Javier D. Fernández – Green Big Data

I have a MSc and a PhD degree in Computer Science, and it’s sad (but honest) to say that in all my academic and professional career the word “privacy” was hardly mentioned. We do learn about “security” but as a mere non-functional requirement, as it is called. Don’t get me wrong, I do care about privacy and I envision a future where “ethical systems” are the rule and no longer the exception, but when people suggest, promote or ask for privacy-by-design systems, one should also understand that we engineers (at least my generation) are mostly not yet privacy-by-design educated.

That’s why, caring about privacy, I like it so much to read diverse theories and manifestos providing general principles to come up with ethical, responsible and sustainable designs for our systems, in particular where personal Big Data (and all the variants, i.e. Data Science) is involved. The Copenhague letter (promoting open humanity-centered designs to serve society), the Responsible Data Science principles (fairness, accuracy, confidentiality, and transparency) and the Ethical Design Manifesto (focused on maximizing human rights and human experience and respect human effort) are good examples, to name but a few.

Acknowledging that these are inspiring works, an engineer might find the aforementioned principles a bit too general to serve as an everyday reference guide for practitioners. In fact, one could argue that they are deliberately open for interpretation, in order to adapt them to each particular use case: they point to the goal(s) and some intermediate stones (i.e. openess or decentralization), while the work of filling up all the gaps is by no means trivial.

Digging a bit to find more fine-grained principles, I thought of the concept of Green Big Data, to refer to Big Data made and use in a “green”, healthy fashion, i.e, being human-centered, ethical, sustainable and valuable for the society. Interestingly, the closest reference for such term was a highly cited article from 2003 regarding  “green engineering” [1]. In this article, Anastas and Zimmerman inspected 12 principles to serve as a “framework for scientists and engineers to engage in when designing new materials, products, processes, and systems that are benign to human health and the environment”.

Inspired by the 12 principles of green engineering, I started an exercise to map such principles to my idea of Green Big Data. This map is by no means complete, and still subject to interpretation and discussion. Ben Wagner and my colleagues at the Privacy & Sustainable Computing Lab provided valuable feedback and encouraged me to share these principles with the community in order to start a discussion openly and widely. As an example, Axel Polleres already pointed out that “green” is interpreted here as mostly covering the privacy-aware aspect of sustainable computing, but other concepts such as “transparency-aware” (make data easy to consume) or “environmentally-aware” (avoid wasting energy by letting people run the same stuff over and over again) could be further developed.

You can find the Green Big Data principles below, looking forward for your thoughts!

 

[1] Anastas, P. & Zimmerman, J. 2003. Design through the 12 principles of green engineering. Environmental Science and Technology 37(5):94A–101A

Axel Polleres: What is “Sustainable Computing”?

Blog post written by Axel Polleres and originally posted on http://doingthingswithdata.wordpress.com/

A while ago, together with colleagues Sarah Spiekermann-Hoff, Sabrina Kirrane, and Ben Wagner (who joined in a bit later) we founded a joint research lab, to foster interdisciplinary discussions on how information systems can be build in a private, secure, ethical, value-driven, and eventually more human-centric manner.

We called this lab the Privacy & Sustainable Computing Lab to provide a platform to jointly promote and discuss our research and views and provide a think-tank on how these goals can be achieved, also open to others. Since then, we had many partially heated but first and foremost always very rewarding discussions, to create mutual understanding between researchers coming from an engineering, AI, social sciences, or legal background, on how to address challenges around digitization.

Not surprisingly, the first (and maybe still unresolved) discussion was about how to name the lab. Back then, our research was very much focused on privacy, but we all felt that the topic of societal challenges in the context of the digital age need to be viewed broader. Consequently, one of the first suggestions floating around was “Privacy-aware and Sustainable Computing Lab“, emphasizing on privacy-awareness as one of the main pillars, but with the aim for a broader definition of sustainable computing, which we later shortened to just “Privacy & Sustainable Computing Lab” (for merely length reasons, if I remember correctly, my co-founders to correct me if I am wrong 😉 ).

