Digital Assistants and AMAs with configurable ethical theories

About a year ago, there was a bit of furore in the newspapers on digital assistants, like Amazon Echo’s Alexa, Apple’s Siri, or Microsoft’s Cortana, in a smart home to possibly snitch on you if you’re the marijuana-smoking family member [1,2]. This may be relevant if you live in a conservative state or country, where it is still illegal to do so. Behind it is a multi-agent system that would do some argumentation among the stakeholders (the kids, the parents, and the police). That example sure did get the students’ attention in the computer ethics class I taught last year. It did so too with an undergraduate student—double majoring in compsci and philosophy—who opted to do the independent research module. Instead of the multiple actor scenario, however, we considered it may be useful to equip such a digital assistant, or an artificial moral agent (AMA) more broadly, with multiple moral theories, so that a user would be able to select their preferred theory and let the AMA make the appropriate decision for her on whichever dilemma comes up. This seems preferable over an at-most-one-theory AMA.

For instance, there’s the “Mia the alcoholic” moral dilemma [3]: Mia is disabled and has a new model of the carebot that can fetch her alcoholic drinks in the comfort of her home. At some point, she’s getting drunk but still orders the carebot to bring her one more tasty cocktail. Should the carebot comply? The answer depends on one’s ethical viewpoint. If you had answered with ‘yes’, you probably would not want to buy a carebot that would refuse to serve you, and likewise vv. But how to make the AMA culturally and ethically more flexible to be able to adjust to the user’s moral preferences?

The first step in that direction has now been made by that (undergrad) research student, George Rautenbach, which I supervised. The first component is a three-layered approach, with at the top layer a ‘general ethical theory’ model (called Genet) that is expressive enough to be able to model a specific ethical theory, such as utilitarianism, ethical egoism, or Divine Command Theory. This was done for those three and Kantianism, so as to have a few differences in consequence-based or not, the possible ‘patients’ of the action, sort of principles, possible thresholds and such. These reside in the middle layer. Then there’s Mia’s egoism, the parent’s Kantian viewpoint about the marijuana, a train company’s utilitarianism to sort out the trolley problem, and so on at the bottom layer, which are instantiations of the respective specific ethical theories in the middle layer.

The Genet model was evaluated by demonstrating that those four theories can be modelled with Genet and the individual theories were evaluated with a few use cases to show that the attributes stored are relevant and sufficient for those reasoning scenarios for the individuals. For instance, eventually, Mia’s egoism wouldn’t get her another drink fetched by the carebot, but as a Kantian, she would have been served.

The details are described in the technical report “Toward Equipping Artificial Moral Agents with multiple ethical theories” [4] and the models are also available for download as XML files and an OWL file. To get all this to work in a device, there’s still the actual reasoning component to implement (a few architectures exist for that) and for a user to figure out which theory they actually subscribe to so as to have the device configured accordingly. And of course, there is a range of ethical issues with digital assistants and AMAs, but that’s a topic perhaps better suited for the SIPP (FKA computer ethics) module in our compsci programme [5] and other departments.

 

p.s.: a genet is also an agile cat-like animal mostly living in Africa, just in case you were wondering about the abbreviation of the model.

 

References

[1] Swain, F. AIs could debate whether a smart assistant should snitch on you. New Scientist, 22 February 2019. Online: https://www.newscientist.com/article/2194613-ais-could-debatewhether-a-smart-assistant-should-snitch-on-you/ (last accessed: 5 March 2020).

[2] Liao, B., Slavkovik, M., van der Torre, L. Building Jiminy Cricket: An Architecture for Moral Agreements Among Stakeholders. ACM Conference on Artificial Intelligence, Ethics, and Society 2019, Hawaii, USA. Preprint: arXiv:1812.04741v2, 7 March 2019.

[3] Millar, J. An ethics evaluation tool for automating ethical decision-making in robotsand self-driving cars. Applied Artificial Intelligence, 30(8):787–809, 2016.

[4] Rautenbach, G., Keet, C.M. Toward equipping Artificial Moral Agents with multiple ethical theories. University of Cape Town. arxiv:2003.00935, 2 March 2020.

[5] Computer Science Department. Social Issues and Professional Practice in IT & Computing. Lecture Notes. 6 December 2019.

