Page 47 - Cyber Defense eMagazine July 2024

8. Develop policies: as developers of AI, establish and enforce principles for effective security and
privacy; as users of AI, establish and enforce requirements around usage of AI. Be sure to
educate users on the why.

Bias and Discrimination – Revisited

Regarding bias and discrimination, the following is a non-exhaustive list of considerations to mitigate the
risk of exacerbating unfair stereotypes and prejudices.

1. Diverse and representative datasets: AI training data should be diverse and representative of the
population to mitigate bias and discrimination.
2. Inclusive design: design elements must be considered to ensure accessible and equal usability,
regardless of background, identity, or physical ability.
3. Community engagement and feedback: diverse communities should be consulted for input of the
design and implementation to ensure unique needs and perspectives are accounted for.
4. Socioeconomical impacts: consider the socioeconomic implications of AI-based automation for
various tasks. While this may be an ethical question, take stock of how these systems can
potentially lead to job displacement in low-income communities, widening the economic gap
between groups.
5. Human intervention: ensure protocols are in place for fallback or escalations to people, particularly
when AI is used for significant life-changing decisions.

Just like in aspects of cybersecurity where the advancement of technology leads to both more
sophisticated tools and controls for defense, but also more savvy advisories and tactics on offense, AI
poses a similar paradigm. As the algorithms get more advanced, the risks and potential for harm grows
with it. It is crucial to keep the privacy, security, and biases top of mind when leveraging this technology
and always calling for the highest standards of transparency, accountability, and protection.

About the Author

Céline Gravelines has 10 years of experience in the cybersecurity industry,
specializing in data protection, security policies, incident response, risk &
management, vulnerability management, privacy, and more. Named one
of the Cyber Defense Global InfoSec Top Women in Security, she
currently serves as the Director of Cybersecurity Professional Services at
Keyavi where she works with self-protecting data technology to eliminate
data loss. Céline holds a BSc in Computer Science and Physics, and a
MSc in Computer Science, focusing on applying unsupervised machine
learning to brain space.

Céline can be reached by email at [email protected] and at
our company website https://www.keyavi.com/

Cyber Defense eMagazine – July 2024 Edition 47
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