| The Morals for Robots: Ethical Issues in the Automated use of Commercial Internet Resources for Academic Research |
| with Dan L. Burk and Charles Ess. Under second review at Ethics and Information Technology |
Abstract:
Internet researchers increasingly have at their disposal of an array of automated software agents, or “bots,” which can rapidly retrieve a variety of economic and technical data from publicly accessible web sites. While these automated tools greatly facilitate the retrieval and analysis of data for academic research, they may pose ethical quandaries to Internet researchers. Specifically, automated software agents place some load on servers being accessed, possibly in contradiction to the expected use of such servers, and possibly in violation of the legal prerogatives of web site owners. Determining how and when to access such web sites, and whether to seek the consent of web site owners for retrieval of publicly accessible data presents an apparent conflict between general principles of information policy and the emerging legal precedent regarding trespass to computers. This conflict may be characterized as pitting utilitarian considerations against deontological considerations in a fashion reminiscent of previous debates over informed consent in on-line research. In this paper, we examine both utilitarian and deontological characterizations of the ethical obligations of researchers employing automated data retrieval agents, and argue that the conflict between the two approaches is more apparent than real. Instead, we argue that the tension within the relevant practices indicates the need for a “meta-choice” between utilitarian and deontological considerations. We further suggest certain factors that may differentiate such a “meta-ethical” choice in the context of automated data retrieval from the “meta-ethical” choice presented in previously identified contexts of human subjects research or of web browser technology design.
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| The Ontological Foundations for Active Information Systems |
| with Salvatore T. March. Under review at the International Journal of Intelligent Information Technologies |
Abstract:
While passive information systems simply record and report on the observed states of things in the world, active information systems participate in the determination and ascription of state to things. They infer conclusions based on the application of rules that govern how things in the real world are affected when defined and identified events occur. The ontological foundations for active information systems must include constructs to represent such causal rules. Conceptualizing things and events as distinct ontological categories with existence and properties and representing them as entities at the conceptual level is sufficient for this purpose. The properties of an event include data values inherent in the event and rules that define how the states of affected things are changed when the event occurs. In this manner the state-history of a thing is represented by the sequence of events that have affected it. Future states of a thing can be predicted based on proposed or conjectured events. Such a conceptualization enables a parsimonious mapping between an active information system and the real world system it is intended to model.
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| Do Shopbots Characterize Online Markets? A Study of Shopbot Market Representativeness |
| with Jianan Wu. In draft, targeted to MIS Quarterly. |
Abstract:
The increased availability of pricing data at shopbots has proliferated a stream of empirical research on pricing behavior in electronic markets. Many researchers believe in the capability of these shopbots and consequently validate their research using data collected from a small set of shopbots (one or two in general). This practice raises a fundamental question: To what degree do these shopbots represent the market being studied? Using a data set collected from over 400 products on eight popular shopbots for a four month time period with 2.2 million observations in the Internet book market, we found that: 1) It is an invalid assumption that shopbots are equally representative. Some shopbots represent the market better than others. 2) Two important factors jointly determine a shopbot’s market representativeness: its vendor coverage capability and its vendor affiliation strategy. Two shopbots can have equal market representativeness for fundamentally different reasons. 3) More shopbots jointly represent the market better on average, but a wisely chosen few can outperform a poorly chosen many.
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| The Effects of Anchoring and Adjustment on Database Query Reuse |
| with Jeffrey Parsons. In data analysis, targeted to Information Systems Research (ISR) |
Abstract:
Cognitive heuristics are basic unconscious mechanisms people use to cope with complexity in problem solving. However, the use of heuristics has been shown to produce biases in a range of settings. The anchoring heuristic and resulting adjustment bias have been shown to affect the reuse of program code and design models in systems development. In this research, we extend the notions of anchoring and adjustment to the reuse of SQL queries. We conduct an online study involving hundreds of students from several universities to examine this issue empirically.
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| Advances in Data Modeling |
| with Akhilesh Bajaj, Vijay Khatri, Sudah Ram and Keng Siau. In draft, targeted to Communications of the AIS |
| Momentum in World Markets |
| with David Lesmond. In draft, targeted to the Journal of Finance |
| An Ontology of the Artificial |
| with Salvatore T. March. In draft, targeted to the IEEE Transactions on Knowledge and Data Engineering |
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Research