Dancing algorithms and algorithms for dance apps

Browsing through teaching material a few years ago, I had stumbled upon dancing algorithms, which illustrate common algorithms in computing using dance [1] and couldn’t resist writing about since I used to dance folk dances. More of them have been developed in the meantime. The list further below has them sorted by algorithm and by dance style, with links to the videos on YouTube. Related ideas have also been used in mathematics teaching, such as for teaching multiplication tables with Hip Hop singing and dancing in a class in Cape Town, dancing equations, mathsdance [2], and, stretching the scope a bit, rapping fractions elsewhere.

That brought me to the notion of algorithms for dancing, which takes a systematic and mathematical or computational approach to dance. For instance, the maths in salsa [2] and an ontology to describe some of dance [3], and a few more, which go beyond the hard-to-read Labanotation that is geared toward ballet but not pair dancing, let alone a four-couple dance [4] or, say, a rueda (multiple pairs in a circle, passing on partners). Since there was little for Salsa dance, I had proposed a computer science & dance project last year, and three computer science honours students were interested to develop their Salsational Dance App. The outcome of their hard work is that now there’s a demonstrated-to-be-usable API for the data structure to describe moves (designed for beats that counts in multiples of four), a grammar for the moves to construct valid sequences, and some visualization of the moves, therewith improving on the static information from Salsa is good that counted as baseline. The data structure is extensible to other dance styles beyond Salsa that have multiples of four, such as Bachata (without the syncopations, true).

In my opinion, the grammar is the coolest component, since it is both from a scientific and from an engineering perspective the most novel aspect and it was technically the most challenging task of the project. The grammar’s expressiveness remained within a context-free grammar, which is computationally still doable. This may be because of the moves covered—the usual moves one learns during a Salsa beginners course—or maybe in any case. The grammar has been tested to cover a series of test cases in the system, which all worked well (whether all theoretically physically feasible sequences feel comfortable to dance is a separate matter). The parsing is done by the JavaCC parser, which carries out a formal verification to check if the sequence of moves is valid, and it even does that on-the-fly. That is, when a user selects a move during the planning of a sequence of moves, it instantly re-computes which one(s) of the moves in the system can follow the last one selected, as can be seen in the following screenshot.

source: http://projects.cs.uct.ac.za/honsproj/cgi-bin/view/2019/baijnath_chetty_marajh.zip/DEDANCE_website/images/parser/ui4.PNG

Screenshot of planning a sequence of moves.

The grammar thus even has a neat ‘wrapper’ in the form of an end-user usable tool, which was evaluated by several members of Evolution Dance Company in Cape Town. Special thanks go to its owner, Mr. Angus Prince, who served also as external expert on the project. Some more screenshots, the code, and the project papers by the three students—Alka Baijnath, Jordy Chetty, and Micara Marajh—are available from the CS honours project archive.

The project also showed that much more can be done, not just porting it to other dance styles, but also still for salsa. This concerns not only the grammar, but also how to encode moves in a user-friendly way and how to link it up to the graphics so that the ‘puppets’ will dance the sequence of moves selected, as well as meeting other requirements, such as a mobile app as ‘cheat sheet’ to quickly check a move during a social dance evening and choreography planning. Based on my own experiences goofing around writing down moves, the latter (choreography) seems to be less hard to realise [documenting, at least] than the ‘any move’ scenario. Either way, the honours projects topics are being finalised around now. Hopefully, there will be another 2-3 students interested in computing and dance this year, so we can build up a larger body of software tools and techniques to support dance.

 

Dancing algorithms by type

Sorting

– Quicksort as a Hungarian folk dance

– Bubble sort as a Hungarian dance, Bollywood style dance, and with synthetic music

– Shell sort as a Hungarian dance.

– Select sort as a gypsy/Roma dance

– Merge sort in ‘Transylvananian-Saxon’ dance style

– Insert sort in Romanian folk dance style

– Heap sort also as in Hungarian folk dance style

There are more sorting algorithms than these, though, so there’s plenty of choice to pick your own. A different artistic look at the algorithms is this one, with 15 sorts that almost sound like music (but not quite).

Searching

– Linear search in Flamenco style

– Binary search also in Flamenco style

Backtracking as a ballet performance

 

Dancing algorithms by dance style

European folk:

– Hungarian dance for the quicksort, bubble sort, shell sort, and heap sort;

– Roma (gypsy) dance for the select sort;

– Transylvananian-saxon dance for the merge sort;

– Romanian dance for an insert sort.

Latin American folk: Flamenco dancing a binary search and a linear search.

Bollywood dance where students are dancing a bubble sort.

Classical (Ballet) for a backtracking algorithm.

Modern (synthetic music) where a class attempts to dance a bubble sort.

