Students love digital … don’t they?

In the ever accelerating rush to digital delivery, is this actually what students want or need?

Last week I was at Talis Insight conference. As with previous years, this is a mix of sessions focused on those using or thinking of using Talis products, with lots of rich experience talks. However, also about half of the time is dedicated to plenaries about the current state and future prospects for technology in higher education; so well worth attending (it is free!) whether or not you are a Talis user.

Speakers this year included Bill Rammell, now Vice-Chancellor at the University of Bedfordshire, but who was also Minister of State for Higher Education during the second Blair government, and during that time responsible for introducing the National Student Survey.

Another high profile speaker was Rosie Jones, who is Director of Library Services at the Open University … which operates somewhat differently from the standard university library!

However, among the VCs, CEOs and directors of this and that, it was the two most junior speakers who stood out for me. Eva Brittin-Snell and Alex Davie are to SAGE student scholars from Sussex. As SAGE scholars they have engaged in research on student experience amongst their peers, speak at events like this and maintain a student blog, which includes, amongst other things the story of how Eva came to buy her first textbook.

Eva and Alex’s talk was entitled “Digital through a student’s eyes” (video). Many of the talks had been about the rise of digital services and especially the eTextbook. Eva and Alex were the ‘digital natives’, so surely this was joy to their ears. Surprisingly not.

Alex, in her first year at university, started by alluding to the previous speakers, the push for book-less libraries, and general digital spiritus mundi, but offered an alternative view. Students were annoyed at being asked to buy books for a course where only a chapter or two would be relevant; they appreciated the convenience of an eBook, when core textbooks were permanently out on and, and instantly recalled once one got hold of them. However, she said they still preferred physical books, as they are far more usable (even if heavy!) than eBooks.

Eva, a fourth year student, offered a different view. “I started like Aly”, she said, and then went on to describe her change of heart. However, it was not a revelation of the pedagogical potential of digital, more that she had learnt to live through the pain. There were clear practical and logistic advantages to eBooks, there when and where you wanted, but she described a life of constant headaches from reading on-screen.

Possibly some of this is due to the current poor state of eBooks that are still mostly simply electronic versions of texts designed for paper. Also, one of their student surveys showed that very few students had eBook readers such as Kindle (evidently now definitely not cool), and used phones primarily for messaging and WhatsApp. The centre of the student’s academic life was definitely the laptop, so eBooks meant hours staring at a laptop screen.

However, it also reflects a growing body of work showing the pedagogic advantages of physical note taking, potential developmental damage of early tablet and smartphone use, and industry figures showing that across all areas eBook sales are dropping and physical book sales increasing. In addition there is evidence that children and teenagers people prefer physical books, and public library use by young people is growing.

It was also interesting that both Alex and Eva complained that eTextbooks were not ‘snappy’ enough. In the age of Tweet-stream presidents and 5-minute attention spans, ‘snappy’ was clearly the students’ term of choice to describe their expectation of digital media. Yet this did not represent a loss of their attention per se, as this was clearly not perceived as a problem with physical books.

… and I am still trying to imagine what a critical study of Aristotle’s Poetics would look like in ‘snappy’ form.

There are two lessons from this for me. First what would a ‘digital first’ textbook look like. Does it have to be ‘snappy’, or are there ways to maintain attention and depth of reading in digital texts?

The second picks up on issues in the co-authored paper I presented at NordiChi last year, “From intertextuality to transphysicality: The changing nature of the book, reader and writer“, which, amongst other things, asked how we might use digital means to augment the physical reading process, offering some of the strengths of eBooks such as the ability to share annotations, but retaining a physical reading experience.  Also maybe some of the physical limitations of availability could be relieved, for example, if university libraries work with bookshops to have student buy and return schemes alongside borrowing?

It would certainly be good if students did not have to learn to live with pain.

We have a challenge.

Of academic communication: overload, homeostatsis and nostalgia

open-mailbox-silhouetteRevisiting on an old paper on early email use and reflecting on scholarly communication now.

About 30 years ago, I was at a meeting in London and heard a presentation about a study of early email use in Xerox and the Open University. At Xerox the use of email was already part of their normal culture, but it was still new at OU. I’d thought they had done a before and after study of one of the departments, but remembered clearly their conclusions: email acted in addition to other forms of communication (face to face, phone, paper), but did not substitute.

Gilbert-Cockton-from-IDFIt was one of those pieces of work that I could recall, but didn’t have a reference too. Facebook to the rescue! I posted about it and in no time had a series of helpful suggestions including Gilbert Cockton who nailed it, finding the meeting, the “IEE Colloquium on Human Factors in Electronic Mail and Conferencing Systems” (3 Feb 1989) and the precise paper:

Fung , T. O’Shea , S. Bly. Electronic mail viewed as a communications catalyst. IEE Colloquium on Human Factors in Electronic Mail and Conferencing Systems, , pp.1/1–1/3. INSPEC: 3381096 http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=197821

In some extraordinary investigative journalism, Gilbert also noted that the first author, Pat Fung, went on to fresh territory after retirement, qualifying as a scuba-diving instructor at the age of 75.

The details of the paper were not exactly as I remembered. Rather than a before and after study, it was a comparison of computing departments at Xerox (mature use of email) and OU’s (email less ingrained, but already well used). Maybe I had simply embroidered the memory over the years, or maybe they presented newer work at the colloquium, than was in the 3 page extended abstract.   In those days this was common as researchers did not feel they needed to milk every last result in a formal ‘publication’. However, the conclusions were just as I remembered:

“An exciting finding is its indication that the use of sophisticated electronic communications media is not seen by users as replacing existing methods of communicating. On the contrary, the use of such media is seen as a way of establishing new interactions and collaboration whilst catalysing the role of more traditional methods of communication.”

As part of this process following various leads by other Facebook friends, I spent some time looking at early CSCW conference proceedings, some at Saul Greenburg’s early CSCW bibliography [1] and Ducheneaut and Watts (15 years on) review of email research [2] in the 2005 HCI special issue on ‘reinventing email’ [3] (both notably missing the Fung et al. paper). I downloaded and skimmed several early papers including Wendy McKay’s lovely early (1988) study [4] that exposed the wide variety of ways in which people used email over and above simple ‘communication’. So much to learn from this work when the field was still fresh,

This all led me to reflect both on the Fung et al. paper, the process of finding it, and the lessons for email and other ‘communication’ media today.

Communication for new purposes

A key finding was that “the use of such media is seen as a way of establishing new interactions and collaboration“. Of course, the authors and their subjects could not have envisaged current social media, but the finding if this paper was exactly an example of this. In 1989 if I had been trying to find a paper, I would have scoured my own filing cabinet and bookshelves, those of my colleagues, and perhaps asked people when I met them. Nowadays I pop the question into Facebook and within minutes the advice starts to appear, and not long after I have a scanned copy of the paper I was after.

Communication as a good thing

In the paper abstract, the authors say that an “exciting finding” of the paper is that “the use of sophisticated electronic communications media is not seen by users as replacing existing methods of communicating.” Within paper, this is phrased even more strongly:

“The majority of subjects (nineteen) also saw no likelihood of a decrease in personal interactions due to an increase in sophisticated technological communications support and many felt that such a shift in communication patterns would be undesirable.”

