Accelerated Research Program

Human-Machine Teaming: Applications, Issues, and Case Studies

Faculty Advisor: Adjunct Faculty, Carnegie Mellon School of Computer Science

What is an Accelerated Research Program?

Our Accelerated Research Practicum combines recorded and live sessions with the Faculty Advisor. It allows students to achieve tangible outcomes and potentially earn a letter of recommendation in a shorter period of time.

Research Program Introduction

Humans and machines have different capabilities. Steve Jobs, decades ago, waxed eloquent on the amplification of human ability by referring to the efficiency of man with a bicycle. With the increasing prevalence of artificial intelligence (AI), the debate is shifting to how machines can complement people, scale human performance and expertise, and reduce risk.

Frameworks and best practices for teaming are evolving in different milieus. Data, mores, task goals, and component capabilities may dictate the overall team architecture. This is a fertile ground for learning and experimenting in a contemporary sandbox. A focus area is bias-free implementations with attention to ethical considerations.

In this project, the Faculty Advisor will provide motivating scenarios and pathways for exploration. Participants will get a taste of data analysis and AI concepts. This innovative practicum will lay a foundation for critical, data-oriented thinking and problem-solving in a technologically advancing world.

The faculty advisor will guide students on which topic they should choose for their final project. Students will have access to videos, notes, and project topics to pursue for their final projects. 

At the end of the program, each student will complete a concise 3 to 5-page research paper or proposal and submit it to the faculty advisor for a final review.

Possible Topics For Final Project

  • Human-machine teaming for health: How can wellness and clinical care be improved by combining expert clinicians and tools?

  • Human-machine teaming in the wealth milieu: Predicting stock prices, analyzing economic data

  • Human-machine teaming in the Wisdom milieu: How to disseminate reliable information in a world with over-flooded information? 

  • Human-machine teaming for prediction: How to design surveys and polling to inform results of future events (in sports, politics, etc.) 

  • Human-machine teaming for social responsibility: How to reduce bias via teaming? How do we achieve social justice?

  • Other professor-approved topics in this subject area that you are interested in

Program Details

  • Cohort size: 2 to 5 students

  • Duration: 4 weeks

  • Target students: 7 to 12th graders interested in computer science, artificial intelligence, data analytics, FinTech, healthcare technology, or machine learning who wish to complete a research project with a prestigious professor rapidly to boost their research experience and obtain deliverables for college applications and other programs.

Program Structure

  • Week 1: Students and the faculty advisor will discuss the available project topics in a live session and agree on a set of goals for the project. 

  • Week 1 to 3: Students will complete an extensive recorded video research program, including core videos that must be completed and optional advanced videos for students with higher aims.

  • Week 4: Students will complete their research project and submit it for review. They will also have a second live session with their faculty advisor to ask questions, discuss their findings, and positively conclude their research experience.