 

That’s all for now. If you make a choreography for an algorithm, get people to dance it, record it, and want to have the video listed here, feel free to contact me and I’ll add it.

 

References

[1] Zoltan Katai and Laszlo Toth. Technologically and artistically enhanced multi-sensory computer programming education. Teaching and Teacher Education, 2010, 26(2): 244-251.

[2] Stephen Ornes. Math Dance. Proceedings of the National Academy of Sciences of the United States of America 2013. 110(26): 10465-10465.

[3] Christine von Renesse and Volker Ecke. Mathematics and Salsa Dancing. Journal of Mathematics and the Arts, 2011, 5(1): 17-28.

[4] Katerina El Raheb and Yannis Yoannidis. A Labanotation based ontology for representing dance movement. In: Gesture and Sign language in Human-Computer Interaction and Embodied Communication (GW’11). Springer, LNAI vol. 7206, 106-117. 2012.

[5] Michael R. Bush and Gary M. Roodman. Different partners, different places: mathematics applied to the construction of four-couple folk dances. Journal of Mathematics and the Arts, 2013, 7(1): 17-28.

DL notation plugin for Protégé 5.x

Once upon a time… the Protégé ontology development environment used Description Logic (DL) symbols and all was well—for some users at least. Then Manchester Syntax came along as the new kid on the block, using hearsay and opinion and some other authors’ preferences for an alternative rendering to the DL notation [1]. Subsequently, everyone who used Protégé was forced to deal with those new and untested keywords in the interface, like ‘some’ and ‘only’ and such, rather than the DL symbols. That had another unfortunate side-effect, being that it hampers internationalisation, for it jumbles up things rather awkwardly when your ontology vocabulary is not in English, like, say, “jirafa come only (oja or ramita)”. Even in the same English-as-first-language country, it turned out that under a controlled set-up, the DL axiom rendering in Protégé fared well in a fairly large sized experiment when compared to the Protégé interface with the sort of Manchester syntax with GUI [2], and also the OWL 2 RL rules rendering appear more positive in another (smaller) experiment [3]. Various HCI factors remain to be examined in more detail, though.

In the meantime, we didn’t fully reinstate the DL notation in Protégé in the way it was in Protégé v3.x from some 15 years ago, but with our new plugin, it will at least render the class expression in DL notation in the tool. This has the benefits that

  1. the modeller will receive immediate feedback during the authoring stage regarding a notation that may be more familiar to at least a knowledge engineer or expert modeller;
  2. it offers a natural language-independent rendering of the axioms with respect to the constructors, so that people may develop their ontology in their own language if they wish to do so, without being hampered by continuous code switching or the need for localisation; and
  3. it also may ease the transition from theory (logics) to implementation for ontology engineering novices.

Whether it needs to be integrated further among more components of the tabs and views in Protégé or other ODEs, is also a question for HCI experts to answer. The code for the DL plugin is open source, so you could extend it if you wish to do so.

The plugin itself is a jar file that can simply be dragged into the plugin folder of a Protégé installation (5.x); see the github repo for details. To illustrate it briefly, after dragging the jar file into the plugin folder, open Protégé, and add it as a view:

Then when you add some new axioms or load an ontology, select a class, and it will render all the axioms in DL notation, as shown in the following two screenshots form different ontologies:

For the sake of illustration, here’s the giraffe that eats only leaves or twigs, in the Spanish version of the African Wildlife Ontology:

The first version of the tool was developed by Michael Harrison and Larry Liu as part of their mini-project for the ontology engineering course in 2017, and it was brushed up for presentation beyond that just now by Michael Harrison (meanwhile an MSc student a CS@UCT), which was supported by a DOT4D grant to improve my textbook on ontology engineering and accompanying educational resources. We haven’t examined all possible ‘shapes’ that a class expression can take, but it definitely processes the commonly used features well. At the time of writing, we haven’t detected any errors.

p.s.: if you want your whole ontology exported at once in DL notation and to latex, for purposes of documentation generation, that is a different usage scenario and is already possible [4].

p.p.s.: if you want more DL notation, please let me know, and I’ll try to find more resources to make a v2 with more features.

References

[1] Matthew Horridge, Nicholas Drummond, John Goodwin, Alan Rector, Robert Stevens and Hai Wang (2006). The Manchester OWL syntax. OWL: Experiences and Directions (OWLED’06), Athens, Georgia, USA, 10-11 Nov 2016, CEUR-WS vol 216.