Effectively, email was seen as potentially damaging if it replaced other more human means of communication, and the good outcome of this report was that this did not appear to be happening (or strictly subjects believed it was not happening).

However, by the mid-1990s, papers discussing ’email overload’ started to appear [5].

I recall a morning radio discussion of email overload about ten years ago. The presenter asked someone else in the studio if they thought this was a problem. Quite un-ironically, they answered, “no, I only spend a couple of hours a day”. I have found my own pattern of email change when I switched from highly structured Eudora (with over 2000 email folders), to Gmail (mail is like a Facebook feed, if it isn’t on the first page it doesn’t exist). I was recently talking to another academic who explained that two years ago he had deliberately taken “email as stream” as a policy to control unmanageable volumes.

If only they had known …

Communication as substitute

While Fung et al.’s respondents reported that they did not foresee a reduction in other forms of non-electronic communication, in fact even in the paper the signs of this shift to digital are evident.

Here are the graphs of communication frequency for the Open University (30 people, more recent use of email) and Xerox (36 people, more established use) respectively.

( from Fung et al., 1989)

( from Fung et al., 1989)

( from Fung et al., 1989)

( from Fung et al., 1989)

It is hard to draw exact comparisons as it appears there may have been a higher overall volume of communication at Xerox (because of email?).  Certainly, at that point, face-to-face communication remains strong at Xerox, but it appears that not only the proportion, but total volume of non-digital non-face-to-face communications is lower than at OU.  That is sub substitution has already happened.

Again, this is obvious nowadays, although the volume of electronic communications would have been untenable in paper (I’ve sometimes imagined printing out a day’s email and trying to cram it in a pigeon-hole), the volume of paper communications has diminished markedly. A report in 2013 for Royal Mail recorded 3-6% pa reduction in letters over recent years and projected a further 4% pa for the foreseeable future [6].

academic communication and national meetungs

However, this also made me think about the IEE Colloquium itself. Back in the late 1980s and 1990s it was common to attend small national or local meetings to meet with others and present work, often early stage, for discussion. In other fields this still happens, but in HCI it has all but disappeared. Maybe I have is a little nostalgia, but this does seem a real loss as it was a great way for new PhD students to present their work and meet with the leaders in their field. Of course, this can happen if you get your CHI paper accepted, but the barriers are higher, particularly for those in smaller and less well-resourced departments.

Some of this is because international travel is cheaper and faster, and so national meetings have reduced in importance – everyone goes to the big global (largely US) conferences. Many years ago research on day-to-day time use suggested that we have a travel ‘time budget’ reactively constant across counties and across different kinds of areas within the same country [7]. The same is clearly true of academic travel time; we have a certain budget and if we travel more internationally then we do correspondingly less nationally.

(from Zahavi, 1979)

(from Zahavi, 1979)

However, I wonder if digital communication also had a part to play. I knew about the Fung et al. paper, even though it was not in the large reviews of CSCW and email, because I had been there. Indeed, the reason that the Fung et al.paper was not cited in relevant reviews would have been because it was in a small venue and only available as paper copy, and only if you know it existed. Indeed, it was presumably also below the digital radar until it was, I assume, scanned by IEE archivists and deposited in IEEE digital library.

However, despite the advantages of this easy access to one another and scholarly communication, I wonder if we have also lost something.

In the 1980s, physical presence and co-presence at an event was crucial for academic communication. Proceedings were paper and precious, I would at least skim read all of the proceedings of any event I had been to, even those of large conferences, because they were rare and because they were available. Reference lists at the end of my papers were shorter than now, but possibly more diverse and more in-depth, as compared to more directed ‘search for the relevant terms’ literature reviews of the digital age.

And looking back at some of those early papers, in days when publish-or-perish was not so extreme, when cardiac failure was not an occupational hazard for academics (except maybe due to the Cambridge sherry allowance), at the way this crucial piece of early research was not dressed up with an extra 6000 words of window dressing to make a ‘high impact’ publication, but simply shared. Were things more fun?


 

[1] Saul Greenberg (1991) “An annotated bibliography of computer supported cooperative work.” ACM SIGCHI Bulletin, 23(3), pp. 29-62. July. Reprinted in Greenberg, S. ed. (1991) “Computer Supported Cooperative Work and Groupware”, pp. 359-413, Academic Press. DOI: http://dx.doi.org/10.1145/126505.126508
https://pdfs.semanticscholar.org/52b4/d0bb76fcd628c00c71e0dfbf511505ae8a30.pdf

[2] Nicolas Ducheneaut and Leon A. Watts (2005). In search of coherence: a review of e-mail research. Hum.-Comput. Interact. 20, 1 (June 2005), 11-48. DOI= 10.1080/07370024.2005.9667360
http://www2.parc.com/csl/members/nicolas/documents/HCIJ-Coherence.pdf

[3] Steve Whittaker, Victoria Bellotti, and Paul Moody (2005). Introduction to this special issue on revisiting and reinventing e-mail. Hum.-Comput. Interact. 20, 1 (June 2005), 1-9.
http://www.tandfonline.com/doi/abs/10.1080/07370024.2005.9667359

[4] Wendy E. Mackay. 1988. More than just a communication system: diversity in the use of electronic mail. In Proceedings of the 1988 ACM conference on Computer-supported cooperative work (CSCW ’88). ACM, New York, NY, USA, 344-353. DOI=http://dx.doi.org/10.1145/62266.62293
https://www.lri.fr/~mackay/pdffiles/TOIS88.Diversity.pdf

[5] Steve Whittaker and Candace Sidner (1996). Email overload: exploring personal information management of email. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’96), Michael J. Tauber (Ed.). ACM, New York, NY, USA, 276-283. DOI=http://dx.doi.org/10.1145/238386.238530
https://www.ischool.utexas.edu/~i385q/readings/Whittaker_Sidner-1996-Email.pdf

[6] The outlook for UK mail volumes to 2023. PwC prepared for Royal Mail Group, 15 July 2013
http://www.royalmailgroup.com/sites/default/files/ The%20outlook%20for%20UK%20mail%20volumes%20to%202023.pdf

[7] Yacov Zahavi (1979). The ‘UMOT’ Project. Prepared For U.S. Department Of Transportation Ministry Of Transport and Fed. Rep. Of Germany.
http://www.surveyarchive.org/Zahavi/UMOT_79.pdf

principles vs guidelines

I was recently asked to clarify the difference between usability principles and guidelines.  Having written a page-full of answer, I thought it was worth popping on the blog.

As with many things the boundary between the two is not absolute … and also the term ‘guidelines’ tends to get used differently at different times!

However, as a general rule of thumb:

  • Principles tend to be very general and would apply pretty much across different technologies and systems.
  • Guidelines tend to be more specific to a device or system.

As an example of the latter, look at the iOS Human Interface Guidelines on “Adaptivity and Layout”   It starts with a general principle:

“People generally want to use their favorite apps on all their devices and in multiple contexts”,

but then rapidly turns that into more mobile specific, and then iOS specific guidelines, talking first about different screen orientations, and then about specific iOS screen size classes.

