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![ ](./photos/alessandra.png width="210px" align=left) [Alessandra Rossi](https://www.alessandrarossi.net/) is Assistant Professor at the University of Naples “Federico II”, Italy. Her PhD thesis was part of the Marie Sklodowska-Curie Research ETN SECURE project at the University of Hertfordshire (UK). She is also a Visiting Lecturer at University of Hertfordshire. Her research interests include Human–(Multi) Robot Interaction, social robotics, trust, XAI, multi-agent systems and user profiling. Alessandra is Project Manager of Marie Sklodowska-Curie Research ETN PERSEO. Alessandra is Special Session chair of IEEE RO-MAN 2024. She has been Publicity chair of IEEE RO-MAN 2022 and 2023, Virtual Organizing Chair of IEEE RO-MAN 2021, Registration Chair and Social Media Responsible for IEEE RO-MAN 2020. Alessandra has great experience in organising scientific events as main organiser and in collaboration with her peers, some examples are the workshops SCRITA at RO-MAN 2018-2023, workshop TRAITS at HRI 2021 and 2022, special sessions at RO-MAN 2019-2023, special issues at international journals (e.g., International Journal of Social Robotics, and Paladyn Journal of Behavioral Robotics). **Title:** To trust a robot: factors and development of people's perception of a robot. **Abstract:** There is a common agreement that trust is a fundamental factor for a successful cooperation between people and robots. Nevertheless, trust is a very complex feeling even between humans, and it can be fostered and enhanced according different factors, including those related to the interacting agents (e.g. humans, robots, pets), itself (e.g. capabilities, reliability), the context (e.g. task), and the environment (e.g. public spaces vs private spaces vs working spaces). In general, most roboticists agree that insufficient levels of trust lead to a risk of disengagement while over-trust in technology can cause over-reliance and inherit dangers, for example, in emergency situations. In this talk, I am going to provide an overview on the main factors affecting people's trust in the robot, and initial investigation for mitigating negative effects on people and robot interactions when there has been a breach of trust.