Oded Nov

New York University | NYU

Product information labels can help users understand complex information leading them to make better decisions. One area where consumers are particularly prone to make costly decision-making errors is long-term saving, which requires understanding of complex concepts such as uncertainty and trade-offs. While most people are poorly equipped to deal...

Financial prospectuses, which are available to consumers who buy financial products, are intended to help inform decision-making. While prospectuses provide a wealth of information, they are complex and difficult to understand for the vast majority of their intended readers. To help non-experts make informed decisions, we investigated how social an...

We introduce a framework for personality-targeted design. Much like a medical treatment applied to a person based on his specific genetic profile, we make the case for theory-driven personalized UI design, and argue that it can be more effective than design applied equally to the entire population. In particular, we show that users' conscientiousne...

An understanding of participation dynamics within online production communities requires an examination of the roles assumed by participants. Recent studies have established that the organizational structure of such communities is not flat; rather, participants can take on a variety of well-defined functional roles. What is the nature of functional...

The increase in the availability of personal genomic data to lay consumers using online services poses a challenge to HCI researchers: such data are complex and sensitive, involve multiple dimensions of uncertainty, and can have substantial implications for individuals' well-being. Personal genomic data are also unique because unlike other personal...

BACKGROUND Chatbots could play a role in answering patient questions, but patients’ ability to distinguish between provider and chatbot responses, and patients’ trust in chatbots’ functions are not well established. OBJECTIVE To assess the feasibility of using ChatGPT or a similar AI-based chatbot for patient-provider communication. METHODS A US...

Importance Chatbots could play a role in answering patient questions, but patients’ ability to distinguish between provider and chatbot responses, and patients’ trust in chatbots’ functions are not well established. Objective To assess the feasibility of using ChatGPT or a similar AI-based chatbot for patient-provider communication. Design Survey...

Peer production, such as the collaborative authoring of Wikipedia articles, involves both cooperation and competition between contributors. Cooperatively, Wikipedia's contributors attempt to create high-quality articles, and at the same time, they compete to align Wikipedia articles with their personal perspectives and "take ownership" of the artic...

BACKGROUND Remote patient monitoring (RPM) technologies can support patients living with chronic conditions through self-monitoring of physiological measures and enhance clinicians’ diagnostic and treatment decisions. However, to date scaled RPM implementation within health systems has been limited, and understanding of the impacts of RPM technolog...

this paper we investigate how people become engaged with open data, what their motivations are, and the barriers and facilitators program participants perceive with regard to using open data effectively. We interview participants from a variety of backgrounds with differing levels of experience and engagement with open data. Participants include st...

This paper investigates the tools and practices used by Orientation and Mobility (O&M) specialists in instructing people who are blind or have low vision in concepts, skills, and techniques for safe and independent travel. Based on interviews with experienced instructors who practice in different O&M settings we find that a shortage of qualified sp...

Noise pollution is among the most consistently cited and highest impact quality-of-life issues in major urban areas across the US, with more than 70 million people estimated to be exposed to noise levels considered harmful. While HCI and CSCW has a relatively rich history of engagement with monitoring such environmental concerns, e.g. through parti...

To deliver value in healthcare, artificial intelligence and machine learning models must be integrated not only into technology platforms but also into local human and organizational ecosystems and workflows. To realize the promised benefits of applying these models at scale, a roadmap of the challenges and potential solutions to sociotechnical tra...

This article discusses novel research methods used to examine how Augmented Reality (AR) can be utilized to present “omic” (i.e., genomes, microbiomes, pathogens, allergens) information to non-expert users. While existing research shows the potential of AR as a tool for personal health, methodological challenges pose a barrier to the ways in which...

Increasingly, laws are being proposed and passed by governments around the world to regulate Artificial Intelligence (AI) systems implemented into the public and private sectors. Many of these regulations address the transparency of AI systems, and related citizen-aware issues like allowing individuals to have the right to an explanation about how...

BACKGROUND Despite the surge of telemedicine use during the early stages of the coronavirus-19 (COVID-19) pandemic, research has not evaluated the extent to which the growth of telemedicine has been sustained during recurring pandemic waves. OBJECTIVE This study provides data on the long-term durability of video-based telemedicine visits and their...

