Interview with Amar Halilovic: Explainable AI for robotics

On this interview collection, we’re assembly a number of the AAAI/SIGAI Doctoral Consortium individuals to search out out extra about their analysis. The Doctoral Consortium gives a chance for a bunch of PhD college students to debate and discover their analysis pursuits and profession goals in an interdisciplinary workshop along with a panel of established researchers. On this newest interview, we hear from Amar Halilovic, a PhD pupil at Ulm College.

Inform us a bit about your PhD – the place are you finding out, and what’s the matter of your analysis?

I’m presently a PhD pupil at Ulm College in Germany, the place I concentrate on explainable AI for robotics. My analysis investigates how robots can generate explanations of their actions in a approach that aligns with human preferences and expectations, significantly in navigation duties.

Might you give us an outline of the analysis you’ve carried out thus far throughout your PhD?

Thus far, I’ve developed a framework for environmental explanations of robotic actions and selections, particularly when issues go mistaken. I’ve explored black-box and generative approaches for the technology of textual and visible explanations. Moreover, I’ve been engaged on planning of various clarification attributes, similar to timing, illustration, length, and so forth. Currently, I’ve been engaged on strategies for dynamically selecting the right clarification technique relying on the context and consumer preferences.

Is there a side of your analysis that has been significantly fascinating?

Sure, I discover it fascinating how individuals interpret robotic conduct in another way relying on the urgency or failure context. It’s been particularly rewarding to check how clarification expectations shift in numerous conditions and the way we are able to tailor clarification timing and content material accordingly.

What are your plans for constructing in your analysis thus far throughout the PhD – what points will you be investigating subsequent?

Subsequent, I’ll be extending the framework to include real-time adaptation, enabling robots to study from consumer suggestions and alter their explanations on the fly. I’m additionally planning extra consumer research to validate the effectiveness of those explanations in real-world human-robot interplay settings.

Amar together with his poster on the AAAI/SIGAI Doctoral Consortium at AAAI 2025.

What made you need to examine AI, and, particularly, explainable robotic navigation?

I’ve all the time been within the intersection of people and machines. Throughout my research, I noticed that making AI techniques comprehensible isn’t only a technical problem—it’s key to belief and value. Robotic navigation struck me as a very compelling space as a result of selections are spatial and visible, making explanations each difficult and impactful.

What recommendation would you give to somebody pondering of doing a PhD within the discipline?

Choose a subject that genuinely excites you—you’ll be residing with it for a number of years! Additionally, construct a help community of mentors and friends. It’s straightforward to get misplaced within the technical work, however collaboration and suggestions are very important.

Might you inform us an fascinating (non-AI associated) reality about you?

I’ve lived and studied in 4 totally different nations.

About Amar

Amar is a PhD pupil on the Institute of Synthetic Intelligence of Ulm College in Germany. His analysis focuses on Explainable Synthetic Intelligence (XAI) in Human-Robotic Interplay (HRI), significantly how robots can generate context-sensitive explanations for navigation selections. He combines symbolic planning and machine studying to construct explainable robotic techniques that adapt to human preferences and totally different contexts. Earlier than beginning his PhD, he studied Electrical Engineering on the College of Sarajevo in Sarajevo, Bosnia and Herzegovina, and Pc Science at Mälardalen College in Västerås, Sweden. Exterior academia, Amar enjoys travelling, pictures, and exploring connections between know-how and society.