I note that the definition on page 259 of Chapter 7 of the HCI textbook is slightly ambiguous.  When it says that guidelines are less authoritative and more general in application, it means in comparison to standards … although I’d now add a few caveats for the latter too!

Basically in terms of ‘authority’, from low to high:

lowest principles agreed by community, but not mandated
guidelines proposed by manufacture, but rarely enforced
highest standards mandated by standards authority

In terms of general applicability, high to low:

highest principles very broad e.g. ‘observability’
guidelines more specific, but still allowing interpretation
lowest standards very tight

This ‘generality of application’ dimension is a little more complex as guidelines are often manufacturer specific so arguably less ‘generally applicable’ than standards, but the range of situations that standard apply to is usually much tighter.

On the whole the more specific the rules, the easier they are to apply.  For example, the general principle of observability requires that the designer think about how it applies in each new application and situation. In contrast, a more specific rule that says, “always show the current editing state in the top right of the screen” is easy to apply, but tells you nothing about other aspects of system state.

Human-Like Computing

Last week I attended an EPSRC workshop on “Human-Like Computing“.

The delegate pack offered a tentative definition:

“offering the prospect of computation which is akin to that of humans, where learning and making sense of information about the world around us can match our human performance.” [E16]

However, the purpose of this workshop was to clarify, and expand on this, exploring what it might mean for computers to become more like humans.

It was an interdisciplinary meeting with some participants coming from more technical disciplines such as cognitive science, artificial intelligence, machine learning and Robotics; others from psychology or studying human and animal behaviour; and some, like myself, from HCI or human factors, bridging the two.

Why?

Perhaps the first question is why one might even want more human-like computing.

There are two obvious reasons:

(i) Because it is a good model to emulate — Humans are able to solve some problems, such as visual pattern finding, which computers find hard. If we can understand human perception and cognition, then we may be able to design more effective algorithms. For example, in my own work colleagues and I have used models based on spreading activation and layers of human memory when addressing ‘web scale reasoning’ [K10,D10].

robot-3-clip-sml(ii) For interacting with people — There is considerable work in HCI in making computers easier to use, but there are limitations. Often we are happy for computers to be simply ‘tools’, but at other times, such as when your computer notifies you of an update in the middle of a talk, you wish it had a little more human understanding. One example of this is recent work at Georgia Tech teaching human values to artificial agents by reading them stories! [F16]

To some extent (i) is simply the long-standing area of nature-inspired or biologically-inspired computing. However, the combination of computational power and psychological understanding mean that perhaps we are the point where new strides can be made. Certainly, the success of ‘deep learning’ and the recent computer mastery of Go suggest this. In addition, by my own calculations, for several years the internet as a whole has had more computational power than a single human brain, and we are very near the point when we could simulate a human brain in real time [D05b].

Both goals, but particularly (ii), suggest a further goal:

(iii) new interaction paradigms — We will need to develop new ways to design for interacting with human-like agents and robots, not least how to avoid the ‘uncanny valley’ and how to avoid the appearance of over-competence that has bedevilled much work in this broad area. (see more later)

Both goals also offer the potential for a fourth secondary goal:

(iv) learning about human cognition — In creating practical computational algorithms based in human qualities, we may come to better understand human behaviour, psychology and maybe even society. For example, in my own work on modelling regret (see later), it was aspects of the computational model that highlighted the important role of ‘positive regret’ (“the grass is greener on the other side”) to hep us avoid ‘local minima’, where we stick to the things we know and do not explore new options.

Human or superhuman?

Of course humans are not perfect, do we want to emulate limitations and failings?

For understanding humans (iv), the answer is probably “yes”, and maybe by understanding human fallibility we may be in a better position to predict and prevent failures.

Similarly, for interacting with people (ii), the agents should show at least some level of human limitations (even if ‘put on’); for example, a chess program that always wins would not be much fun!

However, for simply improving algorithms, goal (i), we may want to get the ‘best bits’, from human cognition and merge with the best aspects of artificial computation. Of course it maybe that the frailties are also the strengths, for example, the need to come to decisions and act in relatively short timescales (in terms of brain ‘ticks’) may be one way in which we avoid ‘over learning’, a common problem in machine learning.

In addition, the human mind has developed to work with the nature of neural material as a substrate, and the physical world, both of which have shaped the nature of human cognition.

Very simple animals learn purely by Skinner-like response training, effectively what AI would term sub-symbolic. However, this level of learning require many exposures to similar stimuli. For more rare occurrences, which do not occur frequently within a lifetime, learning must be at the, very slow pace of genetic development of instincts. In contrast, conscious reasoning (symbolic processing) allows us to learn through a single or very small number of exposures; ideal for infrequent events or novel environments.

Big Data means that computers effectively have access to vast amounts of ‘experience’, and researchers at Google have remarked on the ‘Unreasonable Effectiveness of Data’ [H09] that allows problems, such as translation, to be tackled in a statistical or sub-symbolic way which previously would have been regarded as essentially symbolic.

Google are now starting to recombine statistical techniques with more knowledge-rich techniques in order to achieve better results again. As humans we continually employ both types of thinking, so there are clear human-like lessons to be learnt, but the eventual system will not have the same ‘balance’ as a human.

If humans had developed with access to vast amounts of data and maybe other people’s experience directly (rather than through culture, books, etc.), would we have developed differently? Maybe we would do more things unconsciously that we do consciously. Maybe with enough experience we would never need to be conscious at all!

More practically, we need to decide how to make use of this additional data. For example, learning analytics is becoming an important part of educational practice. If we have an automated tutor working with a child, how should we make use of the vast body of data about other tutors interactions with other children?   Should we have a very human-like tutor that effectively ‘reads’ learning analytics just as a human tutor would look at a learning ‘dashboard’? Alternatively, we might have a more loosely human-inspired ‘hive-mind’ tutor that ‘instinctively’ makes pedagogic choices based on the overall experience of all tutors, but maybe in an unexplainable way?

What could go wrong …

There have been a number of high-profile statements in the last year about the potential coming ‘singularity’ (when computers are clever enough to design new computers leading to exponential development), and warnings that computers could become sentient, Terminator-style, and take over.

There was general agreement at the workshop this kind of risk was overblown and that despite breakthroughs, such as the mastery of Go, these are still very domain limited. It is many years before we have to worry about even general intelligence in robots, let alone sentience.

A far more pressing problem is that of incapable computers, which make silly mistakes, and the way in which people, maybe because of the media attention to the success stories, assume that computers are more capable than they are!

Indeed, over confidence in algorithms is not just a problem for the general public, but also among computing academics, as I found in my personal experience on the REF panel.

There are of course many ethical and legal issues raised as we design computer systems that are more autonomous. This is already being played out with driverless cars, with issues of insurance and liability. Some legislators are suggesting allowing driverless cars, but only if there is a drive there to take control … but if the car relinquishes control, how do you safely manage the abrupt change?

Furthermore, while the vision of autonomous robots taking over the world is still far fetched; more surreptitious control is already with us. Whether it is Uber cabs called by algorithm, or simply Google’s ranking of search results prompting particular holiday choices, we all to varying extents doing “what the computer tells us”. I recall in the Dalek Invasion of Earth, the very un-human-like Daleks could not move easily amongst the rubble of war-torn London. Instead they used ‘hypnotised men’ controlled by some form of neural headset. If the Daleks had landed today and simply taken over or digitally infected a few cloud computing services would we know?

