Recently a great deal of attention has focused on quantum computation following a sequence of results [4,16,15] suggesting that quantum computers are more powerful than classical probabilistic computers. Following Shor's result that factoring and the extraction of discrete logarithms are both solvable in quantum polynomial time, it is natural to ask whether all of NP can be efficiently solved in quantum polynomial time. In this paper, we address this question by proving that relative to an oracle chosen uniformly at random, with probability 1, the class NP cannot be solved on a quantum Turing machine in time o(2 n/2 ). We also show that relative to a permutation oracle chosen uniformly at random, with probability 1, the class NP ∩ co-NP cannot be solved on a quantum Turing machine in time o(2 n/3 ). The former bound is tight since recent work of Grover [13] shows how to accept the class NP relative to any oracle on a quantum computer in time O(2 n/2 ).
Organizations’ pursuit of increased workplace collaboration has led managers to transform traditional office spaces into ‘open’, transparency-enhancing architectures with fewer walls, doors and other spatial boundaries, yet there is scant direct empirical research on how human interaction patterns change as a result of these architectural changes. In two intervention-based field studies of corporate headquarters transitioning to more open office spaces, we empirically examined—using digital data from advanced wearable devices and from electronic communication servers—the effect of open office architectures on employees' face-to-face, email and instant messaging (IM) interaction patterns. Contrary to common belief, the volume of face-to-face interaction decreased significantly (approx. 70%) in both cases, with an associated increase in electronic interaction. In short, rather than prompting increasingly vibrant face-to-face collaboration, open architecture appeared to trigger a natural human response to socially withdraw from officemates and interact instead over email and IM. This is the first study to empirically measure both face-to-face and electronic interaction before and after the adoption of open office architecture. The results inform our understanding of the impact on human behaviour of workspaces that trend towards fewer spatial boundaries.This article is part of the theme issue ‘Interdisciplinary approaches for uncovering the impacts of architecture on collective behaviour’.
Observation is key to management scholarship and practice. Yet a holistic view of its role in management has been elusive, in part due to shifting terminology. The current popularity of the term "transparency" provides the occasion for a thorough review, which finds (a) a shift in the object of observation from organizational outcomes to the detailed individual activities within them; (b) a shift from people observing the technology to technology observing people; and (c) a split in the field, with managers viewing observation almost entirely from the observer's perspective, leaving the perspective of the observed to the realm of scholarly methodology courses and philosophical debates on privacy. I suggest how the literature on transparency and related literatures might be improved with research designed in light of these trends.KEYWORDS: transparency, privacy, performance, organizations, management theory ACKNOWLEDGEMENTS: I thank Julie Battilana, Ethan Burris, Tim Earle, Amy Edmondson, John Elder, Elizabeth Hansen, Rosabeth Moss Kanter, Joshua Margolis, Tsedal Neeley, Nitin Nohria, Shefali Patil, Kathy Qu, Ryan Raffaelli, Lakshmi Ramarajan, and Bradley Staats for feedback on prior versions of this work; Jim Detert, Sim Sitkin, and two anonymous reviewers for insightful and developmental feedback; and the Harvard Business School for financial support.Please cite as: Bernstein, E. S. Making transparency transparent: The evolution of observation in management theory. Academy of Management Annals, 11(1): 217-266. 2We are increasingly observed and observing at work. Fifty years ago, a typical manager might have tracked production, revenue, and expenses against budget and periodically observed workers during in-person audits (e.g., Dalton, 1959). Today, advances in technology, from smart cameras to wearable tracking devices, make possible a kind of real-time "SuperVision" (Gilliom & Monahan, 2012) far beyond any level of observability envisioned 50 years ago or when Frederick Taylor (1911) originally promoted managerial oversight through scientific management.Public attention is captured by extreme examples of observation at work, like handheld computers (Amazon) or wearable bands (Tesco) tracking and optimizing employees' every move (Head, 2014;Kantor & Streitfeld, 2015;Rawlinson, 2013), embedded sensors in large fleets of company-owned trucks (e.g., UPS) recording hundreds of measurements to capture every action of the truck and its driver to unearth and enforce time-saving tactics (Goldstein, 2014;Levy, 2015), cameras at Las Vegas casino Harrah's tracking the smiles of card dealers and wait staff as a proxy for customer service quality (Peck, 2013), point-of-sale systems scraping every transaction for signs of employee fraud (Pierce, Snow, & McAfee, 2015), and RFID (radiofrequency identification)-enabled workspaces automatically capturing factory worker progress (Ranganathan, 2015), how long employees spend at their desks (Zillman, 2016), and even who does and does not use hand-soap and hand-sanitizer dispensers ...
SignificanceMany human endeavors—from teams and organizations to crowds and democracies—rely on solving problems collectively. Prior research has shown that when people interact and influence each other while solving complex problems, the average problem-solving performance of the group increases, but the best solution of the group actually decreases in quality. We find that when such influence is intermittent it improves the average while maintaining a high maximum performance. We also show that storing solutions for quick recall is similar to constant social influence. Instead of supporting more transparency, the results imply that technologies and organizations should be redesigned to intermittently isolate people from each other’s work for best collective performance in solving complex problems.
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