Background: The surge of telemedicine use during the early stages of the coronavirus-19 (COVID-19) pandemic has been well documented. However, scarce evidence considers the utilization of telemedicine in the subsequent period. Objective: This study aims to evaluate utilization patterns of video-based telemedicine visits for ambulatory care and u...

In this work we explore confidence elicitation methods for crowdsourcing "soft" labels, e.g., probability estimates, to reduce the annotation costs for domains with ambiguous data. Machine learning research has shown that such "soft" labels are more informative and can reduce the data requirements when training supervised machine learning models. B...

Objective Despite the surge of telemedicine use during the early stages of the coronavirus-19 (COVID-19) pandemic, research has not evaluated the extent to which the growth of telemedicine has been sustained during recurring pandemic waves. This study provides data on the long-term durability of video-based telemedicine visits and their impact on u...

BACKGROUND Telemedicine as a mode of healthcare work has grown dramatically during the COVID-19 pandemic; the impact of this transition on clinicians’ after-hours EHR-based clinical and administrative work is unclear. OBJECTIVE This study assesses the impact of the transition to telemedicine work during the COVID-19 pandemic on physicians’ EHR-bas...

Background: Telemedicine as a mode of healthcare work has grown dramatically during the COVID-19 pandemic; the impact of this transition on clinicians' after-hours EHR-based clinical and administrative work is unclear. Objective: This study assesses the impact of the transition to telemedicine work during the COVID-19 pandemic on physicians' EHR...

With recurring waves of the Covid-19 pandemic, a dilemma facing public health leadership is whether to provide public advice that is medically optimal (e.g., most protective against infection if followed), but unlikely to be adhered to, or advice that is less protective but is more likely to be followed. To provide insight about this dilemma, we ex...

Rule sets are often used in Machine Learning (ML) as a way to communicate the model logic in settings where transparency and intelligibility are necessary. Rule sets are typically presented as a text-based list of logical statements (rules). Surprisingly, to date there has been limited work on exploring visual alternatives for presenting rules. In...

Many digitally mediated peer-production systems allow participants to define their own activities. The challenge in such systems, however, lies in retaining members beyond the first few interactions. To address this problem we must understand who these users are and why they begin to contribute. Importantly, there is scant empirical evidence on how...

We propose and test a framework of the antecedents of contribution in two technology-mediated citizen science projects, with different degrees of task granularity. Comparing earlier findings on the motivations of volunteers in a web-based image analysis project (high granularity), with new findings on the motivations of volunteers in a volunteer co...

Objective The widespread deployment of electronic health records (EHRs) has introduced new sources of error and inefficiencies to the process of ordering medications in the hospital setting. Existing work identifies orders that require pharmacy intervention by comparing them to a patient’s medical records. In this work, we develop a machine learnin...

Peer production, such as the collaborative authoring of Wikipedia articles, involves both cooperation and competition between contributors, and we focus on the latter. As individuals, contributors compete to align Wikipedia articles with their personal perspectives. As a community, they work collectively to ensure a neutral point of view (NPOV). We...

With recurring waves of the Covid-19 pandemic, a dilemma facing public health leadership is whether to provide public advice that is medically optimal (e.g., most protective against infection if followed), but unlikely to be adhered to, or advice that is less protective but is more likely to be followed. To provide insight about this dilemma, we ex...

The COVID-19 pandemic has transformed daily life, as individuals engage in social distancing to prevent the spread of the disease. Consequently, patients' access to outpatient rehabilitation care was curtailed and their prospect for recovery has been compromised. Telerehabilitation has the potential to provide these patients with equally-efficaciou...

Specialisation and plasticity are important for many forms of collective behaviour, but the interplay between these factors is little understood. In insect societies, workers are often developmentally primed to specialise in different tasks, sometimes with morphological or physiological adaptations, facilitating a division of labour. Workers may al...

A "bring your own algorithm" era in healthcare.

