algorithms that are among the world’s fastest and most accurate across 

demographic groups and other challenging use cases. We began our biometrics business as a 

leading provider of Automated Fingerprint Identification Systems (AFIS) to state and local law 

enforcement agencies, and we built on our law enforcement expertise to become a trusted 

biometric technology provider to the U.S. federal government. We also provide commercial 

customers in the aviation, health care, entertainment, financial services, and hospitality industries 

with a variety of unimodal and multimodal biometric solutions.

II. NEC Practices to Promote Responsible, Trustworthy AI

A. NEC’s Corporate Structure Helps Mitigate AI Risks and Maximize AI Benefits.

NEC Corporation works to incorporate Environmental, Social, and Governance (ESG) 

initiatives into our worldwide corporate practices. Specifically, NEC Corporation works to build 

safer cities and promote innovation throughout the value chain by taking actions to address 

climate change, strengthen privacy policies and implement other measures aligned with societal 

expectations, heighten security to maximize ICT possibilities, and develop sustainably and 

socially literate human resources. 
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NEC Corporation’s Digital Trust Business Strategy Division (DTBSD) works with the 

Corporate Communication and Sustainability Promotion Divisions on several of these ESG 

initiatives and leads ongoing efforts to formulate and implement a strategy for promoting human 

rights in our biometrics and broader AI business. Throughout the course of developing and 

implementing the global human rights promotion strategy, DTBSD consults diverse experts 

about human rights issues relevant to our business and to the communities in which we operate. 

Furthermore, to improve and manage company-wide privacy and human rights policies and 

programs, DTBSD collaborates with other internal teams worldwide, including the People and 

Organization Development Division, global quality management and cybersecurity teams, and 

regional subsidiary teams that are working to build digital trust in their local markets.

In the United States, NEC takes a three-pillared approach to building digital trust by 

promoting (1) reliability, (2) ethics and human rights, and (3) security in our business 

practices, services, and technologies. The NEC Digital Trust Working Group strives to 

coordinate with the Diversity, Equity & Inclusion Steering Committee, Creating Social Value 

Task Force, and the NEC Foundation to align objectives and effectively leverage resources to 

strengthen all of our U.S. ESG initiatives. 

B. NEC Promotes AI Reliability with Quality and Safety Management and Third-Party

Testing.

Our approach to AI reliability is integrated into our broader safety and quality 

management initiatives that help promote reliability throughout NEC’s supply chain and in 

product design, development, and deployment. NEC Corporation works with NEC and other 

subsidiaries to hold semi-annual quality promotion meetings and implement the “Quality and 

Safety Action Policy.” These efforts aim to help prevent product defects, facilitate compliance 

with worldwide quality and safety laws and regulations (including consumer protection laws in 

Japan, Britain, and Canada), encourage internal teams to share expertise, and standardize 

practices and key technology components. The “NEC Group Procurement Policy” underscores 

NEC’s commitment to procuring quality goods and services under fair business terms.

Additionally, NEC Corporation has been working to create Environment and Total Quality 

Management Divisions in each business unit and consolidated subsidiary and to have each 

business unit and subsidiary appoint a Quality and Safety Management Officer. 

To address quality management issues specific to AI technologies, NEC Corporation 

developed “Guidelines to Quality Assurances for Machine-Learning-Based AI.” These 

guidelines aim to go beyond traditional software quality assurance guidelines and help data 

analysts across NEC Corporation companies better understand the processes behind machine

learning and other forms of AI analysis.

Furthermore, NEC seeks out opportunities to submit our AI solutions to independent, 

third-party testing to help validate and improve their performance. For example, to obtain 

independent evaluations of our biometric algorithms’ accuracy overall and across demographic 

groups and other challenging use cases, NEC has been participating in NIST vendor tests for 

over a decade. NEC also participates in U.S. Department of Homeland Security (DHS) Science 

and Technology Directorate (S&T) Biometric Technology Rally testing. We are proud to have

consistently ranked among the top providers of fingerprint, iris recognition, and face recognition 

algorithms.
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In addition to this recognition from NIST and DHS S&T, NEC Corporation is proud to 

have received several other global awards producing innovative, high-quality, and highperforming AI technologies. In recognition of NEC’s pivot toward biometric solutions beyond 

traditional biometric markets and NEC’s dedication to creating new customer cases and 

enhancing customer solutions, NEC received the 2020 Global Biometrics in Security Market 

Growth Innovation & Leadership Excellence Frost RadarTM Award from Frost & Sullivan. 

