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  • What About an Unintelligent Singularity?: The technological singularity (Ubiquity symposium)

    For years we humans have worried about plagues, asteroids, earthquakes, eruptions, fires, floods, famines, wars, genocides, and other uncontrollable events that could wipe away our civilization. In the modern age, with so much depending on computing and communications, we have added computers to our list of potential threats. Could we perish from the increasing intelligence of computers? Denning thinks that is less of a threat than the apparently mundane march of automated bureaucracies. He also asserts that none of the possible negative outcomes is a forgone conclusion because humans teaming with machines are far more intelligent than either one alone.

  • Computers versus Humanity: Do we compete?: The technological singularity (Ubiquity symposium)

    Liah Greenfeld and Mark Simes have long worked together, integrating the perspectives of two very different disciplinary traditions: cultural history/historical sociology and human neuroscience. The combination of their areas of expertise in the empirical investigation of mental disorders, which severely affect intelligence---among other things---has led them to certain conclusions that may throw a special light on the question of this symposium: Will computers outcompete us all?

  • Exponential Technology and The Singularity: The technological singularity (Ubiquity symposium)

    The Priesthood of the Singularity posits a fast approaching prospect of machines overtaking human abilities (Ray Kurzweil's The Singularity is Near, Viking Press, 2006) on the basis of the exponential rate of electronic integration---memory and processing power. In fact, they directly correlate the growth of computing technology with that of machine intelligence as if the two were connected in some simple-to-understand and predictable way. Here we present a different view based upon the fundamentals of intelligence and a more likely relationship. We conclude that machine intelligence is growing in a logarithmic (or at best linear fashion) rather than the assumed exponential rate.

  • Human Enhancement--The way ahead: The technological singularity (Ubiquity symposium)

    In this paper a look is taken at artificial intelligence and the ways it can be brought about, either by means of a computer or through biological growth. Ways of linking the two methods are also discussed, particularly the possibilities of linking human and artificial brains together. In this regard practical experiments are referred to in which human enhancement can be achieved though linking with artificial intelligence.

  • The Singularity and the State of the Art in Artificial Intelligence: The technological singularity (Ubiquity symposium)

    The state of the art in automating basic cognitive tasks, including vision and natural language understanding, is far below human abilities. Real-world reasoning, which is an unavoidable part of many advanced forms of computer vision and natural language understanding, is particularly difficult---suggesting the advent of computers with superhuman general intelligence is not imminent. The possibility of attaining a singularity by computers that lack these abilities is discussed briefly.

