Abstract
Tommaso Colombino, Danilo Gallo, Shreepriya Shreepriya, Yesook Im, Seijin Cha |
International Conference on Automated Software Engineering (ASE), virtual event, 15-19 November, 2021 |
Download |
AUTHOR=Colombino Tommaso, Gallo Danilo, Shreepriya Shreepriya, Im Yesook, Cha Seijin TITLE=Ethical Design of a Robot Platform for Disabled Employees: Some Practical Methodological Considerations JOURNAL=Frontiers in Robotics and AI VOLUME=8 YEAR=2021 PAGES=235 URL=https://www.frontiersin.org/article/10.3389/frobt.2021.643160 DOI=10.3389/frobt.2021.643160 ISSN=2296-9144 ABSTRACT=This paper explains the process of developing a scenario involving the use of a robotic platform to enhance the work experience of disabled employees. We outline the challenges involved in revealing the potential unintended consequences of introducing elements of Artificial Intelligence, automation, and robotics into a socially and ethically complex and potentially fragile scenario, and the practical challenges involved in giving a voice to vulnerable users throughout the design process. While an ideal case scenario would involve the disabled employees as much as possible directly in the design process, this can, realistically, be a challenge. In this paper, we detail a methodological and analytic approach that is centered around ethnography and design fictions. It is designed to provide a deeper understanding of all the stakeholders involved in the scenario while encouraging ethical reflection. Based on our findings, we argue that, while it is relatively easy to adopt an a priori ethical stance through notions such as inclusivity and accessibility, there are risks involved in making such a priori prescriptions with respect to the perspectives of different stakeholders in an applied research project. More specifically, we highlight the importance of understanding the broad organizational and bureaucratic characteristics of a business or workplace when devising HRI scenarios and tasks, and of considering elements such as business models, operating philosophy, and organizational hierarchies in the design process. AUTHOR=Colombino Tommaso, Gallo Danilo, Shreepriya Shreepriya, Im Yesook, Cha Seijin TITLE=Ethical Design of a Robot Platform for Disabled Employees: Some Practical Methodological Considerations JOURNAL=Frontiers in Robotics and AI VOLUME=8 YEAR=2021 PAGES=235 URL=https://www.frontiersin.org/article/10.3389/frobt.2021.643160 DOI=10.3389/frobt.2021.643160 ISSN=2296-9144 ABSTRACT=This paper explains the process of developing a scenario involving the use of a robotic platform to enhance the work experience of disabled employees. We outline the challenges involved in revealing the potential unintended consequences of introducing elements of Artificial Intelligence, automation, and robotics into a socially and ethically complex and potentially fragile scenario, and the practical challenges involved in giving a voice to vulnerable users throughout the design process. While an ideal case scenario would involve the disabled employees as much as possible directly in the design process, this can, realistically, be a challenge. In this paper, we detail a methodological and analytic approach that is centered around ethnography and design fictions. It is designed to provide a deeper understanding of all the stakeholders involved in the scenario while encouraging ethical reflection. Based on our findings, we argue that, while it is relatively easy to adopt an a priori ethical stance through notions such as inclusivity and accessibility, there are risks involved in making such a priori prescriptions with respect to the perspectives of different stakeholders in an applied research project. More specifically, we highlight the importance of understanding the broad organizational and bureaucratic characteristics of a business or workplace when devising HRI scenarios and tasks, and of considering elements such as business models, operating philosophy, and organizational hierarchies in the design process. AUTHOR=Colombino Tommaso, Gallo Danilo, Shreepriya Shreepriya, Im Yesook, Cha Seijin TITLE=Ethical Design of a Robot Platform for Disabled Employees: Some Practical Methodological Considerations JOURNAL=Frontiers in Robotics and AI VOLUME=8 YEAR=2021 PAGES=235 URL=https://www.frontiersin.org/article/10.3389/frobt.2021.643160 DOI=10.3389/frobt.2021.643160 ISSN=2296-9144 ABSTRACT=This paper explains the process of developing a scenario involving the use of a robotic platform to enhance the work experience of disabled employees. We outline the challenges involved in revealing the potential unintended consequences of introducing elements of Artificial Intelligence, automation, and robotics into a socially and ethically complex and potentially fragile scenario, and the practical challenges involved in giving a voice to vulnerable users throughout the design process. While an ideal case scenario would involve the disabled employees as much as possible directly in the design process, this can, realistically, be a challenge. In this paper, we detail a methodological and analytic approach that is centered around ethnography and design fictions. It is designed to provide a deeper understanding of all the stakeholders involved in the scenario while encouraging ethical reflection. Based on our findings, we argue that, while it is relatively easy to adopt an a priori ethical stance through notions such as inclusivity and accessibility, there are risks involved in making such a priori prescriptions with respect to the perspectives of different stakeholders in an applied research project. More specifically, we highlight the importance of understanding the broad organizational and bureaucratic characteristics of a business or workplace when devising HRI scenarios and tasks, and of considering elements such as business models, operating philosophy, and organizational hierarchies in the design process. }
Abstract
Simple domain-specific graphical languages and libraries can empower a variety of users to create application behaviors and logic. However, it remains challenging to produce and maintain a heterogeneous set of client applications based on these descriptions, as each client typically requires the developers to both understand and embed the domain-specific logic. This is because application logic must be encoded to some extent in both the server and client sides.
In this paper, we propose an alternative approach, which allows the specification of application logic to reside solely on the cloud. In our system, reusable application components are assembled on the cloud in different logical chains and the client is solely concerned with how data is displayed and gathered from users. In this way, the chaining of requests and responses is done by the cloud and the client side has no knowledge of the application logic. This means that the experts in the domain build modular cloud components, arrange them in logical chains, generate a simple user interface, and later leave it to client-side developers to customize the presentation.