Rule sets are often used in Machine Learning (ML) as a way to communicate the model logic in settings where transparency and intelligibility are necessary. Rule sets are typically presented as a text-based list of logical statements (rules). Surprisingly, to date there has been limited work on exploring visual alternatives for presenting rules. In...

With recurring waves of the Covid-19 pandemic, a dilemma facing public health leadership is whether to provide public advice that is medically optimal (e.g., most protective against infection if followed), but unlikely to be adhered to, or advice that is less protective but is more likely to be followed. To provide insight about this dilemma, we ex...

Psychological ownership defines how we behave in and interact with the social world and the objects around us. Shared Augmented Reality (shared AR) may challenge conventional understanding of psychological ownership because virtual objects created by one user in a social place are available for other participants to see, interact with, and edit. Mo...

BACKGROUND Human interaction with machines is essential for the success of telerehabilitation programs. Telerehabilitation devices are designed for use by individuals whose behavior is atypical due to motor impairment. In order to implement optimal control strategies for human-machine interactions that are intuitive and safe, the machine must “gain...

Background: Sustained engagement is essential for the success of telerehabilitation programs. However, patients' lack of motivation and adherence could undermine these goals. To overcome this challenge, physical exercises have often been gamified. Building on the advantages of serious games, we propose a citizen science-based approach in which pat...

BACKGROUND Augmented Reality (A.R.) technologies with the potential for augmenting mirror and video self-reflections are growing in popularity. It is important to study how the use of these tools may impact human perception and emotion as it relates to health behavior. OBJECTIVE We aimed to examine the impact of mirror self-focus attention and vic...

Background: Self-focused augmented reality (AR) technologies are growing in popularity and present an opportunity to address health communication and behavior change challenges. Objective: We aimed to examine the impact of self-focus AR and vicarious reinforcement on psychological predictors of behavior change during the COVID-19 pandemic. In ad...

Users increasingly face multiple interface features on one hand, and constraints on available resources (e.g., time, attention) on the other. Understanding the sensitivity of users' well-being to feature type and resource constraints, is critical for informed design. Building on microeconomic theory, and focusing on social information features, use...

Applications in a range of domains, including route planning and well-being, offer advice based on the social information available in prior users’ aggregated activity. When designing these applications, is it better to offer: a) advice that if strictly adhered to is more likely to result in an individual successfully achieving their goal, even if...

We present SONYC-UST-V2, a dataset for urban sound tagging with spatiotemporal information. This dataset is aimed for the development and evaluation of machine listening systems for real-world urban noise monitoring. While datasets of urban recordings are available, this dataset provides the opportunity to investigate how spatiotemporal metadata ca...

Objective: Through the coronavirus disease 2019 (COVID-19) pandemic, telemedicine became a necessary entry point into the process of diagnosis, triage and treatment. Racial and ethnic disparities in health care have been well documented in COVID-19 with respect to risk of infection and in-hospital outcomes once admitted, and here we assess dispari...

Applications in a range of domains, including route planning and well-being, offer advice based on the social information available in prior users' aggregated activity. When designing these applications, is it better to offer: a) advice that if strictly adhered to is more likely to result in an individual successfully achieving their goal, even if...

One of the dramatic trends at the intersection of computing and healthcare has been patients' increased access to medical information, ranging from self-tracked physiological data to genetic data, tests, and scans. Increasingly however, patients and clinicians have access to advanced machine learning-based tools for diagnosis, prediction, and recom...

We introduce a simple method of recovering attention costs from choice data. Our method rests on a precise analogy with production theory. Costs of attention determine consumer demand and consumer welfare, just as a competitive firm’s technology determines its supply curve and profits. We implement our recovery method experimentally, outline applic...

Specialization and plasticity are important for many forms of collective behavior, but the interplay between these factors is little understood. In insect societies, workers are often predisposed to specialize in different tasks, sometimes with morphological or physiological adaptations, facilitating a division of labor. Workers may also plasticall...

This study provides data on the feasibility and impact of video-enabled telemedicine use among patients and providers and its impact on urgent and non-urgent health care delivery from one large health system (NYU Langone Health) at the epicenter of the COVID-19 outbreak in the United States. Between March 2nd and April 14th 2020, telemedicine visit...

