Artificial Intelligence (AI) and Quantum Computing (QC) are at the forefront of technological advancement. Consequently, both technologies attract significant research and development investments as they promise to revolutionize numerous industries (e.g., finance, drug discovery, and simulations) with their transformative capabilities. However, this convergence also brings about distinct ethical challenges that must be addressed proactively to ensure these technologies' responsible development and implementation. To this end, this Shonan seminar will study these issues individually for each of these technologies, namely, AI and QC. It will then discuss how the interactions between these technologies raise novel ethical issues that require the software engineering community's attention.

We aim to run the seminar in three parts:

In the first part of the seminar, we will focus on AI. Diversity and inclusion (D&I) in AI involving diverse human attributes in the AI ecosystem's data, processes, systems, and governance [1]. Integrating diverse perspectives in development helps engineers design AI systems that understand and meet varied user needs, promoting equitable outcomes. [2, 3] This approach mitigates algorithmic biases and enhances fairness, transparency, and accountability [1, 4, 5]. This part will discuss various aspects, such as data representation, algorithmic fairness, and inclusive system design. Specifically, we will explore how diverse datasets can minimize representational biases, the role of fairness metrics in evaluating AI models, and the importance of interdisciplinary teams in developing equitable AI solutions. Practical strategies for promoting diversity in AI governance and regulatory frameworks will also be highlighted to ensure these systems align with ethical principles and societal values.

As quantum computers grow more powerful, studying their impact on ethics and D&I becomes essential. As a result, it's reasonable to investigate the ethical implications of quantum software running on quantum computers compared to those of classical software or AI. To understand the necessity of ethics in QSE, we must consider the following research questions: 1) Are the ethical challenges of QSE and the quantum software that enables the QC applications distinct enough from classical software to warrant a separate discussion? 2) Can ethical frameworks for other technologies, such as AI, be adapted or tailored for QSE?

Quantum software works quite differently from classical software due to the unique characteristics of QC, such as its inherently probabilistic nature, superposition, and entanglement. These qualities significantly shape how we think about ethics in technical implementation, influencing areas like algorithmic governance, transparency, cryptography, and representational justice. We will discuss these issues in this part of the seminar.

Building on the D&I aspects discussed individually for each technology, we will explore how their interactions present novel challenges concerning D&I. We will examine various aspects, such as the effects of their interactions on ethics, diversity, inclusion, and equity. Moreover, we will consider issues such as the immense power of these two technologies, which could lead to a power imbalance that would require governance and policy mechanisms. In addition, we will discuss how ethical standards across these two technologies can be coordinated to avoid developing non-standardized frameworks by engaging various stakeholders.

Based on the discussion in the seminar, we aim to write a book about diversity and inclusion in emergent technologies. The participants in this seminar will contribute to various chapters. Based on the three parts of the seminar, the book will be organized into three sections, each with various chapters. Each chapter will discuss key ideas, various issues, current solutions, possible tailoring of solutions to QC, interactions between QC and AI, and open research questions. As a result, a comprehensive research agenda related to QC and the interaction of QC and AI will be formed, which currently does not exist.

Given the interdisciplinary nature of this seminar, we will invite researchers and possibly practitioners from different fields, such as social scientists, software engineers, AI experts, QC experts (e.g., physicists), and philosophers.

The seminar will be conducted in various formats. It will kick off with a welcome meeting, during which each participant will introduce themselves and share their specific interests in different topics related to the seminar. Next, groups will be formed to discuss topics in detail, resulting in the book's outline. There will be combined sessions where different groups will summarize their discussions for all participants. In addition to the book, we anticipate other concrete outputs such as publications, new research cooperation, and projects.

[1] Zowghi, D. and F. da Rimini, Diversity and inclusion in artificial intelligence. arXiv preprint arXiv:2305.12728, 2023.
[2] Bano, M., D. Zowghi, and V. Gervasi. A Vision for Operationalising Diversity and Inclusion in AI. in Proceedings of the 2nd International Workshop on Responsible AI Engineering. 2024.
[3] Bano, M., et al., AI for All: Operationalising Diversity and Inclusion Requirements for AI Systems. arXiv preprint arXiv:2311.14695, 2023.
[4] Nyariro, M., E. Emami, and S. Abbasgholizadeh Rahimi. Integrating Equity, Diversity, and Inclusion throughout the lifecycle of Artificial Intelligence in health. in 13th Augmented Human International Conference. 2022.
[5] Shams, R.A., Zowghi, D. & Bano, M. AI and the quest for diversity and inclusion: a systematic literature review. AI Ethics (2023). https://doi.org/10.1007/s43681-023-00362-w