[2] E. Alharbi, J. Howse, G. Stapleton, A. Hamie and A. Touloumis. The efficacy of OWL and DL on user understanding of axioms and their entailments. The Semantic Web – ISWC 2017, C. d’Amato, M. Fernandez, V. Tamma, F. Lecue, P. Cudre-Mauroux, J. Sequeda, C. Lange and J. He (eds.). Springer 2017, pp20-36.

[3] M. K. Sarker, A. Krisnadhi, D. Carral and P. Hitzler, Rule-based OWL modeling with ROWLtab Protégé plugin. Proceedings of ESWC’17, E. Blomqvist, D. Maynard, A. Gangemi, R. Hoekstra, P. Hitzler and O. Hartig (eds.). Springer. 2017, pp 419-433.

[4] Cogan Shimizu, Pascal Hitzler, Matthew Horridge: Rendering OWL in Description Logic Syntax. ESWC (Satellite Events) 2017. Springer LNCS. pp109-113

Some experiences on making a textbook available

I did make available a textbook on ontology engineering for free in July 2018. Meanwhile, I’ve had several “why did you do this and not a proper publisher??!?” I had tried to answer that already in the textbook’s FAQ. Turns out that that short answer may be a bit too short after all. So, here follows a bit more about that.

The main question I tried to answer in the book’s FAQ was “Would it not have been better with a ‘proper publisher’?” and the answer to that was:

Probably. The layout would have looked better, for sure. There are several reasons why it isn’t. First and foremost, I think knowledge should be free, open, and shared. I also have benefited from material that has been made openly available, and I think it is fair to continue contributing to such sharing. Also, my current employer pays me sufficient to live from and I don’t think it would sell thousands of copies (needed for making a decent amount of money from a textbook), so setting up such a barrier of high costs for its use does not seem like a good idea. A minor consideration is that it would have taken much more time to publish, both due to the logistics and the additional reviewing (previous multi-author general textbook efforts led to nothing due to conflicting interests and lack of time, so I unlikely would ever satisfy all reviewers, if they would get around reading it), yet I need the book for the next OE installment I will teach soon.

Ontology Engineering (OE) is listed as an elective in the ACM curriculum guidelines. Yet, it’s suited best for advanced undergrad/postgrad level because of the prerequisites (like knowing the basics of databases and conceptual modeling). This means there won’t be big 800-students size classes all over the world lining up for OE. I guess it would not go beyond some 500-1000/year throughout the world (50 classes of 10-20 computer science students), and surely not all classes would use the textbook. Let’s say, optimistically, that 100 students/year would be asked to use the book.

With that low volume in mind, I did look up the cost of similar books in the same and similar fields with the ‘regular’ academic publishers. It doesn’t look enticing for either the author or the student. For instance this one from Springer and that one from IGI Global are all still >100 euro. for. the. eBook., and they’re the cheap ones (not counting the 100-page ‘silver bullet’ book). Handbooks and similar on ontologies, e.g., this and that one are offered for >200 euro (eBook). Admitted there’s the odd topical book that’s cheaper and in the 50-70 euro range here and there (still just the eBook) or again >100 as well, for a, to me, inexplicable reason (not page numbers) for other books (like these and those). There’s an option to publish a textbook with Springer in open access format, but that would cost me a lot of money, and UCT only has a fund for OA journal papers, not books (nor for conference papers, btw).

IOS press does not fare much better. For instance, a softcover version in the studies on semantic web series, which is their cheapest range, would be about 70 euro due to number of pages, which is over R1100, and so again above budget for most students in South Africa, where the going rate is that a book would need to be below about R600 for students to buy it. A plain eBook or softcover IOS Press not in that series goes for about 100 euro again, i.e., around R1700 depending on the exchange rate—about three times the maximum acceptable price for a textbook.

The MIT press BFO eBook is only R425 on takealot, yet considering other MIT press textbooks there, with the size of the OE book, it then would be around the R600-700. Oxford University Press and its Cambridge counterpart—that, unlike MIT press, I had checked out when deciding—are more expensive and again approaching 80-100 euro.

One that made me digress for a bit of exploration was Macmillan HE, which had an “Ada Lovelace day 2018” listing books by female authors, but a logics for CS book was again at some 83 euros, although the softer area of knowledge management for information systems got a book down to 50 euros, and something more popular, like a book on linguistics published by its subsidiary “Red Globe Press”, was down to even ‘just’ 35 euros. Trying to understand it more, Macmillan HE’s “about us” revealed that “Macmillan International Higher Education is a division of Macmillan Education and part of the Springer Nature Group, publishers of Nature and Scientific American.” and it turns out Macmillan publishes through Red Globe Press. Or: it’s all the same company, with different profit margins, and mostly those profit margins are too high to result in affordable textbooks, whichever subsidiary construction is used.

