Cyber Defense eMagazine February Edition for 2023

Avoiding bias
Objectivity and credibility of data can also depend on whether data is raw or interpreted. An example
from the medical field where raw data is encoded in order to translate into billing codes indicates that
despite employing trained coding staff, interpreting medical staff notes and diagnoses creates a layer of
human judgment and, as a consequence, a degree of subjectiveness.
Labeling data can also introduce a degree of subjectiveness, particularly if this task is carried out by an
internal team with specific expectations about the outcome—bias can sneak into the process. To ensure
accuracy in a dataset, the following steps can be taken: 1) benchmarking, 2) comparative analysis of
consistency, and 3) auditing. These steps can be demonstrated in practice using the example of a team
of phonetic transcribers annotating large audio-visual datasets for an Automatic Speech Recognition
system, as this is an effort-intensive, manual task involving a degree of human judgment with potential
for error.
As is the case with any technology that has developed through the years, such as steam engines or
computers, AI can empower us or enslave us in digital chains if we are not careful. In our various
companies, It is now our responsibility to avoid the possibility of cementing our ignorance and bias in
various models, and instead, fight for objectivity.
About the Author
Garry M. Paxinos, CTO of netTALK CONNECT and NOOZ.AI. Gary also is
the CTO at NT CONNECT, CTO at netTALK MARITIME, CTO at Axios
Digital Solutions, Head of Technology at Sezmi Corporation, SVP and Chief
Technologist at US Digital Television. He is currently holder of numerous
patents. Garry can be reached online at
https://www.linkedin.com/in/garrypaxinos/ and at our company website
https://nettalkconnect.com/
Cyber Defense eMagazine – February 2023 Edition 161
Copyright © 2023, Cyber Defense Magazine. All rights reserved worldwide.