Development in times of hype: How freelancers explore Generative AI?
Generative AI is on the rise causing some companies to turn to freelancers for support in leveraging its capabilities. However, generative AI comes with challenges that might be novel to some developers who have not dealt with the technology before. Free-lancers might be particularly vulnerable to those challenges given that they lack organizational support and depend on positive feedback from their clients. Understanding those challenges and their impact on freelance developers’ work is essential to provide effective guidance for them. We provide an overview of challenges related to developing solutions based on generative AI, as identified in a study with 52 freelance developers. We show that freelancers grapple with aspects they consider unique to generative AI, such as the unpredictability of its output, hallucinations, and the unstable effort related to trial-and-error prompting cycles. Additionally, limitations of specific frameworks such as to-ken limits and long response times, as well as hype-related aspects like inflated client expectations and a rapidly changing technological ecosystem, create further difficulties. We suggest areas where the software engineering community can offer effective guidance for freelancers working with generative AI and other hyped technologies.
Slide Set from the Conference (Development-in-times-of-hype.pdf) | 2.96MiB |
Wed 17 AprDisplayed time zone: Lisbon change
11:00 - 12:30 | Generative AI studiesResearch Track / Software Engineering Education and Training at Luis de Freitas Branco Chair(s): Walid Maalej University of Hamburg | ||
11:00 15mTalk | ChatGPT Incorrectness Detection in Software Reviews Research Track Minaoar Hossain Tanzil University of Calgary, Canada, Junaed Younus Khan University of Calgary, Gias Uddin York University, Canada DOI Pre-print | ||
11:15 15mTalk | ChatGPT-Resistant Screening Instrument for Identifying Non-Programmers Research Track Raphael Serafini Ruhr University Bochum, Clemens Otto Ruhr University Bochum, Stefan Albert Horstmann Ruhr University Bochum, Alena Naiakshina Ruhr University Bochum | ||
11:30 15mTalk | Development in times of hype: How freelancers explore Generative AI? Research Track Mateusz Dolata University of Zurich, Norbert Lange Entschleunigung Lange, Gerhard Schwabe University of Zurich DOI Pre-print File Attached | ||
11:45 15mTalk | How Far Are We? The Triumphs and Trials of Generative AI in Learning Software Engineering Research Track Rudrajit Choudhuri Oregon State University, Dylan Liu Oregon State University, Igor Steinmacher Northern Arizona University, Marco Gerosa Northern Arizona University, Anita Sarma Oregon State University Pre-print | ||
12:00 15mResearch paper | Uncovering the Causes of Emotions in Software Developer Communication Using Zero-shot LLMs Research Track Mia Mohammad Imran Virginia Commonwealth University, Preetha Chatterjee Drexel University, USA, Kostadin Damevski Virginia Commonwealth University Pre-print | ||
12:15 15mTalk | Assessing AI Detectors in Identifying AI-Generated Code: Implications for Education Software Engineering Education and Training Wei Hung Pan School of Information Technology, Monash University Malaysia, Ming Jie Chok School of Information Technology, Monash University Malaysia, Jonathan Leong Shan Wong School of Information Technology, Monash University Malaysia, Yung Xin Shin School of Information Technology, Monash University Malaysia, Yeong Shian Poon School of Information Technology, Monash University Malaysia, Zhou Yang Singapore Management University, Chun Yong Chong Monash University Malaysia, David Lo Singapore Management University, Mei Kuan Lim Monash University Malaysia |