Towards defining Sustainable Computing

On coming up with a joint definition of the term “Sustainable Computing” back then, I answered in an internal e-mail thread that

Sustainable Computing for me encompasses obviously: 

  1. human-friendly 
  2. ecologically-friendly
  3. societally friendly 

aspects of [the design and usage of] Computing and Information Systems. In fact, in my personal understanding these three aspects are – in some contexts – potentially conflicting, but resolving and discussing these conflicts is  one points why we have founded this lab in first place.

Conflicts add Value(s)

Conflicts can arise for instance from individual well-being being weighed higher than ecologic impacts (or vice versa), or likewise in how much a society as a whole needs to respect and protect the individual’s rights and needs, and in which cases (if at all ever) the common well-being should be put above those individual rights.

These are fundamental questions in neither of which I would by any means consider myself an expert, but where obviously, if you think them into design of systems or into a technology research agenda (which would be more my home-turf), then it both adds value and makes us discuss values as such. Conflicts, that is, making value conflicts explicit and resolving conflicts about the understanding and importance of these values is a necessary  part of Sustainable Computing. This is why Sarah suggested the addition of

4. value-based

computing, as part of the definition.

Sabrina added, that although sustainable computing is not mentioned the ideas herein, the notion of Sustainable Computing resonates well with what was postulated in the Copenhagen Letter.

Overall, we haven’t finished the discussion about a crisp definition about what Sustainable Computing is (which is maybe why you don’t find it yet on our Website), but for me this is actually ok: to keep this definition evolving and agile, to keep ready for discussions about it, to keep learning from each other. We’ve also discussed sustainable computing quite extensively in a mission workshop in December 2017, to try to better define what sustainable computing is and how it influences our research.

What I learned mainly is that we as technology experts play a crucial role and carry responsibility in defining Sustainable Computing: by being able to explain limitations of technology but also as advocates of the benefits of technologies, in spite of risks and justified skepticism, and by helping developing technologies to minimize these risks.

Some Examples

Some examples of what falls for me under Sustainable computing:

  • Government Transparency through Open Data, and making such Open Data easily accessible to citizens – we try to get closer to this vision in our national research project CommuniData
  • Building technical infrastructures to support transparency in personal data processing for data subjects, but also to help companies to fulfill the respective requirements in terms of legal regulations such as the GDPR – we are working on such an infrastructure in our EU H2020 project SPECIAL
  • Building standard model processes for value-based, ethical system design, as the IEEE P7000 group does it (with involvement of my colleague Sarah Spiekermann).
  • Thinking about how AI can support ethics (instead of fearmongering the risks of AI) – we will shortly publish a special issue on some examples in a forthcoming volume of ACM Transactions on Internet Technologies (TOIT)
  • Studying phenomena and social behaviours online with the purpose of detecting and pinpointing biases as for example our colleagues at the Complexity Science Hub Vienna do in their work on Computational Social Sciences, understanding Systemic Risks and Socio-Economic Phenomena

Many more such examples are hopefully coming out of our lab through cross-fertilizing, interdisciplinary research and discussions in the years to come…

 

Let’s Switch! Some Simple Steps for Privacy-Activism on the Ground

by Sarah Spiekermann, Professor of Business Informatics & Author,

Vienna University of Economics and Business, Austria

Being an “activist” sounds like the next big hack in order to change society for the better; important work done by really smart and courageous people. But I wonder whether these high standards for activism suffice to really change things on the ground. I think we need more: We need activism on the ground.

What is activism on the ground?

By activism on the ground I mean all of us need to be involved: anyone who consumes products and services. Anyone who currently does not engage in any of those “rational choices” that economists ascribe to us. Lets become rational! Me, you, we all can become activists on the ground and make markets move OUR way. How? By switching! Switching from the products and services that we currently buy and use, where we feel that the companies who provide us with these services don’t deserve our money or attention or – most importantly – any information about your private life.

