Who is accountable for the outcome, when AI assists in the decision?

Accountability (!) Who Owns the Outcome?

Responsibility, Professional Standards, AI, and the Growing “Responsibility Gap**”**

What does it mean to be accountable for your work when more and more of that work is assisted by software, algorithms, and AI?
Traditionally, professional responsibility was relatively simple: if your name was on the report, calculation, diagnosis, recommendation, or decision, you owned the result. But that principle is becoming less obvious. “The software made an error,” “the model hallucinated,” or “the algorithm recommended it” can easily become explanations—and sometimes excuses.

As AI becomes embedded in medicine, finance, engineering, law, education, management, and everyday work, an important question emerges: does using better tools increase our responsibility, or make it easier to avoid it?

Topics we’ll touch on:
If your name is on the work, are you responsible for 100% of the outcome?
When is blaming software legitimate—and when is it avoiding responsibility?
Does AI create a new “responsibility gap”?
Should professionals be expected to verify everything an AI produces?
What happens to expertise when people increasingly trust tools they don’t fully understand?
Are professional standards becoming weaker, or simply changing?
Who is responsible when an AI-assisted decision causes serious harm, the user, the employer, the developer, or everyone?
And finally… can we keep the benefits of AI without losing the culture of personal responsibility that professional work depends on?

Casual discussion. No technical background required, just curiosity, experience, and a willingness to question where responsibility should begin and end.
Bring your examples. Challenge the excuses.
Decide who really owns the outcome.