Taking the Person Seriously: Ethically Aware IS Research in the Era of Reinforcement Learning-Based Personalization

2023 | Journal of the Association for Information Systems | Citations: 0

Authors: Greene, Travis; Shmueli, Galit; Ray, Soumya

Abstract: Advances in reinforcement learning and implicit data collection on large-scale ... Expand

Abstract: Advances in reinforcement learning and implicit data collection on large-scale commercial platforms mark the beginning of a new era of personalization aimed at the adaptive control of human user environments. We present five emergent features of this new paradigm of personalization that endanger persons and societies at scale and analyze their potential to reduce personal autonomy, destabilize social and political systems, and facilitate mass surveillance and social control, among other concerns. We argue that current data protection laws, most notably the European Union's General Data Protection Regulation, are limited in their ability to adequately address many of these issues. Nevertheless, we believe that IS researchers are well-situated to engage with and investigate this new era of personalization. We propose three distinct directions for ethically aware reinforcement learning-based personalization research uniquely suited to the strengths of IS researchers across the sociotechnical spectrum. Collapse

Topics: usability personalization legal context General Data Protection Regulation information privacy law

Methods: reinforcement learning computational algorithm simulation language model experiment

Theories: social sciences theory

ChatGPT and GPTZero in Research and Social Media: A Sentiment- and Topic-based Analysis

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Heumann, Maximilian; Kraschewski, Tobias; Breitner, Michael H.

Abstract: Conversational AI agents like ChatGPT have gained considerable attention in rec ... Expand

Abstract: Conversational AI agents like ChatGPT have gained considerable attention in recent years, with potential implications across various domains. However, there is a gap in understanding the prevailing opinions, topics, and concerns of the public and research communities regarding these technologies. This study conducts a semi-automated analysis of over 1,006,000 tweets and 279 scholarly articles to explore perspectives on ChatGPT and its potential misuse for plagiarism, as well as the comparatively lower interest in GPTZero, a technology designed to counter AI-driven plagiarism. Employing advanced natural language processing techniques, such as sentiment analysis and topic modeling, we identify challenges and opportunities related to ChatGPT and GPTZero. Our findings uncover potential areas for improvement and provide guidance for future research and development in the field of conversational AI. Collapse

Topics: Twitter artificial intelligence human computer interaction usability Python

Methods: chatGPT topic model chatbot sentiment analysis natural language processing