Federal Register / Vol. 85, No. 231 / Tuesday, December 1, 2020 / Notices 77183 

1https://www.nap.edu/catalog/25021/thefrontiers-of-machine-learning-2017-raymond-andbeverly-sackler. 

2 Ian Goodfellow Yoshua Bengio Aaron Courville, 

Deep Learning (Adaptive Computation and 

Machine Learning series), (MIT Press, 2016), 1. 

requirements for the CDQ Program are at 

50 CFR 679.33. 

For most CDQ groundfish species, 

NMFS annually summarizes volume 

and value information for landings of all 

fishery species subject to cost recovery 

in order to estimate a standard price for 

each fishery species. The volume and 

value information is obtained from the 

First Wholesale Volume and Value 

Report and the Pacific Cod Ex-Vessel 

Volume and Value Report. For CDQ 

halibut and fixed-gear sablefish, NMFS 

calculates the standard prices using 

information from the Individual Fishing 

Quota (IFQ) Ex-Vessel Volume and 

Value Report, which collects 

information on both IFQ and CDQ 

volume and value. 

Using the fee percentage formula 

described above, the estimated 

percentage of direct program costs to 

fishery value for the 2020 calendar year 

is 0.84 percent for the CDQ groundfish 

and halibut programs. For 2020, NMFS 

applied the calculated CDQ fee 

percentage to all CDQ groundfish and 

halibut landings made between January 

1 and December 31 to calculate the CDQ 

fee liability for each CDQ group. The 

2020 fee payments must be submitted to 

NMFS on or before December 31, 2020. 

Payment must be made in accordance 

with the payment methods set forth in 

50 CFR 679.33(a)(3)(iv). 

(Authority: 16 U.S.C. 1801 et seq.) 

Dated: November 24, 2020. 

Jennifer M. Wallace, 

Acting Director, Office of Sustainable 

Fisheries, National Marine Fisheries Service. 

[FR Doc. 2020–26432 Filed 11–30–20; 8:45 am] 

BILLING CODE 3510–22–P 

CONSUMER PRODUCT SAFETY 

COMMISSION 

CPSC Artificial Intelligence Forum 

AGENCY: Consumer Product Safety 

Commission. 

ACTION: Announcement of forum. 

SUMMARY: Consumer Product Safety 

Commission (CPSC) staff is holding a 

forum on artificial intelligence (AI), and 

related technologies, such as Machine 

Learning (ML). CPSC staff invites 

interested parties to attend or 

participate in the AI forum via webinar. 

DATES: The AI forum will take place 

from 9 a.m. to 4 p.m., Eastern Standard 

Time (EST) on Tuesday, March 2, 2021, 

via webinar. All attendees should preregister for the webinar. Individuals 

interested in serving on panels or 

presenting information at the forum 

should register by January 15, 2020. All 

other individuals who wish to attend 

the forum should register by February 

15, 2021. 

ADDRESSES: The forum will be held via 

webinar. Attendance is free of charge. 

Persons interested in attending the 

forum should register online at: https:// 

attendee.gotowebinar.com/register/ 

4723099942466621456 and fill in the 

information. After registering, you will 

receive a confirmation email containing 

information about joining the webinar. 

Persons interested in serving on a panel 

or presenting information should email 

ntaylor@cpsc.gov an abstract by January 

4, 2021. Detailed instructions for the 

webinar participants and other 

interested parties will be made available 

on the CPSC website on the public 

calendar: https://cpsc.gov/newsroom/ 

public-calendar. 

FOR FURTHER INFORMATION CONTACT: 

Nevin Taylor, Chief Technologist, 4330 

East West Highway, Bethesda, MD 

20814; telephone: 301–509–0264; email: 

ntaylor@cpsc.gov. 

SUPPLEMENTARY INFORMATION: CPSC staff 

is hosting an AI forum to collect 

information on the voluntary consensus 

standards, certification, and product 

specification efforts associated with 

products using AI, ML, and related 

technologies. The information collected 

from the forum will assist staff in 

making recommendations for improving 

the safety of consumer products that 

include this technology. 

