Tag Archives: privacy

Mum, are we there yet? Why should AI care.

Mike Loukides drew similarities between the current status of AI and children’s learning in an article I read this week.

The children I know are always curious to know where they are going, how long will it take, and how they will know when they get there. They ask others for guidance often.

Loukides wrote that if you look carefully at how humans learn, you see surprisingly little unsupervised learning.

If unsupervised learning is a prerequisite for general intelligence, but not the substance, what should we be looking for, he asked. It made me wonder is it also true that general intelligence is a prerequisite for unsupervised learning? And if so, what level of learning must AI achieve before it is capable of recursive self-improvement? What is AI being encouraged to look for as it learns, what is it learning as it looks?

What is AI looking for and how will it know when it gets there?

Loukides says he can imagine a toddler learning some rudiments of counting and addition on his or her own, but can’t imagine a child developing any sort of higher mathematics without a teacher.

I suggest a different starting point. I think children develop on their own, given a foundation. And if the foundation is accompanied by a purpose — to understand why they should learn to count, and why they should want to — and if they have the inspiration, incentive and  assets they’ll soon go off on their own, and outstrip your level of knowledge. That may or may not be with a teacher depending on what is available, cost, and how far they get compared with what they want to achieve.

It’s hard to learn something from scratch by yourself if you have no boundaries to set knowledge within and search for more, or to know when to stop when you have found it.

You’ve only to start an online course, get stuck, and try to find the solution through a search engine to know how hard it can be to find the answer if you don’t know what you’re looking for. You can’t type in search terms if you don’t know the right words to describe the problem.

I described this recently to a fellow codebar-goer, more experienced than me, and she pointed out something much better to me. Don’t search for the solution or describe what you’re trying to do, ask the search engine to find others with the same error message.

In effect she said, your search is wrong. Google knows the answer, but can’t tell you what you want to know, if you don’t ask it in the way it expects.

So what will AI expect from people and will it care if we dont know how to interrelate? How does AI best serve humankind and defined by whose point-of-view? Will AI serve only those who think most closely in AI style steps and language?  How will it serve those who don’t know how to talk about, or with it? AI won’t care if we don’t.

If as Loukides says, we humans are good at learning something and then applying that knowledge in a completely different area, it’s worth us thinking about how we are transferring our knowledge today to AI and how it learns from that. Not only what does AI learn in content and context, but what does it learn about learning?

His comparison of a toddler learning from parents — who in effect are ‘tagging’ objects through repetition of words while looking at images in a picture book — made me wonder how we will teach AI the benefit of learning? What incentive will it have to progress?

“the biggest project facing AI isn’t making the learning process faster and more efficient. It’s moving from machines that solve one problem very well (such as playing Go or generating imitation Rembrandts) to machines that are flexible and can solve many unrelated problems well, even problems they’ve never seen before.”

Is the skill to enable “transfer learning” what will matter most?

For AI to become truly useful, we need better as a global society to understand *where* it might best interface with our daily lives, and most importantly *why*.  And consider *who* is teaching and AI and who is being left out in the crowdsourcing of AI’s teaching.

Who is teaching AI what it needs to know?

The natural user interfaces for people to interact with today’s more common virtual assistants (Amazon’s Alexa, Apple’s Siri and Viv, Microsoft  and Cortana) are not just providing information to the user, but through its use, those systems are learning. I wonder what percentage of today’s  population is using these assistants, how representative are they, and what our AI assistants are being taught through their use? Tay was a swift lesson learned for Microsoft.

In helping shape what AI learns, what range of language it will use to develop its reference words and knowledge, society co-shapes what AI’s purpose will be —  and for AI providers to know what’s the point of selling it. So will this technology serve everyone?

Are providers counter-balancing what AI is currently learning from crowdsourcing, if the crowd is not representative of society?

So far we can only teach machines to make decisions based on what we already know, and what we can tell it to decide quickly against pre-known references using lots of data. Will your next image captcha, teach AI to separate the sloth from the pain-au-chocolat?

One of the task items for machine processing is better searches. Measurable goal driven tasks have boundaries, but who sets them? When does a computer know, if it’s found enough to make a decision. If the balance of material about the Holocaust on the web for example, were written by Holocaust deniers will AI know who is right? How will AI know what is trusted and by whose measure?

What will matter most is surely not going to be how to optimise knowledge transfer from human to AI — that is the baseline knowledge of supervised learning — and it won’t even be for AI to know when to use its skill set in one place and when to apply it elsewhere in a different context; so-called learning transfer, as Mike Loukides says. But rather, will AI reach the point where it cares?

  • Will AI ever care what it should know and where to stop or when it knows enough on any given subject?
  • How will it know or care if what it learns is true?
  • If in the best interests of advancing technology or through inaction  we do not limit its boundaries, what oversight is there of its implications?

