How to Use AI Responsibly: Start Here (For Creators, Clinicians, Scientists, and Businesses)

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How to Use AI Responsibly: Start Here (For Creators, Clinicians, Scientists, and Businesses)

Introduction

If you’ve spent years being told you’re “too sensitive,” or you’ve dipped into the HSP world and felt half‑seen and half‑misunderstood, this is your starting point. NeuroHyperSensitivity™ (NHS) gives a different, biologically honest name to what your nervous system has been doing all along.

This "Start Here" guide lays out how I approach AI: human first, tools second, with privacy and responsibility built in from the beginning.

1. Why responsible AI matters for real people

For many professionals, AI is not just about productivity. It touches:

Patient stories and health data.
Research notes and unpublished findings.
Client emails, contracts, and internal documents.
Audience trust and professional reputation.

Uploading that into the wrong tool- or using the right tool the wrong way - has consequences: privacy breaches, broken trust, policy violations, and in some contexts, real harm.

Responsible AI use is not optional; it is part of doing your work ethically.

2. My core principles (code of ethics in plain language)

Human first, tools second:
AI supports human judgment; it never replaces responsibility. Humans stay in the loop for decisions that affect people.
Privacy and data protection by default:
I do not encourage or model uploading sensitive, identifiable, or protected data into tools that do not clearly safeguard it.
Transparent use of AI:
When AI assists my content or workflows, I am open about that. I avoid presenting machine-generated output as purely human when that would mislead.
No harmful or deceptive practices:
I refuse tactics and tools that rely on manipulation, spam, or policy violations—even when they're profitable.
Evidence-informed, not hype-driven:
Recommendations are based on real use, clear reasoning, and alignment with ethics and safety, not just affiliate payouts or trends.
Respect for professionals and end users:
Clinicians, scientists, patients, clients, and businesses deserve tools that protect their dignity and data. Everything I teach aims to honor that.
Ongoing learning and correction:
AI and regulations change. When the facts move, my guidance updates. I do not cling to outdated advice for the sake of consistency.

3. What can go wrong if you ignore this

Without a responsible framework, common risks include:

Putting identifiable patient or client data into general AI tools that store, log, or use it for training.
Violating platform policies (for example, not disclosing AI use where required).
Publishing AI-fabricated or hallucinated information as fact.
Building entire businesses on deceptive AI workflows that collapse when rules tighten or trust erodes.

The point is not to scare people away from AI, but to show that "move fast and automate everything" can be reckless in healthcare, research, science, and business operations.

4. A simple checklist for choosing AI tools safely

Before you trust an AI tool with your work, ask:

Can I easily find and understand the privacy policy?
Does the company clearly state whether my data is used to train their models?
Is there any control over training on my data (opt-out, settings)?
How long is data stored, and where (what country/jurisdiction)?
Can I export or delete my data if I stop using the tool?
Is this tool appropriate for the kind of data I'm using (e.g., non-clinical vs clinical, non-identifiable vs identifiable)?
Are there transparent terms about compliance for my field (research, healthcare, science, business, etc.)?

If you cannot confidently answer these, you either limit what you input or choose a different tool.

5. How I personally use AI (and where I draw the line)

I use AI for: ideation, outlining, simplifying technical language, summarizing non-sensitive documents, generating variations, and organizing thoughts.

I do not use AI for: storing raw patient data, copying confidential research notes, making final clinical decisions, or automating ethical judgment.

My rule is: if I would be uncomfortable seeing this text on a public billboard with my name on it, it does not go into a generic AI tool.

6. Where to go next

If you want to see what this looks like in practice, subscribe to my Youtube channel:

Coming soon!

If you're a clinician, scientist, business, or organization and want
training on responsible AI, you can learn about my speaking and
consulting here:

YES, I need this!