I. Background 

For this Forum, we are generally 

defining ‘‘Artificial intelligence’’ (AI) as 

any method for programming computers 

or products to enable them to carry out 

tasks or behaviors that would require 

intelligence if performed by humans.1

‘‘Machine learning’’ (ML) is typically 

understood to be an iterative process of 

applying models or algorithms to data 

sets to learn and detect patterns and/or 

perform tasks, such as prediction or 

decision making that can approximate 

some aspects of intelligence.2

A. Potential Uses of AI ML in Consumer 

Products To Improve Product Safety 

CPSC staff is aware of consumer 

products with claims of AI inclusion. 

Children’s toys, residential appliances, 

and recreational products are being 

marketed touting the use of AI, ML, and 

related technologies to improve product 

efficacy and consumer experience. 

Although opportunities exist for 

manufacturers to improve safety using 

new technologies, hazards may also be 

associated with the inclusion of these 

technologies. 

B. AI, ML, and Related Technologies 

AI, ML, and related technologies have 

the potential to dramatically change the 

nature of consumer products, with 

important ramifications for CPSC’s 

responsibilities to protect consumers 

from product hazards. In particular, 

products with AI or ML technologies 

would be learning from the consumer 

and from the operational environment 

for the product. Customization occurs 

through the evolution of products after 

delivery to the consumer, resulting in 

significant ramifications for 

manufacturer’s implementation of AI 

and ML that shape products and 

transform consumer experience. 

Although adapting to consumer 

preferences has the potential to make 

significant strides in product 

customization of features and safety 

enhancements, using data to predict and 

enhance product operation could result 

in safety hazards. 

C. Ramifications of AI and ML in 

Consumer Products 

Manufacturers may not fully 

understand the operation of the AIenabled products, particularly for those 

using genetic algorithms and other 

evolutionary AI techniques. Changes to 

the product after purchase may impede 

CPSC’s ability to replicate reported 

hazards, creating challenges for 

compliance investigations and product 

safety standards development. 

D. Relevant Voluntary Standards 

Voluntary standards organizations are 

developing consensus standards related 

to AI and ML technologies that will 

likely inform and improve safety-related 

characteristics in consumer products. AI 

and ML standards in the automotive, 

aerospace, and defense industries are 

ongoing, and knowledge from these 

efforts may be valuable in consumer 

product safety standards development. 

II Forum Topics 

The AI forum will discuss existing 

and proposed voluntary consensus 

standards, certifications, testing 

methods, product specifications, best 

practices, and similar guidance for AI, 

ML, and related technologies. There is 

currently considerable interest in 

exploring a variety of areas of AI and 

ML, including ethics, security, and 

privacy. However, given the CPSC 

mission, this forum is focused on 

obtaining information specific to 


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77184 Federal Register / Vol. 85, No. 231 / Tuesday, December 1, 2020 / Notices 

assisting the agency’s safety efforts with 

consumer products that use these 

technologies. CPSC staff is interested in 

discussing the best way to provide 

guidance to manufacturers and 

importers of consumer products with AI 

and ML, to test products for safety that 

address the following considerations: 

• Identification: 

Æ Determine presence of AI and ML 

in consumer products. 

D Does the product have AI and ML 

components? 

• Implications: 

Æ Differentiate what AI and ML 

functionality exists. 

D What are the AI and ML 

capabilities? 

• Impact: 

Æ Discern how AI and ML 

dependencies affect consumers. 

D Do AI and ML affect consumer 

product safety? 

• Iteration: 

Æ Distinguish when AI and ML, 

evolve and how this transformation 

changes outcomes. 

D When do products evolve/transform, 

and do the evolutions/transformations 

affect product safety? 

III. Forum Details 

A. Forum Time and Place 

CPSC staff will hold the forum from 

9 a.m. to 4 p.m., EST on Tuesday, March 

2, 2021, via webinar. 

B. Forum Registration 

If you would like to attend the AI 

Forum, but you do not wish to make a 

presentation or participate on a panel, 

please register online by February 15, 

2021. (See the ADDRESSES portion of this 

document for the website link and 

instructions to register.) 

If you would like to make a 

presentation at the AI Forum, or you 

wish to be considered as a panel 

member for a specific topic or topics, 

email an electronic version of your 

abstract to Nevin Taylor, ntaylor@

cpsc.gov, by January 4, 2021. Abstracts 

should be relevant to the forum topic 

and no longer than two pages. Staff will 

select panelists and individuals to make 

presentations at the AI forum based on 

considerations such as: The submitted 

abstract information, the individual’s 

demonstrated familiarity or expertise 

with the topic to be discussed, the 

practical utility of the information to be 

presented, and the individual’s 

viewpoint or ability to represent certain 

interests (such as large manufacturers, 

small manufacturers, consumer 

advocates, and consumers). Staff would 

like the presentations to represent and 

address a wide variety of stakeholders 

and interests. Staff will notify those who 

are selected to make a presentation or 

participate in a panel by January 15, 

2021, so that you can prepare and 

provide your final presentation by 

February 12, 2021. 