For the digital service world I have started to think about how to switch for quite some time. And in November last year I started a project with my Master Class in Privacy & Security at Vienna University of Business and Economics: We went out and tested the market leading Internet Services that most of us use. We looked into their privacy policies and checked to what extent they give us fair control over our data or – in contrast – hide important information from us. We benchmarked the market leaders with their privacy-friendly competitors. We looked at their privacy defaults and the information and decision control they give us over our data. To check whether switching to a privacy-friendly alternative is a realistic option. We also compared all services’ user experience (nothing is worse than functional but unusable security…). And guess what? Ethical machines are indeed out there.

So why not switch?

Here is the free benchmark study for download that gives you the overview.

Switching your messenger services

For the messenger world, I can personally recommend Signal, which works just as well as WhatsApp does; only that it is blue instead of green. I actually think that WhatsApp does not deserve to be green, because the company shares our contact network information with anyone interested in buying it. My students found that Signal’s privacy design is not quite as good as Wickr Me. I must admit that I had some trouble using Signal on my new GSMK Cryptophone where I obviously reject the idea of installing GooglePlay; but for normal phones Signal works just fine.

Switching your social network

When it comes to social networks, I quit Facebook long ago. I thought the content got a bit boring in these past 4-5 years as people have started to become more cautious in posting their really interesting stuff. I am on Twitter and find it really cool, but the company’s privacy settings and controls are not good. We did not test for Twitter addictiveness …

I signed up with diaspora* which I have known for a long time, because its architecture and early set-up was done by colleagues in the academic community. It is building on a peer-to-peer infrastructure and hence possesses the architecture of choice for a privacy-friendly social network. Not surprisingly, my students found it really good in terms of privacy.  I am not fully done with testing it myself. I certainly hate the name “diaspora”, which is associated with displacement from your homeland. The name signals too much negativity for a service that is actually meant to be a save haven. But other than that I think we should support it more. Interesting enough my students also benchmarked Ello, that is really a social network for artists by now. But as Joseph Beuys already famously proclaimed “Everyone is an artists”, right? I really support this idea! And since their privacy settings are ok (just minor default issues…), this is also an alternative for creative social nomads to start afresh.

Switching your maps service

HERE WeGo is my absolute favorite when it comes to a location service. And this bias has a LONG history, because I already knew the guys who build the service in its earliest versions back then in Berlin (at the time the company was called Gate5). Many of this service’s founding fathers were also members of the Chaos Computer Club. And guess what: when hackers build for themselves, they build really well.

For good reasons my students argue that OSMAND is a great company as well. Especially their decisional data control seems awesome. No matter what you do: Don’t waste your time throwing your location data into the capitalist hands of Google and Apple. Get rid of them! And Maps.me and Waze are not any better according to our benchmark. Location services that don’t get privacy right are the worst we can carry around with us, because letting anyone know where we are at any point in time is really stupid. If you don’t switch for the sake of privacy, switch for the sake of activism.

Switching E-Mail services

I remember when a few of my friends started to be beta-users of gmail. Everyone wanted to have an account. But ever since Google decided to not only scan all our e-mails for advertising purposes but also combine all this knowledge with everything else we do with them (including search, YouTube, etc.) As a result I turned away from the company. I do not even search with Google anymore, but use Startpage as a very good alternative.

That said, gmail is really not the only online mail provider that scans all you write and exchange with others. As soon as you handle your e-mail in the cloud with free providers you must kind of expect that this is the case. My students therefore recommend to switch to Runbox. It is a pay-for e-mail service, but the price is really affordable starting with € 1,35 per month with the smallest package and below € 5 for a really comfortable one. Also: Runbox is a hydropowered e-mail service. So you also do something good for the environment supporting them. An alternative to Runbox is Tutanota. Its usability was rated a bit weaker in comparison to Runbox, but it is available for free.

