Interview with Amar Halilovic: Explainable AI for robotics

On this interview sequence, we’re assembly a number of the AAAI/SIGAI Doctoral Consortium contributors to seek out out extra about their analysis. The Doctoral Consortium supplies a possibility for a bunch of PhD college students to debate and discover their analysis pursuits and profession aims in an interdisciplinary workshop along with a panel of established researchers. On this newest interview, we hear from Amar Halilovic, a PhD scholar at Ulm College.

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

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

Might you give us an summary of the analysis you’ve carried out to this point throughout your PhD?

Thus far, I’ve developed a framework for environmental explanations of robotic actions and choices, particularly when issues go fallacious. I’ve explored black-box and generative approaches for the era of textual and visible explanations. Moreover, I’ve been engaged on planning of various rationalization attributes, akin to timing, illustration, period, and so forth. Recently, I’ve been engaged on strategies for dynamically selecting the right rationalization technique relying on the context and person preferences.

Is there a facet of your analysis that has been significantly attention-grabbing?

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

What are your plans for constructing in your analysis to this point in the course of the PhD – what elements will you be investigating subsequent?

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

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

What made you need to examine AI, and, specifically, 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 choices are spatial and visible, making explanations each difficult and impactful.

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

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

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

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

About Amar

Amar is a PhD scholar 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 choices. He combines symbolic planning and machine studying to construct explainable robotic techniques that adapt to human preferences and completely 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. Outdoors academia, Amar enjoys travelling, pictures, and exploring connections between expertise and society.