Legibility

Sometimes it is sufficient to have a ‘black box’ that makes decisions and acts. So long as it works we are happy. However, a key issue for many ethical and legal issues, but also for practical interaction, is the ability to be able to interrogate a system, so seek explanations of why a decision has been made.

Back in 1992 I wrote about these issues [D92], in the early days when neural networks and other forms of machine learning were being proposed for a variety of tasks form controlling nuclear fusion reactions to credit scoring. One particular scenario, was if an algorithm were used to pre-sort large numbers of job applications. How could you know whether the algorithms were being discriminatory? How could a company using such algorithms defend themselves if such an accusation were brought?

One partial solution then, as now, was to accept underlying learning mechanisms may involve emergent behaviour form statistical, neural network or other forms of opaque reasoning. However, this opaque initial learning process should give rise to an intelligible representation. This is rather akin to a judge who might have a gut feeling that a defendant is guilty or innocent, but needs to explicate that in a reasoned legal judgement.

This approach was exemplified by Query-by-Browsing, a system that creates queries from examples (using a variant of ID3), but then converts this in SQL queries. This was subsequently implemented [D94] , and is still running as a web demonstration.

For many years I have argued that it is likely that our ‘logical’ reasoning arises precisely form this need to explain our own tacit judgement to others. While we simply act individually, or by observing the actions of others, this can be largely tacit, but as soon as we want others to act in planned collaborate ways, for example to kill a large animal, we need to convince them. Once we have the mental mechanisms to create these explanations, these become internalised so that we end up with internal means to question our own thoughts and judgement, and even use them constructively to tackle problems more abstract and complex than found in nature. That is dialogue leads to logic!

Scenarios

We split into groups and discussed scenarios as a means to understand the potential challenges for human-like computing. Over multiple session the group I was in discussed one man scenario and then a variant.

Paramedic for remote medicine

The main scenario consisted of a patient far form a central medical centre, with an intelligent local agent communicating intermittently and remotely with a human doctor. Surprisingly the remote aspect of the scenario was not initially proposed by me thinking of Tiree, but by another member of the group thinking abut some of the remote parts of the Scottish mainland.

The local agent would need to be able communicate with the patient, be able to express a level of empathy, be able to physically examine (needing touch sensing, vision), and discuss symptoms. On some occasions, like a triage nurse, the agent might be sufficiently certain to be able to make a diagnosis and recommend treatment. However, at other times it may need to pass on to the remote doctor, being able to describe what had been done in terms of examination, symptoms observed, information gathered from the patient, in the same way that a paramedic does when handing over a patient to the hospital. However, even after the handover of responsibility, the local agent may still form part of the remote diagnosis, and maybe able to take over again once the doctor has determined an overall course of action.

The scenario embodied many aspects of human-like computing:

  • The agent would require a level of emotional understanding to interact with the patient
  • It would require fine and situation contingent robotic features to allow physical examination
  • Diagnosis and decisions would need to be guided by rich human-inspired algorithms based on large corpora of medical data, case histories and knowledge of the particular patient.
  • The agent would need to be able to explain its actions both to the patient and to the doctor. That is it would not only need to transform its own internal representations into forms intelligible to a human, but do so in multiple ways depending on the inferred knowledge and nature of the person.
  • Ethical and legal responsibility are key issues in medical practice
  • The agent would need to be able manage handovers of control.
  • The agent would need to understand its own competencies in order to know when to call in the remote doctor.

The scenario could be in physical or mental health. The latter is particularly important given recent statistics, which suggested only 10% of people in the UK suffering mental health problems receive suitable help.

Physiotherapist

As a more specific scenario still, one fog the group related how he had been to an experienced physiotherapist after a failed diagnosis by a previous physician. Rather than jumping straight into a physical examination, or even apparently watching the patient’s movement, the physiotherapist proceeded to chat for 15 minutes about aspects of the patient’s life, work and exercise. At the end of this process, the physiotherapist said, “I think I know the problem”, and proceeded to administer a directed test, which correctly diagnosed the problem and led to successful treatment.

Clearly the conversation had given the physiotherapist a lot of information about potential causes of injury, aided by many years observing similar cases.

To do this using an artificial agent would suggest some level of:

  • theory/model of day-to-day life

Thinking about the more conversational aspects of this I was reminded of the PhD work of Ramanee Peiris [P97]. This concerned consultations on sensitive subjects such as sexual health. It was known that when people filled in (initially paper) forms prior to a consultation, they were more forthcoming and truthful than if they had to provide the information face-to-face. This was even if the patient knew that the person they were about to see would read the forms prior to the consultation.

Ramanee’s work extended this first to electronic forms and then to chat-bot style discussions which were semi-scripted, but used simple textual matching to determine which topics had been covered, including those spontaneously introduced by the patient. Interestingly, the more human like the system became the more truthful and forthcoming the patients were, even though they were less so wit a real human.

As well as revealing lessons for human interactions with human-like computers, this also showed that human-like computing may be possible with quite crude technologies. Indeed, even Eliza was treated (to Weizenbaum’s alarm) as if it really were a counsellor, even though people knew it was ‘just a computer’ [W66].

Cognition or Embodiment?

I think it fair to say that the overall balance, certainly in the group I was in, was towards the cognitivist: that is more Cartesian approach starting with understanding and models of internal cognition, and then seeing how these play out with external action. Indeed, the term ‘representation’ used repeatedly as an assumed central aspect of any human-like computing, and there was even talk of resurrecting Newells’s project for a ‘unified theory of cognition’ [N90]

There did not appear to be any hard-core embodiment theorist at the workshops, although several people who had sympathies. This was perhaps as well as we could easily have degenerated into well rehearsed arguments for an against embodiment/cognition centred explanations … not least about the critical word ‘representation’.

However, I did wonder whether a path that deliberately took embodiment centrally would be valuable. How many human-like behaviours could be modelled in this way, taking external perception-action as central and only taking on internal representations when they were absolutely necessary (Alan Clark’s 007 principle) [C98].

Such an approach would meet limits, not least the physiotherapist’s 25 minute chat, but I would guess would be more successful over a wider range of behaviours and scenarios then we would at first think.

Human–Computer Interaction and Human-Like Computing

Both Russell and myself were partly there representing our own research interest, but also more generally as part of the HCI community looking at the way human-like computing would intersect exiting HCI agendas, or maybe create new challenges and opportunities. (see poster) It was certainly clear during the workshop that there is a substantial role for human factors from fine motor interactions, to conversational interfaces and socio-technical systems design.

Russell and I presented a poster, which largely focused on these interactions.

HCI-HLC-poster

There are two sides to this:

  • understanding and modelling for human-like computing — HCI studies and models complex, real world, human activities and situations. Psychological experiments and models tend to be very deep and detailed, but narrowly focused and using controlled, artificial tasks. In contrast HCI’s broader, albeit more shallow, approach and focus on realistic or even ‘in the wild’ tasks and situations may mean that we are in an ideal position to inform human-like computing.

human interfaces for human-like computing — As noted in goal (iii) we will need paradigms for humans to interact with human-like computers.

