Nicola Dell

Assistant Professor
Information and Computer Science
Cornell Tech
111 8th Ave, #303
New York, NY, 10011

nixdell (at) cornell.edu

I do research at the intersection of human-computer interaction (HCI) and information and communication technologies for development (ICTD). My high-level goal is to create new technologies that empower underserved populations to overcome global challenges in critical domains like healthcare, security and privacy, accessibility, and more.

This is a list of a few projects I am working on or have worked in the past.

Participant having their fingerprints taken

Privacy and Surveillance in the Global South: Biometric Mobile Registration in Bangladesh

With the rapid growth of ICT adoption in the Global South, crimes over and through digital technologies have also increased. Consequently, governments have begun to undertake a variety of different surveillance programs, which in turn provoke questions regarding citizens' privacy rights. However, both the concepts of privacy and of citizens' corresponding political rights have not been well-developed in HCI for non-Western contexts. We conducted a three-month long ethnography and online survey in Bangladesh, where the government recently imposed mandatory biometric registration for every mobile phone user. Our analysis surfaces important privacy and safety concerns regarding identity, ownership, and trust, and reveals the cultural and political challenges of imposing biometric registration program in Bangladesh. Read more about the project here.

Feedback for CHWs about their performance

Closing the feedback loop: Providing health workers with personalized, on-demand feedback

Community Health Workers, known in India as ASHAs, are increasingly important members of the public health system and many organizations are deploying mobile health tools in an effort to support them in the field. The goal of this project is to investigate the impact of closing the feedback loop by providing health workers in remote settings with personalized, on-demand information regarding the work they have done. Specifically, we designed and built the ASHA Self-Tracking Application (ASTA), a tool that enables ASHAs to access feedback about their own performance that is derived from the data that they have collected in the field. Findings from our 12-month deployment with 142 ASHAs in India provide promising evidence that tools like ASTA could be cost effective and impactful for ASHA programs. Read more about the project here and here.

The Privacy Challenges Surrounding Broken Digital Artifacts in Bangladesh

Privacy Vulnerabilities in the Practices of Repairing Broken Digital Artifacts in Bangladesh

The goal of this project is to improve the practices surrounding the repair of digital artifacts in low-resource settings. Specifically, we examine the privacy challenges associated with the process of repairing digital artifacts, which usually requires that the owner of a broken artifact hand over the technology to a repairer. Findings from our ethnographic work conducted at 10 repair markets in Dhaka, Bangladesh, show a variety of ways in which the privacy of an individual’s personal data may be compromised during the repair process. We also examine people’s perceptions around privacy in repair and its connections with broader social and cultural values. Read more about the project here.

Social Media Platforms for Low-Income Blind People in India

Social Media Platforms for Low-Income Blind People in India

This project examines the use and non-use of social media platforms by low-income blind users in rural and peri-urban India. We study the benefits received by low-income blind people from Facebook, Twitter and WhatsApp and investigate constraints that impede their social media participation. We also analyze how low-income blind people used a voice-based social media platform deployed in India that received significant traction from low-income people in rural and peri-urban areas. In 11 weeks of deployment, fifty-three blind participants collectively placed 4784 voice calls, contributed 1312 voice messages, cast 33,909 votes, and listened to messages 46,090 times. Read more about our work here.

A hybrid SMS system

Engaging pregnant women in Kenya with a hybrid computer-human SMS communication system

The proliferation of mobile devices throughout the world is providing opportunities to create mobile applications that deliver health and information services to people living in poverty. This project investigates if a hybrid computer-human SMS system can engage pregnant women in health-related conversations with a nurse. Read about our findings from a 12 month deployment with 100 pregnant women here.

ODK Scan

Digitizing paper-based data in global development

Global development organizations working in low-resource environments rely on large-scale data collection to measure their impact and control the quality of the services they provide. In regions constrained by poor infrastructure and limited resources, this data must often be collected in paper - not digital - format. However, paper-based data is difficult to navigate, process, and store, and many of the complex analyses and visualizations that now routinely help people make sense of the data are only feasible if it is in digital formats. To address this problem, we created ODK Scan, a mobile camera-based system that automates the extraction of digital data from paper. You can read about our analysis of paper-digital workflows in global development organizations here, the initial development of the system here, and findings from a deployment of the system in Mozambique here. If you'd like to try it, ODK Scan is free and open-source software available here.

Response Bias

Quantifying participant response bias in HCI

Although HCI researchers and practitioners frequently work with groups of people that differ significantly from themselves, little attention has been paid to the effects these differences have on the evaluation of HCI systems. We did an experiment to measure participant response bias and understand the role of social and demographic factors in influencing that bias. We find that respondents are about 2.5x more likely to prefer a technological artifact they believe to be developed by the interviewer, even when the alternative is identical. When the interviewer is a foreign researcher requiring a translator, the bias towards the interviewer's artifact increases to 5x. In fact, the interviewer's artifact is preferred even when it is degraded to be obviously inferior to the alternative. Read more here.

ODK Diagnostics

Automatically analyzing diagnostic tests for infectious diseases

Health workers in remote settings often lack access to affordable and usable diagnostic technologies that could help them to quickly diagnose and treat infectious diseases. In this project, we created a mobile system that uses a smartphone's built-in camera to capture a photograph of a diagnostic test, after which computer vision algorithms running on the device automatically analyze the image, compute the diagnosis, and deliver it to the health worker. Read more about the development of the system here. Read about our field evaluation of the system 60 health workers at five hospitals and clinics in Zimbabwe here.

Open Data Kit

Open Data Kit

Open Data Kit (ODK) is an open-source suite of tools that helps organizations author, field, and manage mobile data collection solutions. Our goals are to make open-source and standards-based tools that are easy to try, easy to use, easy to modify and easy to scale. ODK has become one of the leading mobile data collection solutions available and has been deployed by a wide variety of organizations in dozens of countries around the world. Read about the recent development of the ODK 2.0 tools here. To use the tools and find out more visit the ODK webpage.

Touch-Free Interaction

Mobile touch-free interaction for global health

The suitability of mobile devices for health applications in developing countries has resulted in the creation of tools designed to increase access to healthcare, improve disease diagnosis and tracking, and provide health workers with ongoing medical education and training. Many of these applications require health workers to handle potentially infectious material, like blood or other biological samples and touching a mobile device risks contamination. We developed a mobile system that uses the built-in camera on the device and computer vision to detect in-air gestures so that health workers are able to interact with the device touch free. Read more about the system here.