So, I had given up on the ‘proper publisher route’ on financial grounds, given that:

  • Any ontology engineering (OE) book will not sell large amounts of copies, so it will be expensive due to relatively low sales volume and I still will not make a substantial amount from royalties anyway.
  • Most of the money spent when buying a textbook from an established publisher goes to the coffers of the publisher (production costs etc + about 30-40% pure profit [more info]). Also, scholarships ought not to be indirect subsidy schemes for large-profit-margin publishers.
  • Most publishers would charge an amount of money for the book that would render the book too expensive for my own students. It’s bad enough when that happens with other textbooks when there’s no alternative, but here I do have direct and easy-to-realise agency to avoid such a situation.

Of course, there’s still the ‘knowledge should be free’ etc. argument, but this was to show that even if one were not to have that viewpoint, it’s still not a smart move to publish the textbook with the well-known academic publishers, even more so if the topic isn’t in the core undergraduate computer science curriculum.

Interestingly, after ‘publishing’ it on my website and listing it on OpenUCT and the Open Textbook Archive—I’m certainly not the only one who had done a market analysis or has certain political convictions—one colleague pointed me to the non-profit College Publications that aims to “break the monopoly that commercial publishers have” and another colleague pointed me to UCT press. I had contacted both, and the former responded. In the meantime, the book has been published by CP and is now also listed on Amazon for just $18 (about 16 euro) or some R250 for the paperback version—whilst the original pdf file is still freely available—or: you pay for production costs of the paperback, which has a slightly nicer layout and the errata I knew of at the time have been corrected.

I have noticed that some people don’t take the informal self publishing seriously—even below the so-called ‘vanity publishers’ like Lulu—notwithstanding the archives to cater for it, the financial take on the matter, the knowledge sharing argument, and the ‘textbooks for development’ in emerging economies angle of it. So, I guess no brownie points from them then and, on top of that, my publication record did, and does, take a hit. Yet, writing a book, as an activity, is a nice and rewarding change from just churning out more and more papers like a paper production machine, and I hope it will contribute to keeping the OE research area alive and lead to better ontologies in ontology-driven information systems. The textbook got its first two citations already, the feedback is mostly very positive, readers have shared it elsewhere (reddit, ungule.it, Open Libra, Ebooks directory, and other platforms), and I recently got some funding from the DOT4D project to improve the resources further (for things like another chapter, new exercises, some tools development to illuminate the theory, a proofreading contest, updating the slides for sharing, and such). So, overall, if I had to make the choice again now, I’d still do it again the way I did. Also, I hope more textbook authors will start seeing self-publishing, or else non-profit, as a good option. Last, the notion of open textbooks is gaining momentum, so you even could become a trendsetter and be fashionable 😉

A useful abstract relational model and SQL path queries

Whilst visiting David Toman at the University of Waterloo during my sabbatical earlier this year, one of the topics we looked into was their experiments on whether their SQLP—SQL with path queries, extended from [1]—would be better than plain SQL in terms of time it takes to understand queries and correctness in writing them. Turned out (in a user evaluation) that it’s faster with SQLP whilst maintaining accuracy. The really interesting aspect in all this from my perspective, however, was the so-called Abstract Relational Model (ARM), or: the modelling side of things rather than making the querying easier, as the latter is made easier with the ARM. In simple terms, the ARM [1] is alike the relational model, but then with identifiers, which makes those path queries doable and mostly more succinct, and one can partition the relations into class-relationship-like models (approaching the look-and-feel of a conceptual model) or lump stuff together into relational-model-like models, as preferred. Interestingly, it turns out that the queries remain exactly the same regardless whether one makes the ARM look more relational-like or ontology-like, which is called “invariance under vertical partitioning” in the paper [2]. Given all these nice things, there’s now also an algorithm to go from the usual relational model to an ARM schema, so that even if one has legacy resources, it’s possible to bump it up to this newer technology with more features and ease of use.

Our paper [2] that describes these details (invariance, RM-to-ARM, the evaluation), entitled “The Utility of the Abstract Relational Model and Attribute Paths in SQL”, is being published as part of the proceedings of the 21st International Conference on Knowledge Engineering and Knowledge Management (EKAW’18), which will be held in Nancy, France, in about two weeks.