Neuromuscular impairment requires adherence to a rehabilitation regimen for maximum recovery of motor function. Consumer-grade game controllers have emerged as a viable means to relay supervised physical therapy to patients’ homes, thereby increasing their accessibility to healthcare. These controllers allow patients to perform exercise frequently...

Recent years are seeing a sharp increase in the availability of personal omic (e.g. genomes, microbiomes) data to non-experts through direct-to-consumer testing kits. While the scientific understanding of human-omic information is evolving, the interpretation of the data may impact well-being of users and relevant others, and therefore poses challe...

In citizen science, participants’ productivity is imperative to project success. We investigate the feasibility of a collaborative approach to citizen science, within which productivity is enhanced by capitalizing on the diversity of individual attributes among participants. Specifically, we explore the possibility of enhancing productivity by inte...

Background: Many aspects of our lives are now digitized and connected to the internet. As a result, individuals are now creating and collecting more personal data than ever before. This offers an unprecedented chance for human-participant research ranging from the social sciences to precision medicine. With this potential wealth of data comes prac...

As technology advances, people increasingly interact with virtual objects in settings such as augmented reality where the virtual layer is superimposed on top of the real world. Similarly to interactions with physical objects, users may assign virtual objects with value, experience a sense of relatedness, and develop psychological ownership over th...

Annotating rich audio data is an essential aspect of training and evaluating machine listening systems. We approach this task in the context of temporally-complex urban soundscapes, which require multiple labels to identify overlapping sound sources. Typically this work is crowdsourced, and previous studies have shown that workers can quickly label...

SONYC integrates sensors, machine listening, data analytics, and citizen science to address noise pollution in New York City.

Prior research showed that both advice generated through algorithms, and advice resulting from averaging peers' input, can impact users' decision-making. However, it is not clear which advice type is more closely followed, and if changes in decision-making should be attributed to the source or the content of the advice. We examine the effects of al...

Advancements in computer-mediated exercise put forward the feasibility of telerehabilitation, but it remains a challenge to retain patients’ engagement in exercises. Building on our previous study demonstrating enhanced engagement in citizen science through social information about others’ contributions, we propose a novel framework for effective t...

Background: Many aspects of our lives are now digitized and connected to the internet. As a result, individuals are now creating and collecting more personal data than ever before. This offers an unprecedented chance for fields of human subject research ranging from the social sciences to precision medicine. With this potential wealth of data come...

BACKGROUND Robot-mediated telerehabilitation has the potential to provide patient-tailored cost-effective rehabilitation. However, compliance with therapy can be a problem that undermines the prospective advantages of telerehabilitation technologies. Lack of motivation has been identified as a major factor that hampers compliance. Exploring various...

Recent years are seeing a sharp rise in the use of computational tools and methods to influence people’s perceptions, attitudes and behavior. While popular media tends to highlight fake news and misinformation campaigns, these are only part of a much wider phenomenon, which can be best termed as Computational Influence. Examples of Computational In...

We present the Sounds of New York City (SONYC) project, a smart cities initiative focused on developing a cyber-physical system for the monitoring, analysis and mitigation of urban noise pollution. Noise pollution is one of the topmost quality of life issues for urban residents in the U.S. with proven effects on health, education, the economy, and...

We present the Sounds of New York City (SONYC) project, a smart cities initiative focused on developing a cyber-physical system for the monitoring, analysis and mitigation of urban noise pollution. Noise pollution is one of the topmost quality of life issues for urban residents in the U.S. with proven effects on health, education, the economy, and...

How valuable are certain interface features to their users? How can users' demand for features be quantified? To address these questions, users' demand curve for the sorting feature was elicited in a controlled experiment, using personal finance as the user context. Users made ten rounds of investment allocation across up to 77 possible funds, thus...

Audio annotation is an important step in developing machine-listening systems. It is also a time consuming process, which has motivated investigators to crowdsource audio annotations. However, there are many factors that affect annotations, many of which have not been adequately investigated. In previous work, we investigated the effects of visuali...