As an illustration of the first of these, the poster used my work on making sense of the apparently ‘bad’ emotion of regret [D05] .

An initial cognitive model of regret was formulated involving a rich mix of imagination (in order to pull past events and action to mind), counter-factual modal reasoning (in order to work out what would have happened), emption (which is modified to feel better or worse depending on the possible alternative outcomes), and Skinner-like low-level behavioural learning (the eventual purpose of regret).

cog-model

This initial descriptive and qualitative cognitive model was then realised in a simplified computational model, which had a separate ‘regret’ module which could be plugged into a basic behavioural learning system.   Both the basic system and the system with regret learnt, but the addition of regret did so with between 5 and 10 times fewer exposures.   That is, the regret made a major improvement to the machine learning.

architecture

Turning to the second. Direct manipulation has been at the heart of interaction design since the PC revolution in the 1980s. Prior to that command line interfaces (or worse job control interfaces), suggested a mediated paradigm, where operators ‘asked’ the computer to do things for them. Direct manipulation changed that turning the computer into a passive virtual world of computational objects on which you operated with the aid of tools.

To some extent we need to shift back to the 1970s mediated paradigm, but renewed, where the computer is no longer like an severe bureaucrat demanding the precise grammatical and procedural request; but instead a helpful and understanding aide. For this we can draw upon existing areas of HCI such as human-human communications, intelligent user interfaces, conversational agents and human–robot interaction.

References

[C98] Clark, A. 1998. Being There: Putting Brain, Body and the World Together Again. MIT Press. https://mitpress.mit.edu/books/being-there

[D92] A. Dix (1992). Human issues in the use of pattern recognition techniques. In Neural Networks and Pattern Recognition in Human Computer Interaction Eds. R. Beale and J. Finlay. Ellis Horwood. 429-451. http://www.hcibook.com/alan/papers/neuro92/

[D94] A. Dix and A. Patrick (1994). Query By Browsing. Proceedings of IDS’94: The 2nd International Workshop on User Interfaces to Databases, Ed. P. Sawyer. Lancaster, UK, Springer Verlag. 236-248.

[D05] Dix, A..(2005).  The adaptive significance of regret. (unpublished essay, 2005) http://alandix.com/academic/essays/regret.pdf

[D05b] A. Dix (2005). the brain and the web – a quick backup in case of accidents. Interfaces, 65, pp. 6-7. Winter 2005. http://alandix.com/academic/papers/brain-and-web-2005/

[D10] A. Dix, A. Katifori, G. Lepouras, C. Vassilakis and N. Shabir (2010). Spreading Activation Over Ontology-Based Resources: From Personal Context To Web Scale Reasoning. Internatonal Journal of Semantic Computing, Special Issue on Web Scale Reasoning: scalable, tolerant and dynamic. 4(1) pp.59-102. http://www.hcibook.com/alan/papers/web-scale-reasoning-2010/

[E16] EPSRC (2016). Human Like Computing Hand book. Engineering and Physical Sciences Research Council. 17 – 18 February 2016

[F16] Alison Flood (2016). Robots could learn human values by reading stories, research suggests. The Guardian, Thursday 18 February 2016 http://www.theguardian.com/books/2016/feb/18/robots-could-learn-human-values-by-reading-stories-research-suggests

[H09] Alon Halevy, Peter Norvig, and Fernando Pereira. 2009. The Unreasonable Effectiveness of Data. IEEE Intelligent Systems 24, 2 (March 2009), 8-12. DOI=10.1109/MIS.2009.36

[K10] A. Katifori, C. Vassilakis and A. Dix (2010). Ontologies and the Brain: Using Spreading Activation through Ontologies to Support Personal Interaction. Cognitive Systems Research, 11 (2010) 25–41. http://alandix.com/academic/papers/Ontologies-and-the-Brain-2010/

[N90] Allen Newell. 1990. Unified Theories of Cognition. Harvard University Press, Cambridge, MA, USA. http://www.hup.harvard.edu/catalog.php?isbn=9780674921016

[P97] DR Peiris (1997). Computer interviews: enhancing their effectiveness by simulating interpersonal techniques. PhD Thesis, University of Dundee. http://virtual.inesc.pt/rct/show.php?id=56

[W66] Joseph Weizenbaum. 1966. ELIZA—a computer program for the study of natural language communication between man and machine. Commun. ACM 9, 1 (January 1966), 36-45. DOI=http://dx.doi.org/10.1145/365153.365168

level of detail – scale matters

We get used to being able to zoom into every document picture and map, but part of the cartographer’s skill is putting the right information at the right level of detail.  If you took area maps and then scaled them down, they would not make a good road atlas, the main motorways would hardly be visible, and the rest would look like a spider had walked all over it.  Similarly if you zoom into a road atlas you would discover the narrow blue line of each motorway is in fact half a mile wide on the ground.

Nowadays we all use online maps that try to do this automatically.  Sometimes this works … and sometimes it doesn’t.

Here are three successive views of Google maps focused on Bournemouth on the south coast of England.

On the first view we see Bournemouth clearly marked, and on the next, zooming in a little Poole, Christchurch and some smaller places also appear.  So far, so good, as we zoom in more local names are shown as well as the larger place.

bournemouth-1  bournemouth-2

However, zoom in one more level and something weird happens, Bournemouth disappears.  Poole and Christchurch are there, but no  Bournemouth.

bournemouth-3

However, looking at the same level scale on another browser, Bournemouth is there still:

bournemouth-4

The difference between the two is the Hotel Miramar.  On the first browser I am logged into Google mail, and so Google ‘knows’ I am booked to stay in the Hotel Miramar (presumably by scanning my email), and decides to display this also.   The labels for Bournemouth and the hotel label overlap, so Google simply omitted the Bournemouth one as less important than the hotel I am due to stay in.

A human map maker would undoubtedly have simply shifted the name ‘Bournemouth’ up a bit, knowing that it refers to the whole town.  In principle, Google maps could do the same, but typically geocoding (e.g. Geonames) simply gives a point for each location rather than an area, so it is not easy for the software to make adjustments … except Google clearly knows it is ‘big’ as it is displayed on the first, zoomed out, view; so maybe it could have done better.

This problem of overlapping legends will be familiar to anyone involved in visualisation whether map based or more abstract.

cone-trees

The image above is the original Cone Tree hierarchy browser developed by Xerox PARC in the early 1990s1.  This was the early days of interactive 3D visualisation, and the Cone Tree exploited many of the advantages such as a larger effective ‘space’ to place objects, and shadows giving both depth perception, but also a level of overview.  However, there was no room for text labels without them all running over each other.

Enter the Cam Tree:

cam-tree

The Cam Tree is identical to the cone tree, except because it is on its side it is easier to place labels without them overlapping 🙂

Of course, with the Cam Tree the regularity of the layout makes it easy to have a single solution.  The problem with maps is that labels can appear anywhere.

This is an image of a particularly cluttered part of the Frasan mobile heritage app developed for the An Iodhlann archive on Tiree.  Multiple labels overlap making them unreadable.  I should note that the large number of names only appear when the map is zoomed in, but when they do appear, there are clearly too many.

frasan-overlap

It is far from clear how to deal with this best.  The Google solution was simply to not show some things, but as we’ve seen that can be confusing.