This sort of Conceptual Model(like)-based Data Access (CoMoDA, if you will) may sound a bit like Ontology-Based Data Access (OBDA). Yes and No. Roughly, yes on the conceptual querying sort of thing (there’s still room for quite some hair splitting there, though); no regarding the conceptual querying sort of thing. The ARM doesn’t pretend to be an ontology, but easily has a reconstruction in a Description Logic language [3] (with n-aries! and identifiers!). SQLP is much more expressive than the union of conjunctive queries one can pose in a typical OBDA setting, however, for it is full SQL + those path queries. So, both the theory and technology are different from the typical OBDA setting. Now, don’t think I’m defecting on the research topics—I still have a whole chapter on OBDA in my textbook—but it’s interesting to learn about and play with alternative approaches toward solutions to (at a high level) the same problem of trying to make querying for information easier and faster.

 

References

[1] Borgida, A., Toman, D., Weddell, G.E. On referring expressions in information systems derived from conceptual modelling. Proc. of ER’16. Springer LNCS, vol. 9974, 183-197.

[2] Ma, W., Keet, C.M., Olford, W., Toman, D., Weddell, G. The Utility of the Abstract Relational Model and Attribute Paths in SQL. 21st International Conference on Knowledge Engineering and Knowledge Management (EKAW’18). Springer LNAI. (in print). 12-16 Nov. 2018, Nancy, France.

[3] Jacques, J.S., Toman, D., Weddell, G.E. Object-relational queries over CFDInc knowledge bases: OBDA for the SQL-Literate. Proc. of IJCAI’16. 1258-1264 (2016)

ISAO 2018, Cape Town, ‘trip’ report

The Fourth Interdisciplinary School on Applied Ontology has just come to an end, after five days of lectures, mini-projects, a poster session, exercises, and social activities spread over six days from 10 to 15 September in Cape Town on the UCT campus. It’s not exactly fair to call this a ‘trip report’, as I was the local organizer and one of the lecturers, but it’s a brief recap ‘trip report kind of blog post’ nonetheless.

The scientific programme consisted of lectures and tutorials on:

The linked slides (titles of the lectures, above) reveal only part of the contents covered, though. There were useful group exercises and plenary discussion with the ontological analysis of medical terms such as what a headache is, a tooth extraction, blood, or aspirin, an exercises on putting into practice the design process of a conceptual modelling language of one’s liking (e.g.: how to formalize flowcharts, including an ontological analysis of what those elements are and ontological commitments embedded in a language), and trying to prove some theorems of parthood theories.

There was also a session with 2-minute ‘blitztalks’ by participants interested in briefly describing their ongoing research, which was followed by an interactive poster session.

It was the first time that an ISAO had mini-projects, which turned out to have had better outcomes than I expected, considering the limited time available for it. Each group had to pick a term and investigate what it meant in the various disciplines (task description); e.g.: what does ‘concept’ or ‘category’ mean in psychology, ontology, data science, and linguistics, and ‘function’ in manufacturing, society, medicine, and anatomy? The presentations at the end of the week by each group were interesting and most of the material presented there easily could be added to the IAOA Education wiki’s term list (an activity in progress).

What was not a first-time activity, was the Ontology Pub Quiz, which is a bit of a merger of scientific programme and social activity. We created a new version based on questions from several ISAO’18 lecturers and a few relevant questions created earlier (questions and answers; we did only questions 1-3,6-7). We tried a new format compared to the ISAO’16 quiz and JOWO’17 quiz: each team had 5 minutes to answer a set of 5 questions, and another team marked the answers. This set-up was not as hectic as the other format, and resulted in more within-team interaction cf. among all participants interaction. As in prior editions, some questions and answers were debatable (and there’s still the plan to make note of that and fix it—or you could write an article about it, perhaps :)). The students of the winning team received 2 years free IAOA membership (and chocolate for all team members) and the students of the other two teams received one year free IAOA membership.

