HCOMP Workshop

This all-day workshop has the aim of promoting research convergence among participants on topics related to future forms of work (i.e., humans doing their jobs) with intelligent machines. We define intelligent machines as computing technologies characterized by autonomy, the ability to learn, and the ability to interact with other systems and with humans: robots and algorithms interacting with people.

This is an important topic, because the research we collectively perform should and will affect the economy. We want to design for the effects of intelligent machines on our future workplace, and on society as a whole, rather than witness or create inadvertent side effects.

Intended Audience

We seek participation from a wide range of researchers in both the computational and social sciences. We think many in the current HCOMP audience will be interested, and we think the workshop might also have appeal to scholars interested in other fields, including economics, policy, and urban design. We welcome those involved in designing technologies that affect work, in particular those who apply their research to particular industries, including manufacturing, transportation, finance, health care, agriculture, government, as well as specialized service professions like law, consulting, and architecture. We welcome those designing interfaces between algorithms and people. We also are interested in those who are experimenting with new organizational forms, including those who are using machine learning in conjunction with collectives, including crowds and online communities.

The format of the workshop will be participatory and interactive. We will run a poster session at the beginning of the workshop as a way of introducing our research to each other. ​ ​ We welcome abstracts or posters around a wide range of topics:

  • Job design incorporating machine agency
  • AI in human resources (HR)
  • A new form of CSCW: Designing intelligent machine supported cooperative work
  • Explainable AI
  • Collective Intelligence inclusive of machine intelligence
  • Organizational learning utilizing machine learning
  • Anthropomorphic AI
  • Designing, monitoring and cultivating autonomous learning machines
  • Delegation strategies: machines delegating to humans and vice versa
  • Metalevel design: helping humans design machines that design machines
  • Narrative strategies in providing explanations of what machines have learned
  • Causal models that help humans understand machines
  • Teams of humans and machines: theories and case studies
  • Bots and their effects in team settings
  • Ethics and intelligent machines
  • Interfaces to computational creativity
  • Economics of changing labor forces
  • Norms, laws and standards for intelligent machines in the workplace

The workshop has three goals: identifying specific research problems around work and intelligent machines, developing a common language base that can facilitate interdisciplinary collaboration among researchers, and identifying information and cyber-infrastructure needs to support convergent research. Workshop activities will facilitate interdisciplinary dialogue and strive to generate high-impact research ideas to advance each of these goals. The workshop is ​part of work funded by a convergence grant from the US National Science Foundation.

Organizers​​

Jeffrey V. Nickerson

Kevin Crowston

Ingrid Erickson

One-Day Schedule​

8:30-9:00 Poster setup

9:00-9:30 Workshop introduction: Overall goals and tactics for the workshop

9:30-10:00 Participant introduction via poster slam

10:00-10:30 Coffee Break and posters

10:30-12:00 Panel: Activities with Intelligent Machines

12:30 – 2:00 lunch and poster-centric conversations

1:30 – 2:00 clustering exercise for breakout

Identification of topics for breakouts using post-it technique

2:00 – 3:30 breakout sessions

3:30 – 4:00 Coffee break and posters

4:00 – 5:00 Readback of breakout sessions

5:00 – 5:30 Summary, next steps

Date: 
Thursday, July 5, 2018 - 08:30