PhD in “Designing Human-AI Data Sensemaking for Collaborative Decision Making”

PhD in “Designing Human-AI Data Sensemaking for Collaborative Decision Making”

Published Deadline Location
17 Jun 25 Jul Eindhoven

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Job description

Project Background
AI-empowered tools have shown great potential in supporting medical diagnosis in the healthcare domain; however, these tools have still hardly made impacts in real-world practice at this moment. To tackle these challenges, this project aims to develop new approaches and tools that enable designers to effectively harness large amounts of data to analyze complex real-world situations for supporting professional medical experts to make good decisions. Moreover, this project will explore the challenge of multiple stakeholders collaboration in which patients, medical experts with different knowledge and expertise and AI agents work together to understand, analyze and synthesize medical data in the process. In particular, we will design
AI-empowered tools that support a clinical team to understand AI's capabilities and limitations, cope with imperfect AI (e.g., ambiguous/difficult cases), and build trust relationships in collaboration with AI in a high-stakes decision-making process. With this project, we will contribute useful tools, framework and design guidelines for future human-AI collaboration in the context of clinical decision-making.

Industrial Design PhD position
In the design-research trajectory, this PhD student will explore how to design, develop and evaluate the human-AI collaboration for supporting clinical decision making. In particular, this PhD will explore how to incorporate AI into data sensemaking processes to facilitate multi-stakeholder collaboration in the context of clinical decision making. This can be achieved through design contributions to machine learning challenges (e.g., Machine teaching, AI explainability, transparency and uncertainty quantification) and user interface (UI) and user experience (UX) design challenges (e.g., how and when to show AI-generated questions, findings and explanations, appropriately visualize uncertainty and bias for professional end-users, and devise interactive interfaces for AI adoption). Designing effective collaborative data sensemaking is a combined data science, ML/AI and UI/UX design challenge; the PhD student will deal with these challenges in this project.

We are interested in understanding what is the envisioned collaboration between professional medical experts and AI for fostering adoption and appropriate trust of AI in clinical practice. The goal of this project is to gain new knowledge of how data sensemaking impacts clinical decision making and develop AI-powered tools for supporting professional decision making. The project will address critical challenges on various human-AI collaboration strategies on training AI, onboarding AI, communicating with AI and retraining AI.

We will explore some Important questions below:
  • How can we leverage clinical expert's limited time and optimize their efforts on collecting labels, annotations and explanations on medical data for training AI?
  • How can we support clinicians to onboard AI for helping specific sub-tasks (e.g., discover abnormal areas, find similar cases/treatments, etc.) during the decision-making process?
  • How can we design an appropriate interface that provides explainability and transparency for supporting clinicians to make a better use of AI in their collaborative medical-decision making?
  • How can we design tools that support design & development teams to iteratively design and evaluate clinician-AI collaboration over time?

The PhD student will explore these questions by applying the research through design methodology with hands-on making and prototyping in close contact with a wider range of stakeholders of this system such as clinicians, patients and AI agents. These will be closely involved in the co-creation process.

Eindhoven University of Technology (TU/e, www.tue.nl) is one of Europe's leading research universities. The Eindhoven area, in the southern part of the Netherlands, is one of Europe's top 'innovation ecosystems', with many high-tech companies and institutes. TU/e is intertwined with many of these companies and institutes, and research at TU/e is characterized by a combination of academic excellence, industrial relevance and societal interweaving.  The Department of Industrial Design (ID) of the Eindhoven University of Technology (TU/e), founded in 2001, is
a maturing department with over 650 students, both Bachelor and Master, and around
40 research staff members and about 10 lecturers. The mission of the department of Industrial Design at TU/e is Research on and Education in the Design of Systems with Emerging Technologies in a Societal Context.

The PhD will be under the supervision of prof.dr. Lin-Lin Chen, dr. Janet Yi-Ching Huang and
dr. Mathias Funk in the Department of Industrial Design at Eindhoven University of Technology. The project will be executed in collaboration with Philips Experience Design, e/MTC, and other institutes. At the TU/e, the positions are situated within the research cluster of 'Future Everyday'. The Future Everyday cluster investigates the everyday interactions between individual people and the highly interconnected technology that surrounds them. Researchers measure, model and design for the user experience when individuals interact with social-technological networks in their homes, at work, in transit, while doing sports or going out.

Prospective starting date: September 2021.

Specifications

Eindhoven University of Technology (TU/e)

Requirements

  • A Master's degree in an industrial design related discipline (e.g., Industrial Design, Computer Graphics) or an applied science related discipline (e.g., Computer Science) and demonstrated competences in one or more of these domains: AI, Human-Computer Interaction, Design, Computer/Data science, and other relevant fields. The Master's degree needs to be obtained before the prospective starting date of this position: September 2021.
  • A design portfolio demonstrating skills and knowledge in contextual design exploration, digital fabrication and interactive prototyping (of AI-enabled solutions), user evaluation test design & execution skills.
  • A commitment to research through design, reflection and co-design.
  • Ability to conduct and deliver high quality research both independently and as part of an interdisciplinary team.
  • Openness, interest and good soft skills to work closely with people from other disciplines and across organizations.
  • Eager to learn and tackle complex healthcare challenges. Experience working in a healthcare (design) context is a plus.
  • Good conceptual design skills for UI and data visualization.
  • Hands-on programming skills for AI and data visualization. Knowledge and skills in Programming languages (e.g., Python, Java, JavaScript), Data Visualization Libraries and tools (e.g. D3.js, Processing), 3D digital models and visualization tools (e.g., Unity, Three.js), and basic AI/ML or data science knowledge and skills (e.g., ml5.js) and eager to further develop these skills.
  • Fluency in English is a must (written and spoken).

Conditions of employment

  • A meaningful job in a dynamic and ambitious university with the possibility to present your work at international conferences.
  • A full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months.
  • To develop your teaching skills, you will spend 10% of your employment on teaching tasks.
  • To support you during your PhD and to prepare you for the rest of your career, you will make a Training and Supervision plan and you will have free access to a personal development program for PhD students (PROOF program).
  • A gross monthly salary and benefits (such as a pension scheme, pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labor Agreement for Dutch Universities.
  • Additionally, an annual holiday allowance of 8% of the yearly salary, plus a year-end allowance of 8.3% of the annual salary.
  • Should you come from abroad and comply with certain conditions, you can make use of the so-called '30% facility', which permits you not to pay tax on 30% of your salary.
  • A broad package of fringe benefits, including an excellent technical infrastructure, moving expenses, and savings schemes.
  • Family-friendly initiatives are in place, such as an international spouse program, and excellent on-campus children day care and sports facilities.

Specifications

  • PhD
  • Engineering
  • max. 38 hours per week
  • University graduate
  • V51.5069

Employer

Eindhoven University of Technology (TU/e)

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Location

De Rondom 70, 5612 AP, Eindhoven

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