Front. Robot. AI, 19 August 2021 | https://doi.org/10.3389/frobt.2021.643160
NAVER LABS Europe 6-8 chemin de Maupertuis 38240 Meylan France Contact
To make robots autonomous in real-world everyday spaces, they should be able to learn from their interactions within these spaces, how to best execute tasks specified by non-expert users in a safe and reliable way. To do so requires sequential decision-making skills that combine machine learning, adaptive planning and control in uncertain environments as well as solving hard combinatorial optimization problems. Our research combines expertise in reinforcement learning, computer vision, robotic control, sim2real transfer, large multimodal foundation models and neural combinatorial optimization to build AI-based architectures and algorithms to improve robot autonomy and robustness when completing everyday complex tasks in constantly changing environments. More details on our research can be found in the Explore section below.
For a robot to be useful it must be able to represent its knowledge of the world, share what it learns and interact with other agents, in particular humans. Our research combines expertise in human-robot interaction, natural language processing, speech, information retrieval, data management and low code/no code programming to build AI components that will help next-generation robots perform complex real-world tasks. These components will help robots interact safely with humans and their physical environment, other robots and systems, represent and update their world knowledge and share it with the rest of the fleet. More details on our research can be found in the Explore section below.
Visual perception is a necessary part of any intelligent system that is meant to interact with the world. Robots need to perceive the structure, the objects, and people in their environment to better understand the world and perform the tasks they are assigned. Our research combines expertise in visual representation learning, self-supervised learning and human behaviour understanding to build AI components that help robots understand and navigate in their 3D environment, detect and interact with surrounding objects and people and continuously adapt themselves when deployed in new environments. More details on our research can be found in the Explore section below.
Details on the gender equality index score 2024 (related to year 2023) for NAVER France of 87/100.
The NAVER France targets set in 2022 (Indicator n°1: +2 points in 2024 and Indicator n°4: +5 points in 2025) have been achieved.
—————
Index NAVER France de l’égalité professionnelle entre les femmes et les hommes pour l’année 2024 au titre des données 2023 : 87/100
Détail des indicateurs :
Les objectifs de progression de l’Index définis en 2022 (Indicateur n°1 : +2 points en 2024 et Indicateur n°4 : +5 points en 2025) ont été atteints.
Details on the gender equality index score 2024 (related to year 2023) for NAVER France of 87/100.
1. Difference in female/male salary: 34/40 points
2. Difference in salary increases female/male: 35/35 points
3. Salary increases upon return from maternity leave: Non calculable
4. Number of employees in under-represented gender in 10 highest salaries: 5/10 points
The NAVER France targets set in 2022 (Indicator n°1: +2 points in 2024 and Indicator n°4: +5 points in 2025) have been achieved.
——————-
Index NAVER France de l’égalité professionnelle entre les femmes et les hommes pour l’année 2024 au titre des données 2023 : 87/100
Détail des indicateurs :
1. Les écarts de salaire entre les femmes et les hommes: 34 sur 40 points
2. Les écarts des augmentations individuelles entre les femmes et les hommes : 35 sur 35 points
3. Toutes les salariées augmentées revenant de congé maternité : Incalculable
4. Le nombre de salarié du sexe sous-représenté parmi les 10 plus hautes rémunérations : 5 sur 10 points
Les objectifs de progression de l’Index définis en 2022 (Indicateur n°1 : +2 points en 2024 et Indicateur n°4 : +5 points en 2025) ont été atteints.
To make robots autonomous in real-world everyday spaces, they should be able to learn from their interactions within these spaces, how to best execute tasks specified by non-expert users in a safe and reliable way. To do so requires sequential decision-making skills that combine machine learning, adaptive planning and control in uncertain environments as well as solving hard combinatorial optimisation problems. Our research combines expertise in reinforcement learning, computer vision, robotic control, sim2real transfer, large multimodal foundation models and neural combinatorial optimisation to build AI-based architectures and algorithms to improve robot autonomy and robustness when completing everyday complex tasks in constantly changing environments.
The research we conduct on expressive visual representations is applicable to visual search, object detection, image classification and the automatic extraction of 3D human poses and shapes that can be used for human behavior understanding and prediction, human-robot interaction or even avatar animation. We also extract 3D information from images that can be used for intelligent robot navigation, augmented reality and the 3D reconstruction of objects, buildings or even entire cities.
Our work covers the spectrum from unsupervised to supervised approaches, and from very deep architectures to very compact ones. We’re excited about the promise of big data to bring big performance gains to our algorithms but also passionate about the challenge of working in data-scarce and low-power scenarios.
Furthermore, we believe that a modern computer vision system needs to be able to continuously adapt itself to its environment and to improve itself via lifelong learning. Our driving goal is to use our research to deliver embodied intelligence to our users in robotics, autonomous driving, via phone cameras and any other visual means to reach people wherever they may be.
This web site uses cookies for the site search, to display videos and for aggregate site analytics.
Learn more about these cookies in our privacy notice.
You may choose which kind of cookies you allow when visiting this website. Click on "Save cookie settings" to apply your choice.
FunctionalThis website uses functional cookies which are required for the search function to work and to apply for jobs and internships.
AnalyticalOur website uses analytical cookies to make it possible to analyse our website and optimize its usability.
Social mediaOur website places social media cookies to show YouTube and Vimeo videos. Cookies placed by these sites may track your personal data.
This content is currently blocked. To view the content please either 'Accept social media cookies' or 'Accept all cookies'.
For more information on cookies see our privacy notice.