No Arabic abstract
Quantum information science and technology (QIST) has progressed significantly in the last decade, such that it is no longer solely in the domain of research labs, but is now beginning to be developed for, and applied in, industrial applications and products. With the emergence of this new quantum industry, a new workforce trained in QIST skills and knowledge is needed. To help support education and training of this workforce, universities and colleges require knowledge of the type of jobs available for their students and what skills and degrees are most relevant for those new jobs. Additionally, students need to know how to tailor their degrees to best align with the current needs of the quantum industry. We report on the results from a survey of 57 companies in the quantum industry, with the goal of elucidating the jobs, skills, and degrees that are relevant for this new workforce. We find a range of job opportunities from highly specific jobs, such as quantum algorithm developer and error correction scientist, to broader jobs categories within the business, software, and hardware sectors. These broader jobs require a range of skills, most of which are not quantum related. Further, except for the highly specific jobs, companies that responded to the survey are looking for a range of degree levels to fill these new positions, from bachelors to masters to PhDs. With this knowledge, students, instructors, and university administrators can make informed decisions about how to address the challenge of increasing the future quantum workforce.
Quantum sensing, quantum networking and communication, and quantum computing have attracted significant attention recently, as these quantum technologies offer significant advantages over existing technologies. In order to accelerate the commercialization of these quantum technologies the workforce must be equipped with the necessary skills. Through a qualitative study of the quantum industry, in a series of interviews with 21 U.S. companies carried out in Fall 2019, we describe the types of activities being carried out in the quantum industry, profile the types of jobs that exist, and describe the skills valued across the quantum industry, as well as in each type of job. The current routes into the quantum industry are detailed, providing a picture of the current role of higher education in training the quantum workforce. Finally, we present the training and hiring challenges the quantum industry is facing and how higher education may optimize the important role it is currently playing.
The IBM-HBCU Quantum Center is a first-of-a-kind collaboration between IBM and a consortium of Historically Black Colleges and Universities (HBCUs) that seeks to address the lack of Black representation and build a diverse and aware workforce in quantum information science and engineering (QISE). Key pillars of the Center are focused on 1) building community and fostering a sense of belonging, 2) strengthening relationships internally and with the broader quantum community, and 3) providing funding to support undergraduate, graduate, and faculty research at HBCUs. As a part of the program, students and faculty are invited to participate in grant development workshops, a QISE invited speaker series, community hack-a-thons, and other opportunities to build competencies in the growing field of QISE. Since its launch, the IBM-HBCU Quantum Center has engaged a community of over 400 students, faculty, and researchers and will continue to establish a research presence in QISE and increase opportunities for research and workforce development.
The International Astronomical Youth Camp has benefited thousands of lives during its 50-year history. We explore the pedagogy behind this success, review a survey taken by more than 300 previous participants, and discuss some of the challenges the camp faces in the future.
Quantum based technologies have been fundamental in our world. After producing the laser and the transistor, the devices that have shaped our modern information society, the possibilities enabled by the ability to create and manipulate individual quantum states opens the door to a second quantum revolution. In this paper we explore the possibilities that these new technologies bring to the Telecommu-nications industry
As the use of machine learning (ML) models in product development and data-driven decision-making processes became pervasive in many domains, peoples focus on building a well-performing model has increasingly shifted to understanding how their model works. While scholarly interest in model interpretability has grown rapidly in research communities like HCI, ML, and beyond, little is known about how practitioners perceive and aim to provide interpretability in the context of their existing workflows. This lack of understanding of interpretability as practiced may prevent interpretability research from addressing important needs, or lead to unrealistic solutions. To bridge this gap, we conducted 22 semi-structured interviews with industry practitioners to understand how they conceive of and design for interpretability while they plan, build, and use their models. Based on a qualitative analysis of our results, we differentiate interpretability roles, processes, goals and strategies as they exist within organizations making heavy use of ML models. The characterization of interpretability work that emerges from our analysis suggests that model interpretability frequently involves cooperation and mental model comparison between people in different roles, often aimed at building trust not only between people and models but also between people within the organization. We present implications for design that discuss gaps between the interpretability challenges that practitioners face in their practice and approaches proposed in the literature, highlighting possible research directions that can better address real-world needs.