posted by organizer: AngeloTrottaUnibo85 || 6038 views || tracked by 12 users: [display]

AI for People 2021 : Special Issue on AI for People - AI & SOCIETY (Springer)


When N/A
Where N/A
Abstract Registration Due Mar 15, 2021
Submission Deadline Apr 30, 2021
Notification Due Jul 30, 2021
Final Version Due Nov 30, 2021
Categories    artificial intelligence   computer science   humanities   social sciences

Call For Papers

Springer AI & SOCIETY - Special issue on AI for People

- Abstract submission (extended): March 15, 2021
- Manuscript submission: April 30, 2021

We invite contributions to a Special Issue on AI for People, to be published by the AI & Society - Journal of Culture, Knowledge and Communication (Springer)​

This Special Issue was born out of the idea of shaping Artificial Intelligence technology around human and societal needs. We believe that technology should respect the anthropocentric principle. It should be at the service of the people, not vice-versa. In order to foster this idea, we need to narrow the gap between civil society and technical experts. This gap is one in knowledge, in action and in tools for change.

The ‘social good’ is something which benefits the general public, being ‘for’ the people, and at the same time, it is something which reflects and respects their wishes, being ‘from’ the people. The ‘social good’ can be envisioned as global citizens uniting to unlock the potential of individuals through collaboration to create a positive societal impact. It is about engagement, shareability and bringing people together to change the world for the better. Concurrently, Artificial Intelligence (AI) research is mature enough for stable algorithms and approaches to be used and play a crucial role in the aforementioned ‘social good’, enabling the deployment of revolutionary services and applications. It is envisioned that both the social interaction and the integration with smart devices will meaningfully impact societal development and sustainability.
Nowadays, advances in research on AI systems have yielded a far-reaching discourse about the applicability of the AI Ethics principles when designing, developing, integrating or using AI systems. AI Ethical principles are guidelines put forward by policy makers that can act as abstractions, as normative constraints on the do’s and don’ts of algorithmic use in society. Themes of transparency, justice, and fairness, non-maleficence, responsibility and privacy must be taken into account when deploying real-world AI systems.

This Special Issue will focus on the following AI Ethics principles:
1. Accuracy and Robustness: algorithmic conclusions are probabilities and therefore not infallible and they also might incur in errors during execution. This can lead to unjustified actions.
2. Explainability and Transparency: a lack of interpretability and transparency can lead to algorithmic systems that are hard to control, monitor, and correct. This is the commonly called ‘black-box’ issue.
3. Bias and Fairness: conclusions can only be as reliable (but also as neutral) as the data they are based on, and this can lead to bias. An action could be found to be discriminatory if it has a disproportionate impact on one group of people.
4. Privacy: algorithmic activities, like profiling, can lead to challenges for autonomy and informational privacy.
5. Accountability: it is hard to assign responsibility to algorithmic harms and this can lead to issues with moral responsibility.
6. Safety and Security: AI systems need to respect and support privacy rights and data protection while ensuring the security of data.

The aim of this Special Issue is, however broad, mostly twofold. On one hand, it entails the technical realization of these AI Ethics principles (one or more) in practice. For example, this might refer to specific techniques to ensure principles like ‘fairness’ in an algorithm, with their related practical challenges. On the other hand, it entails addressing these principles from a conceptual standpoint. For example, this might entail, among other things, theorizing, analysing, criticizing and/or further developing the AI principles themselves. Contributions are welcomed from a host of different disciplines, spanning from the sciences, the social sciences and the humanities.

We welcome contributions across the following formats:
- Original​ papers (max 10k words): substantial contribution, theory, method, application. Contributions may be experimental, based on case studies, or conceptual discussions of how AI systems affect organisations, society and humans. Original papers will be double blind peer-reviewed by two reviewers and the editorial team.
- Network Research papers (max 10k words): substantial contributions to theoretical and methodological foundations within societal domains. These will be multi-authored papers that include a summary of the contribution of each author to the paper. Network Research papers will be double blind peer-reviewed by two reviewers and the editorial team.
- Open Forum​ papers (max 8k words): research in progress, ideas paper. Contributions may come from researchers, practitioners and others interested in the topics of the special issue. Contributions might be, but not limited to, discussion papers, literature reviews, case studies, working papers, features, and articles on emerging research. Papers published in the open forum target a broad audience i.e. academics, designers as well as the average reader. Open Forum contributions will be double blind peer-reviewed by two reviewers and the editorial team.
- Student​ papers (max 6k words): research in progress. Contributions may come from post-graduate students and Ph.D. students interested in the topics of the special issue. For articles that are based primarily on the student’s dissertation or thesis, it is recommended that the student is usually listed as principal author. Papers are double blind peer-reviewed by one reviewer and the editorial team.
- Curmudgeon​ papers (max 1k words): short opinionated column on trends in technology, science and society, commenting on issues of concern to the research community and wider society. Whilst the drive for artificial intelligence promotes potential benefits to wider society, it also raises deep concerns of existential risk, thereby highlighting the need for an ongoing conversation between technology and society. At the core of Curmudgeon concern is the question: What are the political-philosophical concepts regarding the present sphere of AI technology? Curmudgeon articles will be reviewed by the Journal editors.

A Best Paper Award is sponsored by the nonprofit association 'AI for People' ( with a cash prize of 200 Euro.

- Abstract submission (extended): July 12, 2021
- Manuscript submission (extended): July 30, 2021
- Notifications: October 30, 2021
- Submission final versions: December 30, 2021

You can find more information about formatting under the section "Submission guidelines" ​

- Angelo Trotta, Department of Computer Science and Engineering, University of Bologna, Italy
- Vincenzo Lomonaco, Department of Computer Science and Engineering, University of Bologna, Italy
- Marta Ziosi, Oxford Internet Institute, University of Oxford, UK

Related Resources

Computer SI on SE4RAI 2023   IEEE Computer - Special Issue on Software Engineering for Responsible AI
IJCAI 2022   31st International Joint Conference on Artificial Intelligence
ICADCML 2022   3rd International Conference on Advances in Distributed Computing and Machine Learning - 2022
ACM--ICMLT--Ei and Scopus 2022   ACM--2022 7th International Conference on Machine Learning Technologies (ICMLT 2022)--Ei Compendex, Scopus
EvoCompAISecurity&Privacy 2022   Evolutionary Computing for AI-Driven Security and Privacy: Advancing the state-of-the-art applications
ACM-EI/Scopus-ITCC 2022   2022 2nd International Conference on Information Technology and Cloud Computing (ITCC 2022)
NLCAI 2022   3rd International Conference on Natural Language Computing and AI
CiViE 2022   6th International Conference On Civil Engineering
ICPR 2022   26th International Conference on Pattern Recognition
SIMPAT SI: Blockchain-AI-IoT 2022   SIMPAT (IF: 3.272) Elsevier - Special Issue on Leveraging blockchain and AI for IoT, mist, fog and cloud computing: a performance modeling and simulation perspective