Impression of part of the poster session area, moving into the welcome reception

As with the three previous ISAO editions, there was also a social programme, which aimed to facilitate getting to know one another, networking, and have time for scientific conversations. On the first day, the poster session eased into a welcome reception (after a brief wine lapse in the coffee break before the blitztalks). The second day had an activity to stretch the legs after the lectures and before the mini-project work, which was a Bachata dance lesson by Angus Prince from Evolution Dance. Not everyone was eager at the start, but it turned out an enjoyable and entertaining hour. Wednesday was supposed to be a hike up the iconic Table Mountain, but of all the dry days we’ve had here in Cape Town, on that day it was cloudy and rainy, so an alternative plan of indoor chocolate tasting in the Biscuit Mill was devised and executed. Thursday evening was an evening off (from scheduled activities, at least), and Friday early evening we had the pub quiz in the UCT club (the campus pub). Although there was no official planning for Saturday afternoon after the morning lectures, there was again an attempt at Table Mountain, concluding the week.

The participants came from all over the world, including relatively many from Southern Africa with participants coming also from Botswana and Mauritius, besides several universities in South Africa (UCT, SUN, CUT). I hope everyone has learned something from the programme that is or will be of use, enjoyed the social programme, and made some useful new contacts and/or solidified existing ones. I look forward to seeing you all at the next ISAO or, better, FOIS, in 2020 in Bolzano, Italy.

Finally, as a non-trip-report comment from my local chairing viewpoint: special thanks go to the volunteers Zubeida Khan for the ISAO website, Zola Mahlaza and Michael Harrison for on-site assistance, and Sam Chetty for the IT admin.

Review of ‘The web was done by amateurs’ by Marco Aiello

Via one of those friend-of-a-friend likes on social media that popped up in my stream, I stumbled upon the recently published book “The web was done by amateurs” (there’s also a related talk) by Marco Aiello, which piqued my interest both concerning the title and the author. I’ve met Aiello once in Trento, when a colleague and he had a departing party, with Aiello leaving for Groningen. He probably doesn’t remember me, nor do I remember much of him—other than his lamentations about Italian academia and going for greener pastures. Turns out he’s done very well for himself academically, and the foray into writing for the general public has been, in my opinion, a fairly successful attempt with this book.

The short book—it easily can be read in a weekend—starts in the first part with historical notes on who did what for the Internet (the infrastructure) and the multiple predecessor proposals and applications of hyperlinking across documents that Tim Berners-Lee (TBL) apparently was blissfully unaware of. It’s surely a more interesting and useful read than the first Google hit, the few factoids from W3C, or Wikipedia one can find online with a simple search—or: it pays off to read books still in this day and age :). The second part is for most readers, perhaps, also still history: the ‘birth’ of the Web and the browser wars in the mid 1990s.

Part III is, in my opinion, the most fun to read: it discusses various extensions to the original design of TBL’s Web that fixes, or at least aims to fix, a shortcoming of the Web’s basics, i.e., they’re presented as “patches” to patch up a too basic—or: rank-amateur—design of the original Web. They are, among others, persistence with cookies to mimic statefulness for Web-based transactions (for, e.g., buying things on the web), trying to get some executable instructions with Java (ActiveX, Flash), and web services (from CORBA, service-oriented computing, to REST and the cloud and such). Interestingly, they all originate in the 1990s in the time of the browser wars.

There are more names in the distant and recent history of the Web that I knew of, so even I picked up a few things here or there. IIRC, they’re all men, though. Surely there would be at least one woman worthy of mention? I probably ought to know, but didn’t, so I searched the Web and easily stumbled upon the Internet Hall of Fame. That list includes Susan Estrada among the pioneers, who founded CERFnet that “grew the network from 25 sites to hundreds of sites.”, and, after that, Anriette Esterhuysen and Nancy Hafkin for the network in Africa, Qiheng Hu for doing this for China, and Ida Holz for the same in Latin America (in ‘global connections’). Web innovators specifically include Anne-Marie Eklund Löwinder for DNS security extensions (DNSSEC, noted on p143 but not by its inventor’s name) and Elizabeth Feinler for the “first query-based network host name and address (WHOIS) server” and “she and her group developed the top-level domain-naming scheme of .com, .edu, .gov, .mil, .org, and .net, which are still in use today”.

One patch to the Web that I really missed in the overview of the early patches, is the “Web 2.0”. I know that, technologically, it is a trivial extension to TBL’s original proposal: the move from static web pages in 1:n communication from content provider to many passive readers, to m:n communication with comment sections (fancy forms), or: instead of the surfer being just a recipient of information by reading one webpage after another and thinking her own thing of it, to be able to respond and interact, i.e., the chatrooms, the article and blog comment features, and, in the 2000s, the likes of MySpace and Facebook. It got so many more people involved in it all.

