Header

UZH-Logo

Maintenance Infos

Development in times of hype: How freelancers explore Generative AI?


Dolata, Mateusz; Lange, Norbert; Schwabe, Gerhard (2024). Development in times of hype: How freelancers explore Generative AI? In: ICSE '24: IEEE/ACM 46th International Conference on Software Engineering, Lisbon Portugal, 14 April 2024 - 20 April 2024. IEEE/ACM, 1-13.

Abstract

The rise of generative AI has led many companies to hire freelancers to harness its potential. However, this technology presents unique challenges to developers who have not previously engaged with it. Freelancers may find these challenges daunting due to the absence of organizational support and their reliance on positive client feedback. In a study involving 52 freelance developers, we identified multiple challenges associated with developing solutions based on generative AI. Freelancers often struggle with aspects they perceive as unique to generative AI such as unpredictability of its output, the occurrence of hallucinations, and the inconsistent effort required due to trial-and-error prompting cycles. Further, the limitations of specific frameworks, such as token limits and long response times, add to the complexity. Hype-related issues, such as inflated client expectations and a rapidly evolving technological ecosystem, further exacerbate the difficulties. To address these issues, we propose Software Engineering for Generative AI (SE4GenAI) and Hype-Induced Software Engineering (HypeSE) as areas where the software engineering community can provide effective guidance. This support is essential for freelancers working with generative AI and other emerging technologies.

Abstract

The rise of generative AI has led many companies to hire freelancers to harness its potential. However, this technology presents unique challenges to developers who have not previously engaged with it. Freelancers may find these challenges daunting due to the absence of organizational support and their reliance on positive client feedback. In a study involving 52 freelance developers, we identified multiple challenges associated with developing solutions based on generative AI. Freelancers often struggle with aspects they perceive as unique to generative AI such as unpredictability of its output, the occurrence of hallucinations, and the inconsistent effort required due to trial-and-error prompting cycles. Further, the limitations of specific frameworks, such as token limits and long response times, add to the complexity. Hype-related issues, such as inflated client expectations and a rapidly evolving technological ecosystem, further exacerbate the difficulties. To address these issues, we propose Software Engineering for Generative AI (SE4GenAI) and Hype-Induced Software Engineering (HypeSE) as areas where the software engineering community can provide effective guidance. This support is essential for freelancers working with generative AI and other emerging technologies.

Statistics

Citations

Dimensions.ai Metrics

Altmetrics

Downloads

22 downloads since deposited on 22 Apr 2024
22 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Conference or Workshop Item (Paper), not_refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Scopus Subject Areas:Physical Sciences > Software
Uncontrolled Keywords:Generative AI, AI-based Systems, Challenges, Freelancers, Hype, SE for Generative AI, SE4GenAI, Hype-Induced SE, Hype-SE, Fashion, Product, Paradigm, Novelty, Qualitative Research
Language:English
Event End Date:20 April 2024
Deposited On:22 Apr 2024 14:43
Last Modified:23 Apr 2024 20:00
Publisher:IEEE/ACM
Number:183
ISBN:9798400702174
OA Status:Hybrid
Publisher DOI:https://doi.org/10.1145/3597503.3639111
Related URLs:https://osf.io/njc25/ (Research Data)
https://www.computer.org/csdl/proceedings-article/icse/2024/021700a967/1V5Bl1gCGEU (Publisher)
  • Content: Published Version
  • Language: English
  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)
  • Content: Accepted Version
  • Language: English
  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)
  • Content: Supplemental Material
  • Language: English
  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)