Evaluating 'Prefer not to say' Around Sensitive Disclosures

As people's offline and online lives become increasingly entwined, the sensitivity of personal information disclosed online is increasing. Disclosures often occur through structured disclosure fields (e.g., drop-down lists). Prior research suggests these fields may limit privacy, with non-disclosing users being presumed to be hiding undesirable information. We investigated this around HIV status disclosure in online dating apps used by men who have sex with men. Our online study asked participants (N=183) to rate profiles where HIV status was either disclosed or undisclosed. We tested three designs for displaying undisclosed fields. Visibility of undisclosed fields had a significant effect on the way profiles were rated, and other profile information (e.g., ethnicity) could affect inferences that develop around undisclosed information. Our research highlights complexities around designing for non-disclosure and questions the voluntary nature of these fields. Further work is outlined to ensure disclosure control is appropriately implemented around online sensitive information disclosures

Cultures in Community Question Answering

CQA services are collaborative platforms where users ask and answer questions. We investigate the influence of national culture on people's online questioning and answering behavior. For this, we analyzed a sample of 200 thousand users in Yahoo Answers from 67 countries. We measure empirically a set of cultural metrics defined in Geert Hofstede's cultural dimensions and Robert Levine's Pace of Life and show that behavioral cultural differences exist in community question answering platforms. We find that national cultures differ in Yahoo Answers along a number of dimensions such as temporal predictability of activities, contribution-related behavioral patterns, privacy concerns, and power inequality.Comment: Published in the proceedings of the 26th ACM Conference on Hypertext and Social Media (HT'15

Understanding Chilling Effects

With digital surveillance and censorship on the rise, the amount of data available online unprecedented, and corporate and governmental actors increasingly employing emerging technologies like artificial intelligence (AI), machine learning, and facial recognition technology (FRT) for surveillance and data analytics, concerns about “chilling effects”, that is, the capacity for these activities “chill” or deter people from exercising their rights and freedoms have taken on greater urgency and importance. Yet, there remains a clear dearth in systematic theoretical and empirical work point. This has left significant gaps in understanding. This article has attempted to fill that void, synthesizing theoretical and empirical insights from law, privacy, and a range of social science fields toward a more comprehensive and unified understanding.I argue that conventional theories, based on fear of legal or privacy harm, are narrow, empirically weak, cannot predict or explain chilling effects in a range of different contexts, and neglect its productive dimensions—how chilling effects shape behavior. Drawing extensively on social science literature, I argue that chilling effects are best understood as a form of social conformity. Chilling effects arise out of contexts of ambiguity and uncertainty—like the ambiguity of public or private sector surveillance—but have deeper psychological foundations as well. In moments of situational uncertainty, people conform to, and comply with, the relevant social norm in that context. Sometimes this means self-censorship, but most often it means more socially conforming speech or conduct. A theory of chilling effects as social conformity has important normative, theoretical, and empirical advantages, including greater explanatory and predictive power, clarifying what chilling effects theory is for and what it produces, as well as providing a basis to navigate competing and differing chilling effect claims. It also has implications, I argue, for constitutional standing as well as the First Amendment chilling effects doctrine

Understanding Chilling Effects

With digital surveillance and censorship on the rise, the amount of data available unprecedented, and corporate and governmental actors increasingly employing emerging technologies like artificial intelligence and facial recognition technology for surveillance and data analytics, concerns about “chilling effects,” that is, the capacity for these activities to “chill” or deter people from exercising their rights and freedoms, have taken on greater urgency and importance. Yet, there remains a clear dearth in systematic theoretical and empirical work points. This has left significant gaps in understanding. This Article has attempted to fill that void, synthesizing theoretical and empirical insights from law, privacy, and a range of social science fields toward a more comprehensive and unified understanding. I argue that conventional theories, based on fear of legal or privacy harm, are narrow, are empirically weak, cannot predict or explain chilling effects in a range of different contexts, and neglect the productive dimensions of chilling effects—how chilling effects shape behavior. Drawing extensively on social science literature, I argue that chilling effects are best understood as a form of social conformity. Chilling effects arise out of contexts of ambiguity and uncertainty—like the ambiguity of a vague law or surveillance—but have deeper psychological foundations as well. In moments of situational uncertainty, people conform to and comply with the relevant social norm in that context. Sometimes this means self-censorship, but most often it means more socially conforming speech or conduct. A theory of chilling effects as social conformity has important normative, theoretical, and empirical advantages, including greater explanatory and predictive power, clarifying what chilling effects theory is for and what it produces, as well as providing a basis to navigate competing and differing chilling effect claims. It also has implications, I argue, for constitutional standing as well as the First Amendment chilling effects doctrine

An experimental analysis of bounded rationality: Applying insights from behavioral economics to information systems

The paradigm of bounded rationality considers the limited ability of individuals to make consistent and rational choices. Due to the scarcity of research on this phenomenon in information systems, we conducted an experimental study investigating decision-making regarding risk preferences and social preferences. Moreover, we explored the stability of these preferences under different conditions and uncovered the role of information retrieval in individual decision-making. We find that although individuals are generally risk-averse and egoistic, none of these preferences is stable under the conditions tested which provides indices of boundedly rational decision-making. Although the information retrieved by participants generally allows to infer their preferences, the increasing amount and complexity of this information again often results in boundedly rational behavior.bounded rationality, experimental design, information retrieval, stability of attitudes and behavior, cognitive tracing, behavioral economics, behavioral information systems

User’s Continuance Intentions of Digital Payment Based on Expectation-Confirmation Method and Trust

Since the Covid-19 pandemic entered Indonesia in 2020, people have started to switch from cash/traditional payments to digital payments with aim to reduce direct physical contact. Digital payment that currently booming is Qris payment method, which offer convenience and speed in transactions. This study aims to look at user continuance intention on using digital payments using the Expectation-Confirmation Model (ECM) approach. In this volatility, uncertainty, complexity, and ambiguity (VUCA) era, this study adapt the concept of trust in technology adoption. Based on the literature study that has been collected, researchers obtain several variables that can influence user intentions to continue using digital payments, including: confirmation, perceived usefulness, satisfaction, information quality, perceived privacy protection and security, trust, and continuance intention