Switching Calender Systems

Calendars are next to our physical locations and contact data an important service to care about when it comes to privacy. After all, the calendar tells whether you are at home or not at a certain time. Just imagine an online calendar was hacked and your home broken into while you are not there. These fears were pretty evident in class discussions I had with my students who created the benchmark study and we therefore compared calendar apps as well. All the big service providers are really not what you want to use. Simple came up as the service of choice you can use on your phone; at least if you have an Android operating system. If you do not have the calendar on you phone or no Android, Fruux is the alternative of choice for you.

In conclusion, there are alternatives available and you can make meaningful choices about your privacy. The question is now, will you be willing to do so?

Consent Request

Olha, would you be so kind and introduce yourself and your project?

My name is Olha Drozd. I am a project related research associate at theInstitute of Management Information Systems, working on the SPECIAL (Scalable Policy-aware Linked Data Architecture For Privacy,Transparency and Compliance) project a Research and Innovation Actionfunded under the H2020-ICT-2016-1 Big Data PPP call (http://specialprivacy.eu/). At the moment, together with my colleagues,I am working on the development of the user interface (UI) for theconsent request that will be integrated into the privacy dashboard.

Would you please explain the privacy dashboard?

With the help of the privacy dashboard users would be able to access the information about what data is/was processed about them, what is/was the purpose for the data processing, and what data processors are/were involved. The users would also be able to request correction and erasure of the data, review the consent they gave for the data processing and withdraw that consent.

We have two ideas of how this dashboard could be implemented:

  1. Every company could have their own privacy dashboard installed on their infrastructure.
  2. The privacy dashboard could be a trusted intermediary between a company and a user. In that case we would have different companies that are represented in a single dashboard.

As I mentioned in the beginning, I am concentrating on the development of different versions of UI for the consent request that could be integrated into the dashboard. Our plan is to test multiple UIs with the help of user studies to identify better suitable UIs for different contexts. At the moment we are planning to develop two UIs for the consent request.

Olha, would you please tell us more about the consent request?

Before a person starts using an online service he/she should be informed about:

  • What data is processed by the service?
  • How is the data processed?
  • What is the purpose for the processing?
  • Is the data shared and with whom?
  • How is the data stored?

All this information is presented in a consent request, because the user has not only to be informed but has to give his/her consent to the processing of his/her data. We are now aiming to create a dynamic consent request, so that users have flexibility and more control over giving consent compared to all-or-nothing approach that is used by companies today. For example, if the person wants to use wearable health tracking device (e.g. for a FitBit watch) but he/she does not want to have an overview of the statistics of all day heart rate but just activity heart rate, then he/she could allow collection/processing of the data just for the purpose of displaying activity heart rate. It should be also possible to show only the relevant information for the specific situation to the user. In order to ensure that the user is not over burdened with consent requests we are planning to group similar requests into categories and ask for consent once per category. Additionally, it should be possible to adjust or revoke the consent at any time.

At the moment, the main issue for the development of the consent request is the amount of information that should be presented to and digested by a user. The general data protection regulation (GDPR) requires that the users should be presented with every detail. For example, not just the company, or the department that processes the information – the users should be able to drill down through the info. In the graph below you can see an overview of the data that should be shown to users in our small exemplifying use case scenario where a person uses health tracking wearable appliance [1]. You can see how much information users have to digest even in this small use case. Maybe for some people this detailed information could be interesting and useful, but if we consider the general public, it is known that people want to immediately use the device or service and not spend an hour reading and selecting what categories of data for what purpose they can allow to be processed. In our user studies we want to test what will happen if we give users all this information.

Olha, you have mentioned that you were palnning to develop two UIs for the consent request. Would you explain the differences between those two?

One is more technical and innovative (in a graph form) and the other one is more traditional (with tabs, like in a browser). We assume that the more traditional UI might work well with older adults and with people who are not so flexible in adapting to change, new styles and new UIs. And the more innovative one could be more popular with young people.