Another option would be to make the level of detail that appears depend not just on the zoom, but also the local density.  In the Frasan map the locations of artefacts are not shown when zoomed out and only appear when zoomed in; it would be possible for them to appear, at first, only in the less cluttered areas, and appear in more busy areas only when the map is zoomed in sufficiently for them to space out.   This would trade clutter for inconsistency, but might be worthwhile.  The bigger problem would be knowing whether there were more things to see.

Another solution is to group things in busy areas.  The two maps below are from house listing sites.  The first is Rightmove which uses a Google map in its map view.  Note how the house icons all overlap one another.  Of course, the nature of houses means that if you zoom in sufficiently they start to separate, but the initial view is very cluttered.  The second is daft.ie; note how some houses are shown individually, but when they get too close they are grouped together and just the number of houses in the group shown.

rightmove-houses  daft-ie-house-site

A few years ago, Geoff Ellis and I reviewed a number of clutter reduction techniques2, each with advantages and disadvantages, there is no single ‘best’ answer. The daft.ie grouping solution is for icons, which are fixed size and small, the text label layout problem is far harder!

Maybe someday these automatic tools will be able to cope with the full variety of layout problems that arise, but for the time being this is one area where human cartographers still know best.

  1. Robertson, G. G. ; Mackinlay, J. D. ; Card, S. K. Cone Trees: animated 3D visualizations of hierarchical informationProceedings of the ACM Conference on Human Factors in Computing Systems (CHI ’91); 1991 April 27 – May 2; New Orleans; LA. NY: ACM; 1991; 189-194.[back]
  2. Geoffrey Ellis and Alan Dix. 2007. A Taxonomy of Clutter Reduction for Information VisualisationIEEE Transactions on Visualization and Computer Graphics 13, 6 (November 2007), 1216-1223. DOI=10.1109/TVCG.2007.70535[back]

Making the most of stakeholder interviews

Recently, I was asked for any tips or suggestions for stakeholder interviews.   I realised it was going to be more than would fit in the response to an IM message!

I’ll assume that this is purely for requirements gathering. For participatory or co-design, many of the same things hold, but there would be additional activities.

See also HCI book chapter 5: interaction design basics and chapter 13: socio-organizational issues and stakeholder requirements.

Kinds of knowing

First remember:

  • what they know – Whether the cleaner of a public lavatory or the CEO of a multi-national, they have rich experience in their area. Respect even the most apparently trivial comments.
  • what they don’t know they know – Much of our knowledge is tacit, things they know in the sense that they apply in their day to day activities, but are not explicitly aware of knowing. Part of your job as interviewer is to bring this latent knowledge to the surface.
  • what they don’t know – You are there because you bring expertise and knowledge, most critically in what is possible; it is often hard for someone who has spent years in a job to see that it could be different.

People also find it easier to articulate ‘what’ compared with ‘why’ knowledge:

  • whatobjects, things, and people involved in their job, also the actions they perform, but even the latter can be difficult if they are too familiar
  • why – the underlying criteria, motivations and values that underpin their everyday activities

Be concrete

Most of us think best when we have concrete examples or situations to draw on, even if we are using these to describe more abstract concepts.

  • in their natural situation – People often find it easier to remember things if they are in the place and amongst the tools where they normally do them.
  • printer-detailshow you what they do – Being in their workplace also makes it easy for them to show you what they do – see “case study: Pensions printout“, for an example of this, the pensions manager was only able to articulate how a computer listing was used when he could demonstrate using the card files in his office. Note this applies to physical things, and also digital ones (e.g. talking through files on computer desktop)
  • watch what they do – If circumstances allow directly observe – often people omit the most obvious things, either because they assume it is known, or because it is too familiar and hence tacit. In “Early lessons – It’s not all about technology“, the (1960s!) system analyst realised that it was the operators’ fear of getting their clothes dirty that was slowing down the printing machine; this was not because of anything any of the operators said, but what they were observed doing.
  • seek stories of past incidents – Humans are born story tellers (listen to a toddler). If asked to give abstract instructions or information we often struggle.
  • normal and exceptional storiesboth are important. Often if asked about a process or procedure the interviewee will give the normative or official version of what they do. This may be because they don’t want to admit to unofficial methods, or maybe that they think of the task in normative terms even though they actually never do it that way. Ask for ‘war stories’ of unusual, exceptional or problematic situations.
  • technology probes or envisioned scenarios – Although it may be hard to envisage new situations, if potential futures are presented in an engaging and concrete manner, then we are much more able to see ourselves in them, maybe using a new system, and say “but no that wouldn’t work.”  (see more at hcibook online! “technology probes“)

Estrangement

As noted the stakeholder’s tacit knowledge may be the most important. By seeking out or deliberately creating odd or unusual situations, we may be able to break out of this blindness to the normal.

  • ask about other people’s jobs – As well as asking a stakeholder about what they do, ask them about other people; they may notice things about others better then the other person does themselves.
  • strangers / new folk / outsiders – Seek out the new person, the temporary visitor from another site, or even the cleaner; all see the situation with fresh eyes.
  • technology probes or envisioned scenarios (again!) – As well as being able to say “but no that wouldn’t work”, we can sometimes say “but no that wouldn’t work, because …”
  • making-teafantasy – When the aim is to establish requirements and gain understanding, there is no reason why an envisaged scenario need be realistic or even possible. Think SciFi and magic 🙂 For an extended example of this look at ‘Making Tea‘, which asked chemists to make tea as if it were a laboratory procedure!

Of course some of these, notably fantasy scenarios, may work better in some organisations than others!

Analyse

You need to make sense of all that interview data!

  • the big picture – Much of what you learn will be about what happens to individuals. You need to see how this all fits together (e.g. Checkland/ Soft System Methodology ‘Rich Picture’, or process diagrams). Dig beyond the surface to make sense of the underlying organisational goals … and how they may conflict with those of individuals or other organisations.
  • the details – Look for inconsistencies, gaps, etc. both within an individual’s own accounts and between different people’s viewpoints. This may highlight the differences between what people believe happens and what actually happens, or part of that uncovering the tacit
  • the deep values – As noted it is often hard for people to articulate the criteria and motivations that determine their actions. You could look for ‘why’ vocabulary in what they say or written documentation, or attempt to ‘reverse engineer’ process to find purposes. Unearthing values helps to uncover potential conflicts (above), but also is important when considering radical changes. New processes, methods or systems might completely change existing practices, but should still be consonant with the underlying drivers for those original practices. See work on transforming musicological archival practice in the InConcert project for an example.

If possible you may wish to present these back to those involved, even if people are unaware of certain things they do or think, once presented to them, the flood gates open!   If your stakeholders are hard to interview, maybe because they are senior, or far away, or because you only have limited access, then if possible do some level of analysis mid-way so that you can adjust future interviews based on past ones.

Prioritise

Neither you nor your interviewees have unlimited time; you need to have a clear idea of the most important things to learn – whilst of course keeping an open ear for things that are unexpected!

If possible plan time for a second round of some or all the interviewees after you have had a chance to analyse the first round. This is especially important as you may not know what is important until this stage!

