Justin Cranshaw

Ali Alkhatib, Justin Cranshaw, Andrés Monroy-Hernández

The "gig economy" has transformed the ways in which people work, but in many ways these markets stifle the growth of workers and the autonomy and protections that workers have grown to expect. We explored the viability of a "worker centric peer economy"--a system wherein workers benefit as well as consumers-- and conducted ethnographic field work across fields ranging from domestic labor to home health care. We discovered seven facets that system designers ought to consider when designing a labor market for "gig workers," consisting principally of the following: constructive feedback, assigning work fairly, managing customer expectations, protecting vulnerable workers, reconciling worker identities, assessing worker qualifications, & communicating worker quality. We discuss these considerations and provide guidance toward the design of a mutually beneficial market for gig workers.

Carlos Toxtli, Andrés Monroy-Hernández, Justin Cranshaw

Effective task management is essential to successful team collaboration. While the past decade has seen considerable innovation in systems that track and manage group tasks, these innovations have typically been outside of the principal communication channels: email, instant messenger, and group chat. Teams formulate, discuss, refine, assign, and track the progress of their collaborative tasks over electronic communication channels, yet they must leave these channels to update their task-tracking tools, creating a source of friction and inefficiency. To address this problem, we explore how bots might be used to mediate task management for individuals and teams. We deploy a prototype bot to eight different teams of information workers to help them create, assign, and keep track of tasks, all within their main communication channel. We derived seven insights for the design of future bots for coordinating work.

Justin Cranshaw, Emad Elwany, Todd Newman et al.

Although information workers may complain about meetings, they are an essential part of their work life. Consequently, busy people spend a significant amount of time scheduling meetings. We present Calendar.help, a system that provides fast, efficient scheduling through structured workflows. Users interact with the system via email, delegating their scheduling needs to the system as if it were a human personal assistant. Common scheduling scenarios are broken down using well-defined workflows and completed as a series of microtasks that are automated when possible and executed by a human otherwise. Unusual scenarios fall back to a trained human assistant who executes them as unstructured macrotasks. We describe the iterative approach we used to develop Calendar.help, and share the lessons learned from scheduling thousands of meetings during a year of real-world deployments. Our findings provide insight into how complex information tasks can be broken down into repeatable components that can be executed efficiently to improve productivity.

Justin Cranshaw, Andrés Monroy-Hernández, S. A. Needham

In this work we present a mobile application we designed and engineered to enable people to log their travels near and far, leave notes behind, and build a community around spaces in between destinations. Our design explores new ground for location-based social computing systems, identifying opportunities where these systems can foster the growth of on-line communities rooted at non-places. In our work we develop, explore, and evaluate several innovative features designed around four usage scenarios: daily commuting, long-distance traveling, quantified traveling, and journaling. We present the results of two small-scale user studies, and one large-scale, world-wide deployment, synthesizing the results as potential opportunities and lessons learned in designing social computing for non-places.