[Ground-station] FCC TAC AI/ML working group kick-off meeting

[Michelle Thompson]

Today is the kick-off meeting for the Artificial Intelligence and Machine
Learning working group that we are part of at the FCC Technological
Advisory Committee for 2022.

A starting point for the weekly meetings and guest speakers is here:

https://www.fcc.gov/sites/default/files/fcc_aiwg_2020_whitepaper_final.pdf

This was where things left off.

Today's agenda:

Agenda:

Introductions

Let us know something about yourself, what your interests are for AI/ML in
general, and what part of the charter (below) are you interested in.

Discuss general approach for the year (speakers, internal discussions, sub
working groups?)
Review .01 draft viewgraphs briefly

Here is our charter for reference:

Artificial Intelligence/Machine Learning WG

Expand pilot project proposal(s) from the 2020 TAC session to provide
details and associated quality metrics that will allow the Commission to
explore, extract the value, and gauge the success of implementing AI/ML
techniques.

Explore the use of AI/ML methods and techniques to improve the utilization
and administration of spectrum (licensed, unlicensed, and shared) by
addressing the fundamental aspects of propagation, interference, signal
processing, and protocols.

Evaluate the use of AI/ML methods and techniques applied to assuring the
safety, security, and performance of network equipment, network control,
and network operations in a network environment that increasingly relies on
automation, is seeing a rapid growth of new network connections, and is
increasingly digitized and software- ized.

Consider the implications of AI/ML adoption by content providers and the
impact on consumers, focusing on understanding causes of and approaches to
dealing with addictive behaviors.
Formulate a better understanding of uses of AI/ML that may result in
modification of human behavior, to develop sound policies that encourage
positive outcomes (e.g., public health measures, and other benefits) and
mitigate against negative outcomes.

Notes from the meeting to follow.

Thank you to everyone that made it possible for ORI to represent open
source and amateur work on the TAC.

-Michelle Thompson
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