Responsible AI on Christa Burger

Give AI a Job Description Before Giving It Access

Wed, 03 Jun 2026 00:00:00 +0000

Before giving AI more access, give it a job description.

What is it responsible for?
What should it ignore?
What does good output look like?
What tools can it use?
When should it escalate?
What should it never decide?

This sounds obvious.

It is apparently not.

People will give AI access to meaningful workflows with less role clarity than they would give an intern named Brayden who starts Monday and says “for sure” too much.

Set It and Forget It Is a Trap in AI Automation

Mon, 11 May 2026 00:00:00 +0000

“Set it and forget it” is not how most useful automation works.

It is how rot gets a login.

Systems without maintenance atrophy with time.

The better model is not forgetting.

It is rhythm:

What runs daily?
What runs weekly?
What runs when triggered?
What needs human review?
What gets summarized?
What gets escalated?
What gets archived?
Do you have something auditing it all?

AI systems need cadence because real life has cadence.

Human-in-the-Loop AI Is Not Enough

Wed, 29 Apr 2026 00:00:00 +0000

“Human in the loop” has become one of those phrases we say to make everyone feel better.

Like “cross-functional alignment.” Or “quick sync.” Or “this should be straightforward.”

The issue is not whether a human is somewhere in the loop.

The issue is whether the human is in the right place.

Before the AI acts?
After it drafts?
When risk is detected?
When money is involved?
When customer trust is at stake?
When a decision needs authority?

That matters.

What AI Governance Actually Means (And Why Most Organizations Get It Wrong)

Sat, 28 Mar 2026 00:00:00 +0000

When most organizations hear “AI governance,” they think one of two things: a policy document nobody reads, or a legal team saying no to everything.

Neither is governance. Both are avoidance.

Real AI governance is the architecture through which an organization makes decisions about AI — consistently, accountably, and in alignment with its values. It answers three fundamental questions:

Who decides? When an AI system affects employees, customers, or communities — who has authority over that decision? Who can challenge it? Who is accountable when it goes wrong?