PhD on human-AI collaboration at work

Updated: 29 days ago
Deadline: 30 May 2021

The Human Performance Management (HPM) Group of the School of Industrial Engineering, in collaboration with the Eindhoven Artificial Intelligence Systems Institute (EAISI), is looking for a PhD-student on human-AI collaboration at work (4-years; 1.0 FTE).

The School of Industrial Engineering is one of the longest-established IE Schools in Europe,
with a strong presence in the international research- and education community. Operations Management and Operations Research are at the core of the undergraduate IE program.
The graduate programs (MSc and PhD) in Operations Management & Logistics and in Innovation Management attract top-level students from all over the world. Researchers participate in industrial activities with members of, amongst others, the European Supply Chain Forum.

Human Performance Management (HPM) at TU/e develops scientific knowledge and tests theories that uncover and explain (psychological) processes contributing to performance at the organizational, team and individual level. By examining the 'people factor' in operational and innovation processes, HPM aims to ensure that employees can help in bringing organizational strategies to fruition in the most rewarding and efficient way possible.

The Eindhoven AI Systems Institute (EAISI) combines all TU/e Artificial Intelligence activities. Top researchers from various research groups work together to create new and exciting AI methodologies and applications with a direct impact on the real world. TU/e has been active in the field of AI for many years, which gives the new institute an excellent starting position to build upon.

The project
In many organizations and across industries, artificial intelligence (AI) is transforming the way
we work. AI-systems are implemented to assist employees with decision making, to decrease workload, or to increase efficiency. Although promising, transforming traditional operations into ones that rely on autonomous systems brings many challenges. For example, when using AI planning systems, users frequently experience difficulties in using and trusting these systems and, as a consequence, deviate from their advice. Prior research highlights the impact of system characteristics (e.g. reliability) on human-AI collaboration. However, these studies disregard the important influence of contextual factors on human-AI collaboration such as organizational climate, various leadership styles or other social and societal features. Therefore, one important challenge concerns the consideration of these different contextual factors when designing and implementing AI-systems at work. To successfully integrate these systems in organizational processes, it is therefore critical to understand when and why users are (un)willing to adopt these systems in their work routines and how we can stimulate its effective usage. The goal of this PhD-project is to address these issues by answering the following research questions:
(1) Which contextual factors (e.g. organizational climate, leadership) and societal factors
(e.g. COVID-19 pandemic), impact planners' willingness to use AI planning systems?
(2) How can human-centered AI and work design help to improve human-AI collaboration?

We expect you to:

  • further develop the project proposal based on academic literature, and in collaboration with ESCF industry partners
  • design empirical (field) studies
  • design lab/online experiments
  • statistically analyze data obtained from field studies and experiments and report on results
  • communicate practical implications of your research to specific stakeholders/the general public
  • present the findings of your research at (inter)national scientific conferences
  • publish papers in internationally renowned academic journals

This PhD project is part of the AI PLANNER OF THE FUTURE program. This ambitious research program is hosted by the TU/e-based Department of Industrial Engineering & Innovation Sciences and is supported by the European Supply Chain Forum, Department of Industrial Engineering & Innovation Sciences, the Eindhoven Artificial Intelligence Systems Institute, and the Logistics Community Brabant. The program connects to the different communities, moonshots strategic agendas and the themes of each of these supporting partners. It combines 25 researchers, 10 PhD students and over 50 Bachelor and Master students, for the coming five years (2021-2026). This AI PLANNER OF THE FUTURE program considers the explicit intertwining of technical and human elements in the context of AI planning for supply chains and logistics, considering all relevant performance indicators (people, profit, and the planet).

The AI PLANNER OF THE FUTURE program
This ambitious research program is hosted by the TU/e-based Department of Industrial Engineering & Innovation Sciences and is supported by the European Supply Chain Forum, Department of Industrial Engineering & Innovation Sciences, the Eindhoven Artificial Intelligence Systems Institute, and the Logistics Community Brabant. The program connects to the different communities, moonshots strategic agendas and the themes of each of these supporting partners. It combines 25 researchers, 10 PhD students and over 50 Bachelor and Master students, for the coming five years (2021-2026). This AI PLANNER OF THE FUTURE program considers the explicit intertwining of technical and human elements in the context of
AI planning for supply chains and logistics, considering all relevant performance indicators
(people, profit, and the planet).

The following 10 individual PhD projects are embedded in this program. We are looking for
PhD candidates from a broad range of disciplines ranging from operations research and management, supply chain management, statistics, ethics, cognivite psychology, artificial intelligence, etc.

Project 1: Learning about Customers: Demand Implications of Logistics-Related Decision-Making in B2B, Gelper, Mutlu, Langerak  https://jobs.tue.nl/en/vacancy/phd-on-marketingoperations-interface-878156.html

Project 2: Context matters: optimizing shared decision making in real-world forecasting and inventory management, Le Blanc, van de Calseyde, Ulfert   PhD on human-AI collaboration at work

Project 3: AI-Based Replenishment and Order Fulfillment Strategies for Omnichannel Supply Chains, Atan , Schrotenboer, Van Woensel  https://jobs.tue.nl/en/vacancy/phd-on-aibased-replenishment-order-fulfillment-strategies-for-supply-chains-878193.html

Project 4: Robust data-driven sustainable food supply chain, Marandi, Rohmer,
Van Woensel  https://jobs.tue.nl/en/vacancy/phd-in-%E2%80%98datadriven-approaches-towards-robust-and-sustainable-cold-chains%E2%80%99-878195.html

Project 5: Digital Twins: An ingenious AI companion or an evil twin?, Raassens, Schepers, Van Woensel https://jobs.tue.nl/en/vacancy/phd-in-ai-and-digital-twinning-878197.html

Project 6: AI for sustainable last-mile delivery by micromobility: a socio-technical perspective, Behrendt, Alkemade  https://jobs.tue.nl/en/vacancy/ai-for-sustainable-lastmile-delivery-by-micromobility-878198.html

Project 7 (Extra: 0.5 EAISI startup package + 0.5 ESCF): Data-driven Optimization using Digital Twins for Sustainable Last-Mile Delivery, Zhang, Bliek, Van Woensel
https://jobs.tue.nl/en/vacancy/phd-on-datadriven-optimization-for-sustainable-lastmile-delivery-878199.html

Project 8: Online Supply Chain Planning, Dijkman, Van Jaarsveld
https://jobs.tue.nl/en/vacancy/phd-in-information-systems-business-intelligence-878200.html

Project 9: From feared competitor to trusted companion: understanding and enhancing trust in AI over time, Snijder, Rooks, Willemsen  https://jobs.tue.nl/en/vacancy/phd-on-humanai-collaboration-in-the-workplace-trust-in-ai-over-time-878201.html

Project 10: Widening the frame: Rational choice beyond a given utility function, Müller
https://jobs.tue.nl/en/vacancy/phd-on-%E2%80%9Cimproving-automated-rational-choice-through-metacognition%E2%80%9D-878202.html


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