[1] Bonatti P., Kirrane S., Polleres A., Wenning R. (2017) Transparent Personal Data Processing: The Road Ahead. In: Tonetta S., Schoitsch E., Bitsch F. (eds) Computer Safety, Reliability, and Security. SAFECOMP 2017. Lecture Notes in Computer Science, vol 10489. Springer, Cham

Council of Europe Study on Algorithms and Human Rights published

After two years of negotiations in the Council of Europe Committee of experts on Internet Intermediaries (MSI-NET) the final documents of the expert group have finally been published. While the negations among the experts and governmental representatives in the group were not without difficulty, the final texts are relatively strong for what are still negotiated texts. Of particularly interest for experts working on the regulation of algorithms and automation is the Study on Algorithms and Human Rights which was drafted by Dr. Ben Wagner, one of the members of the lab and the Rapporteur of the Study.

The study attempts to take a broad approach to the human rights implications of algorithms, looking not just at Privacy but also Freedom of Assembly and Expression or the Right to a Fair trial in the context of the European Convention on Human Rights. While the regulatory responses suggested focus both on transparency and accountability, they also acknowledge that additional standard-setting measures and ethical frameworks will be required in order to ensure that human rights are safeguarded in automated technical systems. Here existing projects at the Lab such as P7000 or SPECIAL can provide an important contribution to the debate and ensure that not just privacy but that all human rights are safeguarded online.

The final version of the study is available to download here.

“Why RFID Chips are Like a Dog Collar” Interview with Sushant Agarwal, Privacy and Sustainable Computing Lab

 

Sushant would you please introduce yourself and tell us about your scientific work and background?

 

Sushant: My name is Sushant Agarwal. I did my Bachelor and Masters in India in Aerospace Engineering at the Indian Institute of Technology Bombay.During this time, I did an internships at the University of Cambridge where I worked on a project related to RFID. There I had to carry several RFID enabled cards – key cards to unlock the university doors, college main entrance, my dorm room and also an id-card for a library. I used to wonder why they don’t just create one RFID chip which would work for everything. Later, I started my thesis which dealt with machine learning. This was the time I started thinking about privacy and how centralisation is not always a good approach. After my studies, I got an opportunity here to work on a project that combined both privacy and RFID.

Would you tell us a little more about this project?

The EU project which was called SERAMIS (Sensor-Enabled Real-World Awareness for Management Information Systems) has been dealing with the use of RFID in fashion retail. My work focused more on the privacy aspects. If you look at clothes that you buy from big fashion retailers, along with the price tags there can be RFID chips as well, which are slowly replacing the security tags or the fancy colour bombs they were using before.

Would you also tell us about the tool you created at the Lab called “PriWUcy”?

This was part of the SERAMIS project as well. We had to develop a tool for Privacy Impact Assessments. When we started developing this tool the landscape of data protection related regulation changed to the General Data Protection Regulation (GDPR). Because of this regulatory change a lot of things in our Privacy Impact Assessment tool had to be adjusted. This was the time when we thought about a sustainable solution and came up with the idea to model the legislation in a machine-readable way in order to easily update the tool based on the changes in the interpretation of the GDPR.

 

Sushant, what is privacy for you?

For me personally, privacy is all about control. I want to have the ultimate control of my data. At least I should be allowed to say who should get my data, as well as what kind of data they should have access to. So it shouldn’t be like logging in online and starting Facebook in one of your tabs and then Facebook tracks you for all the rest of the websites that you browse. That is something I really hate. I try to use online services where I can have the maximum amount of control possible.

 

Would you give us an example for how you make use of your knowledge on privacy in your daily life?

 

Yes, for me the concept of smart homes is something very interesting. And to try this out on a small scale, I started out with some smart bulbs. I bought  some smart-bulbs from China to experiment with. These bulbs work using Wi-Fi and through a switch in my apartment I was communicating first with a server in China and then the server was controlling my light switch. One could say the server in China was a middleman in the process of switching on my lights. And I didn’t really like this design so I looked at some open source alternatives like https://home-assistant.io/ where I had better control and I could avoid the middleman.

