Problem Statement

Software systems are replacing or expanding human decision making in crucial ways. People have become accustomed to algorithms recommending products to buy, songs to listen to, and suggesting social network connections.  However, algorithms are not just recommending; they are also being used to make big decisions about people's lives such as who gets a loan, whose resumes are reviewed by humans for possible employment and the length of prison terms for criminals.  Although algorithmic decision making can offer benefits in terms of speed, efficiency, and even fairness, there is a common misconception that algorithms automatically result in fair decisions. In reality, algorithms that are not easy to understand can also unfairly limit opportunities, restrict services, and even improperly restrict liberty.

Your Challenge

This year’s Young Scholars will be challenged to consider ways in which society can benefit from algorithmic decision making while at the same time preventing software systems from becoming mysterious black boxes that issue decisions that are difficult to challenge. Working with Clarkson professors, students will explore algorithmic decision making in areas such as hiring, housing, credit, criminal justice, and more. They will consider how these systems are constructed, the benefits delivered, and the problems reported when the systems are utilized. Students will learn how machine learning algorithms systems are trained using datasets and the implication of the specific learning algorithms and datasets chosen. They will also will investigate claims of bias in systems being used and develop solutions for preventing bias.

Young Scholars will be tasked with proposing methods and procedures for incentivizing the makers of software systems to identify patterns of mistakes and how to improve their systems. They will be asked to propose ways to keep human decision makers aware of the limitations of these systems and engaged in the decision making process as well as the best way to provide transparency and accountability when appropriate.

Expected Outcomes

Participants in the project will be expected to be able to:

  • Identify real-world examples of high-stakes decisions made with software systems and consider the role of machine learning and individual’s personal data in how these decisions are made.
  • Consider both the pros and cons of algorithmic decision making for the decider, those being decided about, and society as a whole.
  • Consider what rights individuals should have to understand and challenge decisions made about them.
  • Consider what rights companies should have to keep their software and algorithms secret or proprietary.
  • Analyze proposals for providing transparency in the decision making process so that mistakes can be identified.
  • Propose ways to achieve fairness and accountability in algorithmic decision making.


At the end of the week, Young Scholars will present their proposals to guest panelists.

Students who successfully complete the program and meet the admission requirements will receive a $4,000 scholarship ($1,000 per year) toward tuition if they attend The Clarkson School or Clarkson University full time for their undergraduate education. Please note that $1,000 per year is the maximum scholarship amount a student can receive for attending Clarkson University summer programs, no matter how many programs he or she attends.

To download the application and for further information, please visit the Young Scholars main page.