Algorithms That Make You Think

Algorithms That Make You Think

Fourth Annual Virginia Tech Workshop on the Future of Human-Computer Interaction
April 11-12, 2019


The workshop is presented by CHCI, and co-sponsored by CFH and DAC.

Moss Arts Center

Algorithms play an increasingly important role in shaping many aspects of our daily lives. What if human-algorithm communication were different? What if we purposely involve humans in the algorithmic decision making pipeline? What if we support human agency and traits in building and sustaining algorithmic data and decision systems? How can the inherent values of human critical thinking and creativity be incorporated into algorithms? How can we reconcile diverse perspectives and points of view about human-algorithm communication? How can we design effective human-machine collaborations for critical analysis?

The goal of this two-day workshop, held April-11-12, 2019 at Virginia Tech’s Center for Human-Computer Interaction (CHCI) in Blacksburg, Virginia,  is to find answers to these key questions pertaining to human-algorithmic interactions,  while bringing in scholarly expertise from a wide range of disciplines, including human-computer interaction, communication, law, and computer science. Therefore, a driving force behind this workshop is to encourage increased dialogue among researchers from different domain with intersecting interests in human-algorithm communication. Workshop outcomes may include system designs, best practices for ethical and responsible algorithm development, research and policy proposals, and publications and recommendations for building this area of research and practice.

About

Algorithms play an increasingly important role in shaping many aspects of our daily lives, from machine-curated social media feeds and recommendations based on previous purchases to work schedules built on recorded employee performance. This human-algorithm communication involves the development and implementation of algorithmic systems that make decisions through human data . Along with the growing attention given to such algorithmic decision-making systems, a quickly growing body of work has also begun investigating the implications of such systems making decisions on behalf of humans while using their data.

Researchers across a wide variety of disciplines including human-computer interaction, communication, law, and computer science have debated over the ways in which algorithms govern [1] and keep the human out of the decision making process. Thus, algorithmic systems powered by mathematical rigor but devoid of human agency have started exhibiting a number of problems. Specific concerns relate to algorithmic bias [2, 3], discrimination [4, 5], fairness [6], distribution of visibility [7], surveillance [8], and accountability [9].

What if human-algorithm communication were different? What if instead we purposely involve humans in the algorithmic decision making pipeline? What if we support human agency and traits in building and sustaining algorithmic data and decision systems? How can the inherent values of human critical thinking and creativity be incorporated into algorithms? How can we reconcile diverse perspectives and points of view about human-algorithm communication?

The goal of this two-day workshop is to find answers to these key questions pertaining to human-algorithmic interactions. In these interactions, human users understand and can make judgments about the system’s recommendations or actions (explainable AI), and where the system understands the human users’ actions and intentions to help refine its own behaviors (explainable IA or intelligent analyst). This interdisciplinary workshop will thus focus on topic that lie at the intersection of explainable AI and explainable IA, while considering ways to effectively design human-algorithm collaborations for critical analysis.

A series of invited talks, panel discussions, and brainstorming sessions will provoke action through the following objectives:

  • Identifying ongoing work on the topic of human-algorithm communication for critical analysis.
  • Identifying emerging challenges and new research strategies.
  • Setting a provocative vision and ongoing agenda that reimagines the design of human-algorithm systems which supporting human agency, critical thinking, and creativity.

References:

  1. Malte Ziewitz. 2016. Governing Algorithms Myth, Mess, and Methods. Science, Technology & Human Values 41, 1: 3–16.
  2. Bozdag, Engin. “Bias in algorithmic filtering and personalization.” Ethics and information technology 15.3 (2013): 209-227.
  3. Introna, Lucas D., and Helen Nissenbaum. “Shaping the Web: Why the politics of search engines matters.” The information society 16.3 (2000): 169-185.
  4. Gillespie, Tarleton. “The relevance of algorithms.” Media technologies: Essays on communication, materiality, and society 167 (2014).
  5. Kraemer, Felicitas, Kees Van Overveld, and Martin Peterson. “Is there an ethics of algorithms?.” Ethics and Information Technology 13.3 (2011): 251-260.
  6. Dwork, Cynthia, et al. “Fairness through awareness.” Proceedings of the 3rd innovations in theoretical computer science conference. ACM, 2012.
  7. Bucher, Taina. “Want to be on the top? Algorithmic power and the threat of invisibility on Facebook.” new media & society 14.7 (2012): 1164-1180.
  8. Introna, Lucas, and David Wood. “Picturing algorithmic surveillance: The politics of facial recognition systems.” Surveillance & Society 2.2/3 (2004): 177-198. Kroll, Joshua A., et al. “Accountable algorithms.” U. Pa. L. Rev. 165 (2016): 633.
  9. Schuppli, Susan. “Deadly Algorithms: Can Legal Codes Hold Software Accountable for Code That Kills?.” Radical Philosophy 187 (2014): 2-8.