Although staff will make an effort to 

accommodate all persons who wish to 

make a presentation, the time allotted 

for presentations will depend on the 

agenda and the number of persons who 

wish to speak on a given topic. Staff 

recommends that individuals and 

organizations with common interests 

consolidate or coordinate their 

presentations, and request time for a 

joint presentation. If you have any 

questions regarding participating in the 

forum, contact Nevin Taylor, ntaylor@

cpsc.gov, 301–509–0264. 

Alberta E. Mills, 

Secretary, U.S. Consumer Product Safety 

Commission. 

[FR Doc. 2020–26441 Filed 11–30–20; 8:45 am] 

BILLING CODE 6355–01–P 

DEPARTMENT OF DEFENSE 

Office of the Secretary 

[Docket ID: DoD–2020–OS–0069] 

Submission for OMB Review; 

Comment Request 

AGENCY: National Defense University, 

Department of Defense (DoD). 

ACTION: 30-Day information collection 

notice. 

SUMMARY: The DoD has submitted to 

OMB for clearance the following 

proposal for collection of information 

under the provisions of the Paperwork 

Reduction Act. 

DATES: Consideration will be given to all 

comments received by December 31, 

2020. 

ADDRESSES: Written comments and 

recommendations for the proposed 

information collection should be sent 

within 30 days of publication of this 

notice to www.reginfo.gov/public/do/ 

PRAMain. Find this particular 

information collection by selecting 

‘‘Currently under 30-day Review—Open 

for Public Comments’’ or by using the 

search function. 

FOR FURTHER INFORMATION CONTACT: 

Angela James, 571–372–7574, or 

whs.mc-alex.esd.mbx.dd-dodinformation-collections@mail.mil. 

SUPPLEMENTARY INFORMATION: 

Title; Associated Form; and OMB 

Number: National Defense University 

(NDU) Student Profile; OMB Control 

Number 0704–XXXX. 

Type of Request: Existing collection in 

use without an OMB Control Number. 

Number of Respondents: 2,525. 

Responses per Respondent: 1. 

Annual Responses: 2525. 

Average Burden per Response: 20 

minutes. 

Annual Burden Hours: 841.7 hours. 

Needs and Uses: This information 

collection is required to complete the 

official student record, which is stored 

in the University Student Management 

System (USMS), a component of the 

NDU Enterprise Information System. 

Through this information collection, 

students provide profile information 

such as demographics, educational 

background, military service or 

professional background, and 

emergency contact information. The 

information is critical to university 

operations as it is used to fulfill 

mandatory reporting requirements and 

ensure the safety of students. The 

information is collected from students 

electronically, via a web-based form that 

contains a combination of selectedresponse (radio buttons, drop-down 

menus) and open-response items. The 

National Defense University Student 

Profile (NSP) is completed by all 

students, and is administered using a 

Drupal-based survey platform provided 

by USA Learning. The data are 

downloaded, processed, and transferred 

to the USMS by NDU’s Office of 

Institutional Research. The end result is 

a set of complete student records for 

each academic year in the official 

repository for such record. The data are 

used for various institutional purposes 

such as mandatory reporting and 

notifying students of emergencies or 

closures. 

Affected Public: Individuals or 

Households. 

Frequency: Annually. 

Respondent’s Obligation: Voluntary. 

OMB Desk Officer: Ms. Jasmeet 

Seehra. 

You may also submit comments and 

recommendations, identified by Docket 

ID number and title, by the following 

method: 

• Federal eRulemaking Portal: http:// 

www.regulations.gov. Follow the 

instructions for submitting comments. 

Instructions: All submissions received 

must include the agency name, Docket 

ID number, and title for this Federal 

Register document. The general policy 

for comments and other submissions 

from members of the public is to make 

these submissions available for public 

viewing on the internet at http://

www.regulations.gov as they are 

received without change, including any 

personal identifiers or contact 

information. 


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