Employers are adopting algorithmic hiring technology throughout the recruitment pipeline. Algorithmic fairness is especially applicable in this domain due to its high stakes and structural inequalities. Unfortunately, most work in this space provides partial treatment, often constrained by two competing narratives, optimistically focused on replacing biased recruiter decisions or pessimistically pointing to the automation of discrimination. Whether, and more importantly what types of , algorithmic hiring can be less biased and more beneficial to society than low-tech alternatives currently remains unanswered, to the detriment of trustworthiness. This multidisciplinary survey caters to practitioners and researchers with a balanced and integrated coverage of systems, biases, measures, mitigation strategies, datasets, and legal aspects of algorithmic hiring and fairness. Our work supports a contextualized understanding and governance of this technology by highlighting current opportunities and limitations, providing recommendations for future work to ensure shared benefits for all stakeholders.

Understanding what constitutes children’s well-being in digital environments is fundamental for designing technology that supports children’s development while minimizing emerging risks. This is even more urgent with the rapid advances in Artificial Intelligence and the radical transformations in children’s everyday activities, play, and learning. With this workshop, we aim to co-create an agenda for future actions by mapping the current state-of-the-art research about children’s well-being, identifying policy initiatives and relevant stakeholders that come into play, and reflecting on existing good practices and proposing new ones for digital technology that promotes children’s well-being with a special focus on children from under-represented groups.

Following the success of the first edition of Robo-Identity, the second edition will provide an opportunity to expand the discussion about artificial identity. This year, we are focusing on emotions that are expressed through speech and voice. Synthetic voices of robots can resemble and are becoming indistinguishable from expressive human voices. This can be an opportunity and a constraint in expressing emotional speech that can (falsely) convey a human-like identity that can mislead people, leading to ethical issues. How should we envision an agent's artificial identity? In what ways should we have robots that maintain a machine-like stance, e.g., through robotic speech, and should emotional expressions that are increasingly human-like be seen as design opportunities? These are not mutually exclusive concerns. As this discussion needs to be conducted in a multidisciplinary manner, we welcome perspectives on challenges and opportunities from variety of fields. For this year's edition, the special theme will be “speech, emotion and artificial identity”.