 

A GlobArt Workshop at WU’s Privacy & Sustainable Computing Lab November 10, 2017

The Privacy & Sustainable Computing Lab together with GlobArt and Capital 300 hosted a Round Table discussion about artificial intelligence (AI), Ubiquitous Computing and the Question of Ethics on the 9th of November 2017 in Vienna. We were happy to have Jeffrey Sachs as our distinguished guest at this 4-hour intense Workshop on the future of AI. Other distinguished speakers were Bernhard Nessler from Johannes Kepler University Linz introducing to the limits of AI as well as Christopher Coenen unveiling the philosophical and historical roots of our desire to created artificial life.

The session and its speakers were structured by three main questions: What can general AI really do from a technical perspective?

What are the historical and philosophical roots of our desire for artificial life?

What sorts of ethical frameworks should AI adhere to?


The speakers argued that there is a need to differentiate between AI (Artificial Intelligence) and AGI (Artificial General Intelligence), where AI (like IBM Watson) needs quality training as well as quality data, lots of hardware and energy. In contrast, AGI is able to work with unstructured data and can have a better energy consumption rate. The other advantage of AGI is that it can react to un- foreseen situations and could be more easily applicable to various areas. One point that was stressed during the debate was that a lot of the terminology used in the scientific field of AI and AGI is borrowed from neuroscience and humans proper intelligence. Since machines – as experts confirmed – do not live up to this promise, using human-related terminology could lead to a misleading of the public as well as overly confident promises by industry.

It was discussed whether the term ”processing” might be more suitable than ”thinking” – at least at the current state.

Another phenomenon could be due to science fiction (Isaac Asimov, Neal Stephenson …) or Movies like ”Her” or ”Ex Machina”, where we rather should differentiate the terms AGI and Artificial Life. 
What are the socio-cultural, historical and philosophical roots of our desire to create a general artificial intelligence and to diffuse our environments with IT systems?
 ”The World, the Flesh & the Devil” a book published in 1929 by J. Desmond Bernal was a named inspiration for the concept of the ”mechanical man”. This book in turn provided an excellent introduction into the debate about transhumanism, which often goes hand in hand with the discussion about AI. Some prominent figures in technology – such as Ray Kurzweil or Elon Musk – frequently communicate transhumanistic ideas or philosophies.

What ethical guidance can we use as investors, researchers and developers or use in technical standards to ensure that AI does not get out of control? Concerning this question, there was a general agreement on the need to have some basic standards or even regulations of upcoming AI technology. Providing one example of such standards, the IEEE is working on Ethical Aligned Design guidelines under the leading phrase “Advancing Technology for Humanity.” Here particular hope is put into P7000 (Model Process for Addressing Ethical Concerns During System Design) that sets out to describe value based engineering. Value based engineering is an approach aiming to maximize value potential and minimize value harms for human beings in IT-rich environments. The ultimate goal of value based engineering is human wellbeing.

In conclusion, the event provided an excellent basis for further discussions about AI and it’s ethics for both experts and students alike.

Speakers at the Roundtable:

  • Christopher Coenen from the Institute for System Analysis and Technology Impact Assessments in Karlsruhe
  • Peter Hampson from the University of Oxford
  • Johannes Hoff from the University of London
  • Peter Lasinger from Capital 300
  • Konstantin Oppel from Xephor Solutions
  • Michael Platzer from Mostly AI
  • Bill Price who is a Resident Economist
  • Jeffrey Sachs from Columbia University
  • Robert Trappl from the Austrian Research Institute for AI
  • Georg Franck who is Professor Emeritus for Spacial Information Systems
  • Bernhard Nessler from Johannes Kepler University
  • Sarah Spiekermann – Founder of the Privacy & Sustainable Computing Lab and Professor at WU Vienna.

 

Welcome

Welcome to the new Privacy and Sustainable Computing Lab blog!

We look forward to having further blog posts listed here in the next few weeks, giving visitors to this website a better insight on what we’re doing. If you have questions about the Lab please don’t hesitate to contact: ben.wagner@wu.ac.at.