Additionally, NEC’s “Smart Airport” technology won the Service Design iF DESIGN AWARD, 

and our “Walking Analysis Technology” won the Healthcare iF DESIGN AWARD. From 2011 

to 2020, NEC received the Top 100 Global Innovator Award from Clarivate Analytics for

Hardware & Electronics. In 2019, Frost & Sullivan named NEC as the Asia Pacific Biometric 

Company of the Year.

C. NEC Promotes Ethical, Secure AI by Operationalizing our AI and Human Rights 

Principles.

In 2018, DTBSD led the effort to develop NEC Group AI and Human Rights Principles, 

which promote: (1) fairness; (2) privacy; (3) transparency; (4) responsibility to explain the 

effects, value, and impacts of AI utilization; (5) proper utilization of AI technology; (6) 

continued development and improvement of AI technologies; and (7) dialogue with multiple 

stakeholders.

We are committed to upholding our AI and Human Rights Principles, and we have 

already started to operationalize these Principles through our corporate governance, AI product 

risk management, customer and partner relationship management, and our internal and external 

multi-stakeholder engagements. 

1. Corporate Governance

The NEC Corporation Privacy Policy and personal information protection management 

system mandate handling personal information in accordance with the requirements in Japan’s 

Act on the Protection of Personal Information and JIS Q 15001, the Japanese industrial standard 

for safe and appropriate management of personal information in corporations’ and other 

organizations’ operations. We have also developed and implemented data breach response 

procedures to help ensure that, if a data breach does occur, we are well positioned to respond 

effectively and in a manner that minimizes harm to the individuals whose personal information 

we retain. 

NEC Corporation first earned our PrivacyMark certification in October 2005. To earn 

the PrivacyMark certification, companies must comply with JIS Q 15001 and gain third-party 

organization recognition for having systems in place to ensure appropriate protection measures 

for personal information. The PrivacyMark certification also prohibits companies from 

collecting information that could economically impact an employee, such as bank account and 

credit card information; sensitive information, such as birthplace; or highly private information, 

such as a mobile telephone number, without obtaining consent. As of March 2021, NEC 

Corporation and thirty of its affiliated companies hold the PrivacyMark Certification. 

Furthermore, throughout the AI product lifecycle, NEC prioritizes observability and 

traceability, meaning that we monitor our AI’s performance and compare actual performance to 
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intended performance. Our Artificial Intelligence Operations and Machine Learning Operations 

teams help ensure we take appropriate actions to address any biased, unreliable, or otherwise 

unintended AI predictions before we finish developing and start deploying our AI technologies.

2. AI Product Risk Management

Our approach to AI product design and development occurs in three stages: 

visualization, analysis, and prescription. The visualization stage involves digitizing information 

from the real world. During the analysis stage, we analyze and predict the background and 

future of the data we obtained through visualization. In the prescription phase, we plan and 

implement the best solutions for any issues we foresee. 

Throughout all three phases, we work to mitigate technical risks. Technical risks may 

arise due to a variety of issues, including poor quality data, data misinterpretation, ineffective 

feature engineering, insufficient modeling, and adversarial attacks. If our testing and evaluation 

demonstrates that an AI technology is producing unreliable or unfair results, we work to retrain

the technology. Often, our retraining process involves focused efforts to improve our AI 

technology’s performance on particularly challenging use cases. For example, while NEC was 

working on one of its initial face recognition technology aviation projects, we noticed that the 

face recognition technology was less accurately identifying individuals with facial hair. To 

address this problem, we retrained the algorithm using training data that specifically helped the 

algorithm learn to more accurately identify individuals with facial hair. Employing a similar 

retraining approach after testing on other challenging use cases, like demographic groups, has 

helped NEC’s algorithms achieve top performance in NIST Face Recognition Vendor Test 

(FRVT) reports that specifically focused on assessing face recognition algorithm performance 

across age groups and demographic groups based on race and sex.