Privacy, respect and honesty

You may not have total freedom in who you see, what you ask or how it is reported, but in so far as is possible (and maybe refuse unless it is) respect the privacy and personhood of those with whom you interact.

This is partly about good professional practice, but also efficacy – if interviewees know that what they say will only be reported anonymously they are more likely to tell you about the unofficial as well as the official practices! If you need to argue for good practice, the latter argument may hold more sway than the former!

In your reporting, do try to make sure that any accounts you give of individuals are ones they would be happy to hear. There may be humorous or strange stories, but make sure you laugh with not at your subjects. Even if no one else recognises them, they may well recognise themselves.

Of course do ensure that you are totally honest before you start in explaining what will and will not be related to management, colleagues, external publication, etc. Depending on the circumstances, you may allow interviewees to redact parts of an interview transcript, and/or to review and approve parts of a report pertaining to them.

If you do accessibility, please do it properly

I was looking at Coke Cola’s Rugby World Cup site1,

On the all-red web page the tooltip stood out, with the uninformative text, “headimg”.

coke-rugby-web-site-zoom

Peeking in the HTML, this is in both the title and alt attributes of the image.

<img title="headimg" alt="headimg" class="cq-dd-image" 
     src="/content/promotions/nwen/....png">

I am guessing that the web designer was aware of the need for an alt tag for accessibility, and may even have had been prompted to fill in the alt tag by the design software (Dreamweaver does this).  However, perhaps they just couldn’t think of an alternative text and so put anything in (although as the image consists of text, this does betray a certain lack of imagination!); they probably planned to come back later to do it properly.

As the micro-site is predominantly targeted at the UK, Coke Cola are legally bound to make it accessible and so may well have run it through WCAG accessibility checking software.  As the alt tag was present it will have passed W3C validation, even though the text is meaningless.  Indeed the web designer might have added the unhelpful text just to get the page to validate.

The eventual page is worse than useless, a blank alt tag would have meant it was just skipped, and at least the text “header image” would have been read as words, whereas “headimg” will be spelt out letter by letter.

Perhaps I am being unfair,  I’m sure many of my own pages are worse than this … but then again I don’t have the budget of Coke Cola!

More seriously there are important lessons for process.  In particular it is very likely that at the point the designer uploads an image they are prompted for the alt tag — this certainly happens with Dreamweaver.  However, at this point your focus is in getting the page looking right as the client looking at the initial designs is unlikely to be using a screen reader.

Good design software should not just prompt for the right information, but at the right time.  It would be far better to make it easy to say “ask me later” and build up a to do list, rather than demand the information when the system wants it, and risk the user entering anything to ‘keep the system quiet’.

I call this the Micawber principle2 and it is a good general principle for any notifications requiring user action.  Always allow the user to put things off, but also have the application keep track of pending work, and then make it easy for the user see what needs to be done at a more suitable time.

  1. Largely because I was fascinated by the semantically questionable statement “Win one of up to 1 million exclusive Gilbert rugby balls.” (my emphasis).[back]
  2. From Dicken’s Mr Micawber, who was an arch procrastinator.  See Learning Analytics for the Academic:
    An Action Perspective where I discuss this principle in the context of academic use of learning analytics.[back]

REF Redux 1 – UK research assessment for computing; what it means and is it right?

REF is the 5 yearly exercise to assess the quality of UK university research, the results of which are crucial for both funding and prestige. In 2014, I served on the sub-panel that assessed computing submissions. Since, the publication of the results I have been using public domain data from the REF process in order to validate the results using citation data.

The results have been alarming suggesting that, despite the panel’s best efforts to be fair, in fact there was significant bias both in terms of areas of computer science and types of universities.  Furthermore the first of these is also likely to have led to unintentional emergent gender bias.

I’ve presented results of this at a bibliometrics workshop at WebSci 2015 and at a panel at the British HCI conference a couple of weeks ago. However, I am aware that the full data and spreadsheets can be hard to read, so in a couple of posts I’ll try to bring out the main issues. A report and mini-site describes the methods used in detail, so in these posts I will concentrate on the results, and implications, starting in this post by setting the scene seeing how REF ranked sub-areas of computing and the use of citations for validation of the process. The next post will look at how UK computing sits amongst world research, and whether this agrees with the REF assessment.

Few in UK computing departments will have not seen the ranking list produced as part of the final report of the computing REF panel.

REF-ranks

Here topic areas are ranked by the percentage of 4* outputs (the highest rank). Top of the list is Cryptography, with over 45% of outputs ranked 4*. The top of the list is dominated by theoretical computing areas, with 30-40% 4*, whilst the more applied and human areas are at the lower end with less than 20% 4*. Human-centred computing and collaborative computing, the areas where most HCI papers would be placed, are pretty much at the bottom of the list, with 10% and 8.8% of 4* papers respectively.

Even before this list was formally published I had a phone call from someone in an institution where the knowledge of it had obviously leaked. Their department was interviewing for a lectureship and the question being asked was whether they should be recruiting candidates from HCI as this will clearly not be good looking towards REF 2020.

Since then I have heard of numerous institutions who are questioning the value of supporting these more applied areas, due to their apparent poor showing under REF.

In fact, even taken at face value, the data says nothing at all about the value in particular departments., and the sub-panel report includes the warning “These data should be treated with circumspection“.

There are three possible reasons any, or all of which would give rise to the data:

  1. the best applied work is weak — including HCI :-/
  2. long tail — weak researchers choose applied areas
  3. latent bias — despite panel’s efforts to be fair

I realised that citation data could help disentangle these.

There has been understandable resistance against using metrics as part of research assessment. However, that is about their use to assess individuals or small groups. There is general agreement that citation-based metrics are a good measure of research quality en masse; indeed I believe HEFCE are using citations to verify between-panel differences in 4* allocations, and in Morris Sloman’s post REF analysis slides (where the table above first appeared), he also uses the overall correlation between citations and REF scores as a positive validation of the process.

The public domain REF data does not include the actual scores given to each output, but does include citations data provided by Scopus in 2013. In addition, for Morris’ analysis in late 2014, Richard Mortier (then at Nottingham, now at Cambridge) collected Google Scholar citations for all REF outputs.

Together, these allow detailed citation-based analysis to verify (or otherwise) the validity of the REF outputs for computer science.

I’ll go into details in following posts, but suffice to say the results were alarming and show that, whatever other effects may have played a part, and despite the very best efforts of all involved, very large latent bias clearly emerged during the progress.

If the light is on, they can hear (and now see) you

hello-barbie-matel-from-guardianFollowing Samsung’s warning that its television sets can listen into your conversations1, and Barbie’s, even more scary, doll that listens to children in their homes and broadcasts this to the internet2, the latest ‘advances’ make it possible to be seen even when the curtains are closed and you thought you were private.

For many years it has been possible for security services, or for that matter sophisticated industrial espionage, to pick up sounds based on incandescent light bulbs.

The technology itself is not that complicated, vibrations in the room are transmitted to the filament, which minutely changes its electrical characteristics. The only complication is extracting the high-frequency signal from the power line.

