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AI10 min read

AIinSecurityWithoutLosingAccountability

Models can surface patterns humans miss. They cannot own a decision. Here is how to use them without hiding the chain of command.

By Ananya Mehta

Abstract visualisation of AI neural patterns

Introduction

AI is useful in security when it narrows attention: ranking alerts, clustering related events, or highlighting unusual paths through a system.

It becomes dangerous when teams treat a score as a decision. Someone still has to accept the risk, change the control, or leave the system as it is.

Keep a human on the loop

PCS builds programmes where models assist the loop without replacing it. Intelligence stays accountable even when the analysis is automated.

  1. 01

    Narrow attention, do not replace it

    Models are useful when they rank, cluster, or highlight. They are not useful when they hide who decided.

  2. 02

    Name the owner

    Every recommended action needs a person who can accept, change, or refuse it.

  3. 03

    Keep a record

    The organisations that use these tools well can show why an action was taken, not only that a model scored it.

AI10 min read

Written by Ananya Mehta

Tags

  • #ai
  • #accountability
  • #security

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