Moreover, throughout the product design and development process, NEC promotes 

privacy and fairness by leveraging safeguards such as encryption, data minimization, data 

aggregation, data anonymization, and algorithm layering. In addition to producing traditional 

“black-box” AI solutions, we also work to design transparent and explainable white-box AI 

solutions. These white-box AI solutions provide greater insight into why the AI technology 

produced a certain result, which makes them especially useful in use cases for which there is 

more than one possible “right” answer. 

3. Customer and Partner Relationship Management

Before selling our highest-risk AI solutions through new partners and/or to new 

customers, we think that considering the prospective partners’ and customers’ human rights 

records and risk mitigation policies is important. We aim to sell only through trusted partners 

and to trusted customers, and we are willing to decline business opportunities that we determine 

may pose too great a risk to human rights. 

After we decide to sell an AI solution to a customer, we work with the customer (and, if 

applicable, the partner(s)) to plan and execute deployments and to train individuals operating the 

AI systems. We recommend that end users require human review of important algorithm match 

results and continuously monitor system performance, and we provide operators with ongoing 

support via a customer service helpline and field site visits. 
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We also work with our partners and customers around the world to facilitate 

multijurisdictional compliance. We also work with partners and customers to consider ethical 

issues that may arise in the context of the customers’ AI technology deployment, and our 

consideration of these ethical issues reflects perspectives gained through collaboration with 

diverse internal and external stakeholders. 

4. Multi-Stakeholder Engagement

We are actively working to strengthen human rights literacy and promote diversity, 

equity, and inclusion (DEI) throughout NEC, and particularly on our AI teams. In addition to 

providing training programs and advancing other education and information sharing initiatives, 

we recognize the importance of continuing to deepen collaboration between our DEI Steering 

Committee, our Digital Trust Working Group, and our broader product and leadership teams, so 

that we can more completely embed our commitments to DEI and social justice into our policies, 

programs, and practices for designing, developing, deploying, and evaluating our AI 

technologies.

To inform our perspectives and positions on issues at the intersection of AI and human 

rights, we also participate in dialogues with a wide array of external stakeholders, including 

policymakers, civil society organizations/NGOs, think tanks, industry groups, end user groups, 

and academic researchers around the world. In the United States and internationally, we actively 

engage with national and international organizations that work on developing standards and 

ethical guidelines for AI technologies, including the Biometrics Institute, Security Industry 

Association, International Biometrics + Identity Association, U.S. Chamber of Commerce,

Future of Privacy Forum, World Economic Forum, United Nations, and standards bodies like 

NIST. We also welcome opportunities to serve as a resource to policymakers and other 

stakeholders who are interested in learning more about how our AI technologies work and in 

developing approaches to mitigating AI risks while realizing AI benefits.

III. Characteristics of Effective AI Governance and Risk Management Frameworks

We believe that governance frameworks for AI technologies should reflect input from 

diverse stakeholders and should be use-case-specific, risk-based, and supportive of privacy and 

other civil rights and civil liberties, racial and broader social justice, safety, security, economic 

efficiency, and technological innovation. 

Some of the most effective AI governance frameworks that we have seen proposed and 

adopted require appropriate and feasible notice and consent to data collection and the use of AI 

technologies; strong cybersecurity protections; limitations on data handling, storage, retention,

and transfer; independent, third-party testing before and after deploying the AI systems; operator 

training; public reporting and oversight to the degree appropriate for various use cases; 

meaningful human review of high-stakes algorithm outputs; prohibitions on discrimination in 

decision-making based on AI outputs; and use limitations to ensure existing constitutional 

protections appropriately demarcate uses of AI technologies in the United States.

Although several groups have already developed principles, guidelines, best practice 

recommendations, legislative proposals, and other types of governance frameworks to help 
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mitigate AI risks and realize AI benefits, NEC would appreciate additional input from NIST. 

Guidance regarding the technical dimensions of AI risk management during each stage of the AI 

lifecycle would be particularly helpful.

As NIST continues advancing its important AI RMF initiative and related trustworthy AI 

efforts, NEC welcomes future opportunities to support NIST’s work and provide any further 

input and assistance that would be helpful. 

Sincerely,

Shin Takahashi

Chairman and Head of Government Relations