040426-N-7949W-007However, this is a fairly normal challenge for high-end listening devices. Years ago when I was working with submarine designers at Slingsby, we were using the magnetic signature of power running through undersea cables to detect where they were for repair. The magnetic signatures were up to 10,000 times weaker than the ‘noise’ from the Earth’s own magnetic field, but we were able to detect the cables with pin-point accuracy3. Military technology for this is far more advanced.

The main problem is the raw computational power needed to process the mass of data coming from even a single lightbulb, but that has never been a barrier for GCHQ or the NSA, and indeed, with cheap RaspberryPi-based super-computers, now not far from the hobbyist’s budget4.

Using the fact that each lightbulb reacts slightly differently to sound, means that it is, in principle, possible to not only listen into conversations, but work out which house and room they come from by simply adding listening equipment at a neighbourhood sub-station.

The benefits of this to security services are obvious. Whereas planting bugs involves access to a building, and all other techniques involve at least some level of targeting, lightbulb-based monitoring could simply be installed, for example, in a neighbourhood known for extremist views and programmed to listen for key words such as ‘explosive’.

For a while, it seemed that the increasing popularity of LED lightbulbs might end this. This is not because LEDs do not have an electrical response to vibrations, but because of the 12V step down transformers between the light and the mains.

Of course, there are plenty of other ways to listen into someone in their home, from obvious bugs to laser-beams bounced of glass (you can even get plans to build one of your own at Instructables), or even, as MIT researchers recently demonstrated at SIGGRAPH, picking up the images of vibrations on video of a glass of water, a crisp packet, and even the leaves of a potted plant5. However, these are all much more active and involve having an explicit suspect.

Similarly blanket internet and telephone monitoring have applications, as was used for a period to track Osama bin Laden’s movements6, but net-savvy terrorists and criminals are able to use encryption or bypass the net entirely by exchanging USB sticks.

However, while the transformer attenuates the acoustic back-signal from LEDs, this only takes more sensitive listening equipment and more computation, a lot easier than a vibrating pot-plant on video!

So you might just think to turn up the radio, or talk in a whisper. Of course, as you’ve guessed by now, and, as with all these surveillance techniques, simply yet more computation.

Once the barriers of LEDs are overcome, they hold another surprise. Every LED not only emits light, but acts as a tiny, albeit inefficient, light detector (there’s even an Arduino project to use this principle).   The output of this is a small change in DC current, which is hard to localise, but ambient sound vibrations act as a modulator, allowing, again in principle, both remote detection and localisation of light.

220px-60_LED_3W_Spot_Light_eq_25WIf you have several LEDs, they can be used to make a rudimentary camera7. Each LED lightbulb uses a small array of LEDs to create a bright enough light. So, this effectively becomes a very-low-resolution video camera, a bit like a fly’s compound eye.

While each image is of very low quality, any movement, either of the light itself (hanging pendant lights are especially good), or of objects in the room, can improve the image. This is rather like the principle we used in FireFly display8, where text mapped onto a very low-resolution LED pixel display is unreadable when stationary, but absolutely clear when moving.

pix-11  pix-21
pix-12  pix-22
LEDs produce multiple very-low-resolution image views due to small vibrations and movement9.

OLYMPUS DIGITAL CAMERA  OLYMPUS DIGITAL CAMERA
Sufficient images and processing can recover an image.

So far MI5 has not commented on whether it uses, or plans to use this technology itself, nor whether it has benefited from information gathered using it by other agencies. Of course its usual response is to ‘neither confirm nor deny’ such things, so without another Edward Snowden, we will probably never know.

So, next time you sit with a coffee in your living room, be careful what you do, the light is watching you.

  1. Not in front of the telly: Warning over ‘listening’ TV. BBC News, 9 Feb 2015. http://www.bbc.co.uk/news/technology-31296188[back]
  2. Privacy fears over ‘smart’ Barbie that can listen to your kids. Samuel Gibbs, The Guardian, 13 March 2015. http://www.theguardian.com/technology/2015/mar/13/smart-barbie-that-can-listen-to-your-kids-privacy-fears-mattel[back]
  3. “Three DSP tricks”, Alan Dix, 1998. http://alandix.com/academic/papers/DSP99/DSP99-full.html[back]
  4. “Raspberry Pi at Southampton: Steps to make a Raspberry Pi Supercomputer”, http://www.southampton.ac.uk/~sjc/raspberrypi/[back]
  5. A. Davis, M. Rubinstein, N. Wadhwa, G. Mysore, F. Durand and W. Freeman (2014). The Visual Microphone: Passive Recovery of Sound from Video. ACM Transactions on Graphics (Proc. SIGGRAPH), 33(4):79:1–79:10 http://people.csail.mit.edu/mrub/VisualMic/[back]
  6. Tracking Use of Bin Laden’s Satellite Phone, all Street Journal, Evan Perez, Wall Street Journal, 28th May, 2008. http://blogs.wsj.com/washwire/2008/05/28/tracking-use-of-bin-ladens-satellite-phone/[back]
  7. Blinkenlight, LED Camera. http://blog.blinkenlight.net/experiments/measurements/led-camera/[back]
  8. Angie Chandler, Joe Finney, Carl Lewis, and Alan Dix. 2009. Toward emergent technology for blended public displays. In Proceedings of the 11th international conference on Ubiquitous computing (UbiComp ’09). ACM, New York, NY, USA, 101-104. DOI=10.1145/1620545.1620562[back]
  9. Note using simulated images; getting some real ones may be my next Tiree Tech Wave project.[back]

CHI Academy … a Faustian bargain?

I am on a short excursion from walking Wales to CHI 2013 in Paris.

Last night I was inducted into the SIGCHI Academy. No great fanfares or anything, just a select dinner and a short ceremony. I thought Gerrit, who is current SIGCHI chair would look good with a sword dubbing each person, but instead just a plaque, a handshake and a photo or two by Ben Shniederman, amanuensis of CHI.

I feel in two minds. On the one hand there are many lovely people in CHI community, and I spent a great afternoon and evening chatting to folk including Phillipe Palanque, Mary Czerwinsky and Hiroshi Ishii over dinner. However, ACM and to some extent SIGCHI often appear like the Star Wars imperial forces, intent on global domination.

The CEO of ACM did little to dispel this at the opening ceremony this morning.  He spoke of ACM’s international aspirations and praised CHI for regularly having its conferences outside of the US.

Now ACM is the de facto international computing organisation and CHI is the de facto international conference in human–computer interaction, but by virtue of the fact that they are the US ones.  In principle, IFIP and Interact are the international computing organisation and HCI conference respectively, as IFIP is the UNESCO founded body of which ACM and other national computing bodies, such as the BCS in the UK, are members.  Interact, the HCI conference sponsored by IFIP is truly international being held in numerous countries over the years (but I think never yet the US!); in contrast having approximately two out of three conferences in the US is laudable, but hardly the sign of a truly international organisation.

So, is the ACM an originally US organisation that is in the process of slowly becoming truly international, or is it part of more general US cultural domination?  Although probably neither are completely accurate, at present there seems to be significant aspects of the latter under the guise of the former.  In a way this is, in microcosm, an image of the same difficult relationship between USA and UN in other areas of international affairs.

And by joining the SIGCI Academy am I increasing the European presence in CHI and thus part of the process to make it truly international, or selling my academic soul in a Faustian bargain?