Human and machine focus in IEEE Pervasive Computing
It seems like yesterday when a small group at the edge of the computer science/EE academic and research communities interested in HCI, sensors, wireless, and embedded computing met in workshops at retreats like Semi Ah Moo in Washington or Schloss Dagstuhl in Germany to plot out the future of what we then called, for the most part, ubiquitous or pervasive computing. Inspired by Marc Weiser’s seminal vision of less than a decade before, we dreamed big, and before appropriate wireless infrastructure and networking paradigms were appropriately in place, we cobbled together our demos to shine a bit of light into what this now termed “Internet of Things” world would be like. What seemed almost fanciful 20 years ago has become the norm. With infrastructure and agile cloud computing abounding, sensors are indeed getting everywhere, and with advances in machine learning, this ubiquitous data can increasingly be leveraged for nearly infinite purpose. But with our success comes many levels of societal concern. In this special issue, we focus on the twin demons relating to attention – namely the dangers of ubiquitous surveillance and living in a Panopticon vs. the danger of our personal attentional resources being fragmented by too many competing digital factions that exploit intimate knowledge of their users.
Regarding the former, surveillance capabilities once accessible in limited ways by law enforcement or intelligence agencies are now potentially ubiquitous, as we are surrounded by microphones and cameras constantly monitored by tireless AIs, wearing or carrying GPS tracking devices, and in general radiating increasing numbers of bits everywhere we go. Turning sensor-laden items off is less of an option – there isn’t generally an “off” switch and if we manage to power some down, there are starting to be too many smart objects entering our environment to account for. The increase in convenience and capability that these devices contribute to our lives are becoming undeniable and indispensable – on the other hand, this can all change for the worse if bad actors, authoritarian regimes, etc. hack or exploit this information for harmful purposes – some of this is already happening. Furthermore, recent advances in microelectronics, MEMS, low power operation, and energy scavenging are enabling ever smaller sensory “bugs” that bad actors can hide in our environment with increasing effectiveness. Is there a way through which we can again “take control” here, be assured that we can escape from being monitored when it suits us, and achieve a lasting trust in our devices?
On the other hand, the smart environments that IoT enables will get to know us better than we know ourselves, and constantly compete for our attention. How will today’s overwhelmingly distracting online experience, with ubiquitous websites that explode with all manner of “click bait” to lure us into deep pits, scale to the immersive experience that pervasive displays and augmented reality glasses promise? Can we avoid garish nightmares, such as portrayed in Keiichi Matsuda’s fanciful short “Hyper-Reality”? Perhaps leveraging preferences and dynamic models of users can help this, but we already see that being used for further manipulation, with “ads” targeted more directly towards influencing us, or more insidiously, presentation of distorted information or “fake news” in ways that can captivate our attention and increase their effect. Are there means of putting users in true control here, with their precious and limited attentional capability respected and augmented rather than diverted and diminished?
We are interested in papers that address these topics, including, for example:
- Means of securing smart devices in our possession so we know they are properly “off”
- Means of detecting and thwarting unwanted surveillance in our environment
- Ways of jamming or preventing devices from perceiving or transmitting information
- Ways to secure the data produced by these systems so we know it will be used for our purposes
- Systems to more productively focus a user’s attention
- Management of notification systems to prevent unwanted interruption
- Methods of providing information that are properly graded between ambient and foreground
- Systems that respect the context of the user in how they present information
- Systems that can amplify a user’s attention as opposed to fragment it
- Ways of dynamically delegating tasks to agents as opposed to direct interaction with users
- Effects of distraction on effective intelligence and rational choice
The guest editors invite original and high-quality submissions addressing all aspects of this field, as long as the connection to pervasive computing and/or the Internet of Things is clear and central to the paper. Review or summary articles — for example, critical evaluations of the state of the art, or an insightful analysis of established and upcoming technologies — may be accepted if they demonstrate academic rigor and relevance.
Articles submitted to IEEE Pervasive Computing should not exceed 6,000 words, including all text, the abstract, keywords, bibliography, biographies, and table text. The word count should include 250 words for each table and figure. References should be limited to at most 20 citations (30 for survey papers). Authors are encouraged, but not required, to use a template for submission (accepted articles will ultimately be typeset by magazine staff for publication).
Note that the magazine always welcomes submissions into its regular queue that cover the role of computing in the physical world – as characterized by visions such as the Internet of Things and ubiquitous computing. Topics of interest are, e.g., hardware design, sensor networks, mobile systems, human-computer interaction, industrial design, machine learning, data science, but also societal issues including privacy and ethics. Simply select the “Regular” option when submitting at the submission site (submissions are possible at any time; no need for prior abstract by email).
Special Issue Guest Editors
- Joe Paradiso, MIT
- Dan Siewiorek, Carnegie Mellon University
- James Landay, Stanford University