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1. Building for ‘We’: Safety Settings for Couples with Memory Concerns

   https://doi.org/10.1145/3411764.3445071  

   McDonald, Nora; Mentis, Helena M. (January 2021, Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems)

   null (Ed.)

   Designing technologies that support the mutual cybersecurity and autonomy of older adults facing cognitive challenges requires close collaboration of partners. As part of research to design a Safety Setting application for older adults with memory loss or mild cognitive impairment (MCI), we use a scenario-based participatory design. Our study builds on previous findings that couples’ approach to memory loss was characterized by a desire for flexibility and choice, and an embrace of role uncertainty. We find that couples don't want a system that fundamentally alters their relationship and are looking to maximize self-surveillance competence and minimize loss of autonomy for their partners. All desire Safety Settings to maintain their mutual safety rather than designating one partner as the target of oversight. Couples are open to more rigorous surveillance if they have control over what types of activities trigger various levels of oversight. 

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2. “Citizens Too”: Safety Setting Collaboration Among Older Adults with Memory Concerns

   https://doi.org/10.1145/3465217  

   Mcdonald, Nora; Mentis, Helena M. (October 2021, ACM Transactions on Computer-Human Interaction)

   null (Ed.)

   Designing technologies that support the cybersecurity of older adults with memory concerns involves wrestling with an uncomfortable paradox between surveillance and independence and the close collaboration of couples. This research captures the interactions between older adult couples where one or both have memory concerns—a primary feature of cognitive decline—as they make decisions on how to safeguard their online activities using a Safety Setting probe we designed, and over the course of several informal interviews and a diary study. Throughout, couples demonstrated a collaborative mentality to which we apply a frame of citizenship in opensource collaboration, specifically (a) histories of participation , (b) lower barriers to participation, and (c) maintaining ongoing contribution. In this metaphor of collaborative enterprise, one partner (or member of the couple) may be the service provider and the other may be the participant, but at varying moments, they may switch roles while still maintaining a collaborative focus on preserving shared assets and freedom on the internet. We conclude with a discussion of what this service provider-contributor mentality means for empowerment through citizenship, and implications for vulnerable populations’ cybersecurity. 

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3. A Barrier Pair Method for Safe Human-Robot Shared Autonomy

   He, Binghan; Ghasemi, Mahsa; Topcu, Ufuk; and Sentis, Luis (January 2021, IEEE Conference on Decision and Control)

   null (Ed.)

   Shared autonomy provides a framework where a human and an automated system, such as a robot, jointly control the system’s behavior, enabling an effective solution for various applications, including human-robot interaction and remote operation of a semi-autonomous system. However, a challenging problem in shared autonomy is safety because the human input may be unknown and unpredictable, which affects the robot’s safety constraints. If the human input is a force applied through physical contact with the robot, it also alters the robot’s behavior to maintain safety. We address the safety issue of shared autonomy in real-time applications by proposing a two-layer control framework. In the first layer, we use the history of human input measurements to infer what the human wants the robot to do and define the robot’s safety constraints according to that inference. In the second layer, we formulate a rapidly-exploring random tree of barrier pairs, with each barrier pair composed of a barrier function and a controller. Using the controllers in these barrier pairs, the robot is able to maintain its safe operation under the intervention from the human input. This proposed control framework allows the robot to assist the human while preventing them from encountering safety issues. We demonstrate the proposed control framework on a simulation of a two-linkage manipulator robot. 

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4. Evaluating the Impact of Enrichment and Professional Development Activities on REU Students

   1. Nepal, B. (July 2022, 2022 ASEE Annual Conference & Exposition)

   Research Experience for Undergraduates (REU) programs have been credited for attracting and retaining students in science and engineering who otherwise may not have considered disciplines in science and engineering as their career choices. In addition to core research activities, REU programs generally provide multiple enrichment and professional development activities for participants. While the nature and the number of professional development activities vary from one REU program to another, the most common activities include ethics and safety training, research and industry seminars, GRE workshops, writing workshops, graduate school application preparation, and industry visits. Furthermore, some of these professional development activities are also conducted in large group settings with students from other research programs beyond the REU cohort. The rationale behind combining REU students with other researchers is to create a community of learners and provide them with an opportunity to build/extend their professional network. Although professional development activities are an integral part of the REU sites, there is often very limited coverage of such activities in the existing literature on REU projects. This paper presents the impact of professional development activities on the experience of REU participants in a manufacturing REU site at a major research university in the southwestern United States. For this study, data was collected from participants by an external evaluator by using both qualitative and quantitative methods. This paper presents and describes the cumulative data from three REU cohorts. The analysis and results of the data are disaggregated by the student academic level (sophomore, junior, senior), gender, ethnicity, the type of their home institutions (research or teaching institution), and desired career paths in the future (graduate school or industry). The paper also provides a detailed discussion and implications of these findings. 

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5. Situational Confidence Assistance for Lifelong Shared Autonomy

   https://doi.org/10.1109/ICRA48506.2021.9561839  

   Zurek, Matthew; Bobu, Andreea; Brown, Daniel; Dragan, Anca (April 2021, International Conference on Robotics and Automation)

   Shared autonomy enables robots to infer user intent and assist in accomplishing it. But when the user wants to do a new task that the robot does not know about, shared autonomy will hinder their performance by attempting to assist them with something that is not their intent. Our key idea is that the robot can detect when its repertoire of intents is insufficient to explain the user’s input, and give them back control. This then enables the robot to observe unhindered task execution, learn the new intent behind it, and add it to this repertoire. We demonstrate with both a case study and a user study that our proposed method maintains good performance when the human’s intent is in the robot’s repertoire, outperforms prior shared autonomy approaches when it isn’t, and successfully learns new skills, enabling efficient lifelong learning for confidence-based shared autonomy. 

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