Publication Type

Journal Article

Version

publishedVersion

Publication Date

10-2024

Abstract

The advent of Generative Artificial Intelligence—systems that can produce human-like content such as text, music, visual art, or source code—marks not only a significant leap for Artificial Intelligence (AI) but also a pivotal moment for software practitioners and researchers. The role of software engineering researchers and practitioners in adopting the technologies that shape our world is critical. Historically, the human aspects of developing software have been treated as secondary to more technical innovations. However, the emergence of Generative AI will simultaneously enhance human capabilities while surfacing complex ethical, social, legal, and technical challenges.While primarily aimed at software engineering (SE) researchers and practitioners, who are at the forefront of integrating Generative AI into our digital infrastructure, this manifesto equally underscores the ripple effects such innovations have on end-users of software, shaping their experiences and interactions in profound ways.SE practitioners and researchers have a moral duty to help the world navigate this enduring landscape of new AI technologies ethically and sustainably, and foster values such as fairness, transparency, societal wellbeing, and environmental resilience. This transformative era challenges us to extend our focus beyond technical expertise, integrating human values and ethical considerations into the fabric of our technological advancements This is in addition to maintaining our existing obligations, such as adherence to codes of conduct (e.g., ACM Code of Ethics and Professional Conduct or the IEEE Code of Ethics) and compliance with legal frameworks (e.g., EU AI Act).By establishing this manifesto, we seek to catalyze a shift in how Generative AI is conceived, developed, and applied within SE—a shift that reaffirms the primacy of human dignity, agency, and collective wellbeing in the face of rapid technological change.

Discipline

Artificial Intelligence and Robotics | Software Engineering

Research Areas

Software and Cyber-Physical Systems

Areas of Excellence

Digital transformation

Publication

Journal of Systems and Software

Volume

216

First Page

1

Last Page

2

ISSN

0164-1212

Identifier

10.1016/j.jss.2024.112115

Publisher

Elsevier

Copyright Owner and License

Publisher

Creative Commons License

Creative Commons Attribution 3.0 License
This work is licensed under a Creative Commons Attribution 3.0 License.

Comments

Full list of authors: Daniel Russo, Sebastian Baltes, Niels van Berkel, Paris Avgeriou, Fabio Calefato, Beatriz Cabrero-Daniel, Gemma Catolino, Jürgen Cito, Neil Ernst, Thomas Fritz, Hideaki Hata, Reid Holmes, Maliheh Izadi, Foutse Khomh, Mikkel Baun Kjærgaard, Grischa Liebel, Alberto Lluch Lafuente, Stefano Lambiase, Walid Maalej, Gail Murphy, Nils Brede Moe, Gabrielle O'Brien, Elda Paja, Mauro Pezzè, John Stouby Persson, Rafael Prikladnicki, Paul Ralph, Martin Robillard, Thiago Rocha Silva, Klaas-Jan Stol, Margaret-Anne Storey, Viktoria Stray, Paolo Tell, Christoph Treude, Bogdan Vasilescu

Additional URL

https://doi.org/10.1016/j.jss.2024.112115

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