The Architecture of Responsible Value Creation
How can ethics be made operational, measurable and verifiable? Lukas Madl had the opportunity to explore this question that is becoming increasingly important.
AI Liability Starts Before Compliance Deadlines
Delaying AI Act timelines doesn’t delay liability risks. The Digital Omnibus might push deadlines back but responsibility doesn’t get postponed with them.
AIMS-Workshop 2: How AIMS Brings Human Values into AI-Based Patient Safety
How can responsible AI be achieved in hospitals? In yesterday’s workshop on the AIMS project, we discussed this very question in depth, in a very open and respectful exchange.
AIMS-Workshop 1: How AIMS Brings Human Values into AI-Based Patient Safety
Can AI improve patient safety without compromising human values? This question was at the heart of the AIMS ethics workshop, held on June 2 at Johannes Kepler University Linz.
“Ethics is not a burden—it’s a design choice.”
Marybelle Cherfan spoke with Lukas Madl about turning AI ethics into practice through Value-Based Engineering, EU AI Act compliance, auditability, and ethical guardrails for autonomous AI agents.
Purpose Workshop at Landesklinikum Baden Mödling
Relieve the burden on nursing staff. Provide better care for patients.
This isn’t just a nice-to-have—it’s the benchmark for meaningful innovation.
When AI Agents are almost right, things can go very wrong
AI agents don’t need to be malicious to cause harm—just slightly misaligned.
A recent incident at Meta shows how quickly things can escalate.
AI Act Delays: Why Trustworthy AI Can’t Wait
The Digital Omnibus on AI will likely delay key milestones of the EU AI Act.
However, deadlines may move but responsibility doesn’t—build trustworthy AI now.
The Mountain of Trust in Technology
Trust in digital and AI technologies is not built at the top. It is climbed — layer by layer. At the summit lies what we all want: trustworthy technology. But reaching it requires a solid foundation underneath.
Developing AI ethically! How does that work?
85% of the largest companies use AI in recruiting — but what if these systems reinforce biases instead of recognizing talent?