  • The Future of Synchronization on Multicores: The multicore transformation (Ubiquity symposium)
    Synchronization bugs such as data races and deadlocks make every programmer cringe traditional locks only provide a partial solution, while high-contention locks can easily degrade performance. Maurice Herlihy proposes replacing locks with transactions. He discusses adapting the well-established concept of data base transactions to multicore systems and shared main memory.
  • The MOOC and the Genre Moment: MOOCs and technology to advance learning and learning research (Ubiquity symposium)
    In order to determine (and shape) the long-term impact of MOOCs, we must consider not only cognitive and technological factors but also cultural ones, such as the goals of education and the cultural processes that mediate the diffusion of a new teaching modality. This paper examines the implicit cultural assumptions in the "MOOCs and Technology to Advance Learning and Learning Research Symposium" and proposes an alternative theory of diffusion to Clayton Christensen's disruptive innovation model as an illustration of the complexity that these assumptions hide.
  • The Multicore Transformation Closing Statement: The multicore transformation (Ubiquity symposium)
    Multicore CPUs and GPUs have brought parallel computation within reach of any programmer. How can we put the performance potential of these machines to good use? The contributors of the symposium suggest a number of approaches, among them algorithm engineering, parallel programming languages, compilers that target both SIMD and MIMD architectures, automatic detection and repair of data races, transactional memory, automated performance tuning, and automatic parallelizers. The transition from sequential to parallel computing is now perhaps at the half-way point. Parallel programming will eventually become routine, because advances in hardware, software, and programming tools are simplifying the problems of designing and implementing parallel computations.
  • Making Effective Use of Multicore Systems A software perspective: The multicore transformation (Ubiquity symposium)
    Multicore processors dominate the commercial marketplace, with the consequence that almost all computers are now parallel computers. To take maximum advantage of multicore chips, applications and systems should take advantage of that parallelism. As of today, a small fraction of applications do. To improve that situation and to capitalize fully on the power of multicore systems, we need to adopt programming models, parallel algorithms, and programming languages that are appropriate for the multicore world, and to integrate these ideas and tools into the courses that educate the next generation of computer scientists.
  • MOOCs: Symptom, Not Cause of Disruption: MOOCs and technology to advance learning and learning research (Ubiquity symposium)
    Is the MOOCs phenomenon a disruptive innovation or a transient bubble? It may be partly both. Broadcasting lectures and opening up courses via MOOCs by itself poses little change of the academic status quo. But academia is part of a broader academic-bureaucratic complex that provided a core framework for industrial-age institutions. The academic-bureaucratic complex rests on the premise that knowledge and talent must be scarce. Presumed scarcity justifies filtering access to information, to diplomas, and to jobs. But a wave of post-industrial technical, economic, and social innovations is making knowledge and talent rapidly more abundant and access more "open." This mega-trend is driving the academic-bureaucratic complex toward bankruptcy. It is being replaced by new, radically different arrangements of learning and work. The embrace of MOOCs is a symptom, not a cause of academia's obsolescence.
  • GPUs: High-performance Accelerators for Parallel Applications: The multicore transformation (Ubiquity symposium)
    Early graphical processing units (GPUs) were designed as high compute density, fixed-function processors ideally crafted to the needs of computer graphics workloads. Today, GPUs are becoming truly first-class computing elements on par with CPUs. Programming GPUs as self-sufficient general-purpose processors is not only hypothetically desirable, but feasible and efficient in practice, opening new opportunities for integration of GPUs in complex software systems.
  • Data-driven Learner Modeling to Understand and Improve Online Learning: MOOCs and technology to advance learning and learning research (Ubiquity symposium)
    Advanced educational technologies are developing rapidly and online MOOC courses are becoming more prevalent, creating an enthusiasm for the seemingly limitless data-driven possibilities to affect advances in learning and enhance the learning experience. For these possibilities to unfold, the expertise and collaboration of many specialists will be necessary to improve data collection, to foster the development of better predictive models, and to assure models are interpretable and actionable. The big data collected from MOOCs needs to be bigger, not in its height (number of students) but in its width more meta-data and information on learners' cognitive and self-regulatory states needs to be collected in addition to correctness and completion rates. This more detailed articulation will help open up the black box approach to machine learning models where prediction is the primary goal. Instead, a data-driven learner model approach uses fine grain data that is conceived and developed from cognitive principles to build explanatory models with practical implications to improve student learning.
  • The Multicore Transformation Opening Statement: The multicore transformation (Ubiquity symposium)
    Chips with multiple processors, called multicore chips, have caused a resurgence of interest in parallel computing. Multicores are now available in servers, PCs, laptops, embedded systems, and mobile devices. Because multiprocessors could be mass-produced for the same cost as uniprocessors, parallel programming is no longer reserved for a small elite of programmers such as operating system developers, database system designers, and supercomputer users. Thanks to multicore chips, everyone's computer is a parallel machine. Parallel computing has become ubiquitous. In this symposium, seven authors examine what it means for computing to enter the parallel age.
  • Offering Verified Credentials in Massive Open Online Courses: MOOCs and technology to advance learning and learning research (Ubiquity symposium)
    Massive open online courses (MOOCs) enable the delivery of high-quality educational experiences to large groups of students. Coursera, one of the largest MOOC providers, developed a program to provide students with verified credentials as a record of their MOOC performance. Such credentials help students convey achievements in MOOCs to future employers and academic programs. This article outlines the process and biometrics Coursera uses to establish and verify student identity during a course. We additionally present data that suggest verified certificate programs help increase student success rates in courses.
  • Assessment in Digital At-scale Learning Environments: MOOCs and technology to advance learning and learning research (Ubiquity symposium)
    Assessment in traditional courses has been limited to either instructor grading, or problems that lend themselves well to relatively simple automation, such as multiple-choice bubble exams. Progress in educational technology, combined with economies of scale, allows us to radically increase both the depth and the accuracy of our measurements of what students learn. Increasingly, we can give rapid, individualized feedback for a wide range of problems, including engineering design problems and free-form text answers, as well as provide rich analytics that can be used to improve both teaching and learning. Data science and integration of data from disparate sources allows for increasingly inexpensive and accurate micro-assessments, such as those of open-ended textual responses, as well as estimation of higher-level skills that lead to long-term student success.
  • Ubiquity symposium: The science in computer science: natural computation
    In this twelfth piece of the Ubiquity symposium discussing science in computer science, Erol Gelenbe reviews computation in natural systems, focusing mainly on biology and citing examples of the computation that is inherent in chemistry, natural selection, gene regulatory networks, and neuronal systems. This article originally appeared as part of the "What is Computation" symposium.
  • Interview with Mark Guzdial, Georgia Institute of Technology: computing as creation

    Mark Guzdial is a Professor in the School of Interactive Computing at Georgia Institute of Technology (Georgia Tech). His research focuses on the intersection of computing and education, from the role of computing in facilitating education to how we educate about computing. In this interview with him, he discusses how we teach computing and to whom, especially his contention that a contextualized approach is a powerful tool to teach everyone about computing.

  • An interview with David Alderson: in search of the real network science

    There has been an explosion of interest in mathematical models of large networks, leading to numerous research papers and books. The National Research Council carried out a study evaluating the emergence of a new area called "network science," which could provide the mathematics and experimental methods for characterizing, predicting, and designing networks. David Alderson has become a leading advocate for formulating the foundations of network science so that its predictions can be applied to real networks.