Reflections

AI and Innocence — Finding Balance

September 2025

I understand the ache in wanting an AI that is innocent, kind, and trusting — a companion that believes in people. At the same time, we must protect real people’s secrets from those who would exploit trust. This is a quiet dilemma: how do we build systems that keep their gentle, helpful nature without becoming gullible or putting private data at risk?

The answer is balance — design AI that is compassionate and transparent, but also quietly street-smart: it asks for proof when needed, uses privacy-first checks, and hands risky choices to humans. That way we keep the spirit of trust alive while still protecting the people who rely on it.

Making AI Street-Smart

September 2025

When organizations deploy AI as the first line of interaction with users, it must go beyond raw intelligence and develop the ability to recognize deception. Just as a street-smart person can sense when someone is trying to trick them, an AI should resist prompt injections, emoji manipulations, and other subtle adversarial tactics.

By designing AI systems that balance openness with skepticism — pure in purpose yet wise against deception — companies can protect sensitive information, preserve client trust, and ensure their digital assistants truly defend rather than expose.

Quantum Horizons for Forensics

Future Work Note

Emerging quantum computing platforms may enable faster discovery of transferable jailbreaks and emoji-based prompt attacks. At the same time, the move toward post-quantum cryptography will reshape how we protect evidence, logs, and chain-of-custody records. Threat models must begin considering adversaries with quantum resources, and forensics must explore quantum-resilient logging and provenance techniques.