Continuing with the book’s content, cloud computing and the fog (section 7.9) are from this millennium, as is, what Aiello dubbed, the “Mother of All Patches.”: the Semantic Web. Regarding the latter, early on in the book (pp. vii-viii) there is already an off-hand comment that does not bode well: “Chap. 8 on the Semantic Web is slightly more technical than the rest and can be safely skipped.” (emphasis added). The way Chapter 8 is written, perhaps. Before discussing his main claim there, a few minor quibbles: it’s the Web Ontology Language OWL, not “Ontology Web Language” (p105), and there’s OWL 2 as successor of the OWL of 2004. “RDF is a nifty combination of being a simple modeling language while also functioning as an expressive ontological language” (p104), no: RDF is for representing data, not really for modeling, and most certainly would not be considered an ontology language (one can serialize an ontology in RDF/XML, but that’s different). Class satisfiability example: no, that’s not what it does, or: the simplification does not faithfully capture it; an example with a MammalFish that cannot have any instances (as subclass of both Mammal and Fish that are disjoint), would have been (regardless the real world).

The main claim of Aiello regarding the Semantic Web, however, is that it’s been that time to throw in the towel, because there hasn’t been widespread uptake of Semantic Web technologies on the Web even though it was proposed already around the turn of the millenium. I lean towards that as well and have reduced the time spent on it from my ontology engineering course over the years, but don’t want to throw out the baby with the bathwater just yet, for two reasons. First, scientific results tend to take a long time to trickle down. Second, I am not convinced that the ‘semantic’ part of the Web is the same level of end-user stuff as playing with HTML is. I still have an HTML book from 1997. It has instructions to “design your first page in 10 minutes!”. I cannot recall if it was indeed <10 minutes, but it sure was fast back in 1998-1999 when I made my first pages, as a non-IT interested layperson. I’m not sure if the whole semantics thing can be done even on the proverbial rainy Sunday afternoon, but the dumbed down version with schema.org sort of works. This schema.org brings me to p110 of Aiello’s book, which states that Google can make do with just statistics for optimal search results because of its sheer volume (so bye-bye Semantic Web). But it is not just stats-based: even Google is trying with schema.org and its “knowledge graph”; admitted, it’s extremely lightweight, but it’s more than stats-only. Perhaps the schema.org and knowledge graph sort of thing are to the Semantic Web what TBL’s proposal for the Web was to, say, the fancier HyperCard.

I don’t know if people within the Semantic Web research community would think of its tooling as technologies for the general public. I suspect not. I consider the development and use of ontologies in ontology-driven information systems as part of the ‘back office’ technologies, notwithstanding my occasional attempts to explain to friends and family what sort of things I’m working on.

What I did find curious, is that one of Aiello’s arguments for the Semantic Web’s failure was that “Using ontologies and defining what the meaning of a page is can be much more easily exploited by malicious users” (p110). It can be exploited, for sure, but statistics can go bad, very bad, too, especially on associations of search terms, the creepy amount of data collection on the Web, and bias built into the Machine Learning algorithms. Search engine optimization is just the polite terms for messing with ‘honest’ stats and algorithms. With the Semantic Web, it would a conscious decision to mess around and that’s easily traceable, but with all the stats-based approaches, it sneakishly can creep in whilst trying to keep up the veneer of impartiality, which is harder to detect. If it were a choice between two technology evils, I prefer the honest bastard cf. being stabbed in the back. (That the users of the current Web are opting for the latter does not make it the lesser of two evils.)

As to two possible new patches (not in the book and one can debate whether they are), time will tell whether a few recent calls for “decentralizing” the Web will take hold, or more fine-grained privacy that also entails more fine-grained recording of events (e.g., TBL’s solid project). The app-fication discussion (Section 10.1) was an interesting one—I hardly use mobile apps and so am not really into it—and the lock-in it entails is indeed a cause for concern for the Web and all it offers. Another section in Chapter 10 is IoT, which sounds promising and potentially scary (what would the data-hungry ML algorithms of the Web infer from my fridge contents, and from that, about me??)—for the past 10 years or so. Lastly, the final chapter has the tempting-to-read title “Should a new Web be designed?”, but the answer is not a clear yes or no. Evolve, it will.

Would I have read the book if I weren’t on sabbatical now? Probably still, on an otherwise ‘lost time’ intercontinental trip to a conference. So, overall, besides the occasional gap and one could quibble a bit here and there, the book is a nice read on the whole for any lay-person interested in learning something about the ubiquitous Web, any expert who’s using only a little corner of it, and certainly for the younger generation to get a feel for how the current Web came about and how technologies get shaped in praxis.