Online limits will limit what we can reach in Thinking and Learning

If you look carefully at how humans learn online, I think rather than seeing  surprisingly little unsupervised learning, you see a lot of unsupervised questioning. It is often in the questioning that is done in private we discover, and through discovery we learn. Often valuable discoveries are made; whether in science, in maths, or important truths are found where there is a need to challenge the status quo. Imagine if Galileo had given up.

The freedom to think freely and to challenge authority, is vital to protect, and one reason why I and others are concerned about the compulsory web monitoring starting on September 5th in all schools in England, and its potential chilling effect. Some are concerned who  might have access to these monitoring results today or in future, if stored could they be opened to employers or academic institutions?

If you tell children do not use these search terms and do not be curious about *this* subject without repercussions, it is censorship. I find the idea bad enough for children, but for us as adults its scary.

As Frankie Boyle wrote last November, we need to consider what our internet history is:

“The legislation seems to view it as a list of actions, but it’s not. It’s a document that shows what we’re thinking about.”

Children think and act in ways that they may not as an adult. People also think and act differently in private and in public. It’s concerning that our private online activity will become visible to the State in the IP Bill — whether photographs that captured momentary actions in social media platforms without the possibility to erase them, or trails of transitive thinking via our web history — and third-parties may make covert judgements and conclusions about us, correctly or not, behind the scenes without transparency, oversight or recourse.

Children worry about lack of recourse and repercussions. So do I. Things done in passing, can take on a permanence they never had before and were never intended. If expert providers of the tech world such as Apple Inc, Facebook Inc, Google Inc, Microsoft Corp, Twitter Inc and Yahoo Inc are calling for change, why is the government not listening? This is more than very concerning, it will have disastrous implications for trust in the State, data use by others, self-censorship, and fear that it will lead to outright censorship of adults online too.

By narrowing our parameters what will we not discover? Not debate?  Or not invent? Happy are the clockmakers, and kids who create. Any restriction on freedom to access information, to challenge and question will restrict children’s learning or even their wanting to.  It will limit how we can improve our shared knowledge and improve our society as a result. The same is true of adults.

So in teaching AI how to learn, I wonder how the limitations that humans put on its scope — otherwise how would it learn what the developers want — combined with showing it ‘our thinking’ through search terms,  and how limitations on that if users self-censor due to surveillance, will shape what AI will help us with in future and will it be the things that could help the most people, the poorest people, or will it be people like those who programme the AI and use search terms and languages it already understands?

Who is accountable for the scope of what we allow AI to do or not? Who is accountable for what AI learns about us, from our behaviour data if it is used without our knowledge?

How far does AI have to go?

The leap for AI will be if and when AI can determine what it doesn’t know, and it sees a need to fill that gap. To do that, AI will need to discover a purpose for its own learning, indeed for its own being, and be able to do so without limitation from the that humans shaped its framework for doing so. How will AI know what it needs to know and why? How will it know, what it knows is right and sources to trust? Against what boundaries will AI decide what it should engage with in its learning, who from and why? Will it care? Why will it care? Will it find meaning in its reason for being? Why am I here?

We assume AI will know better. We need to care, if AI is going to.

How far are we away from a machine that is capable of recursive self-improvement, asks John Naughton in yesterday’s Guardian, referencing work by Yuval Harari suggesting artificial intelligence and genetic enhancements will usher in a world of inequality and powerful elites. As I was finishing this, I read his article, and found myself nodding, as I read the implications of new technology focus too much on technology and too little on society’s role in shaping it.

AI at the moment has a very broad meaning to the general public. Is it living with life-supporting humanoids?  Do we consider assistive search tools as AI? There is a fairly general understanding of “What is A.I., really?” Some wonder if we are “probably one of the last generations of Homo sapiens,” as we know it.

If the purpose of AI is to improve human lives, who defines improvement and who will that improvement serve? Is there a consensus on the direction AI should and should not take, and how far it should go? What will the global language be to speak AI?

As AI learning progresses, every time AI turns to ask its creators, “Are we there yet?”,  how will we know what to say?

image: Stephen Barling flickr.com/photos/cripsyduck (CC BY-NC 2.0)

Gotta know it all? Pokémon GO, privacy and behavioural research

I caught my first Pokémon and I liked it. Well, OK, someone else handed me a phone and insisted I have a go. Turns out my curve ball is pretty good. Pokémon GO is enabling all sorts of new discoveries.

Discoveries reportedly including a dead man, robbery, picking up new friends, and scrapes and bruises. While players are out hunting anime in augmented reality, enjoying the novelty, and discovering interesting fun facts about their vicinity, Pokémon GO is gathering a lot of data. It’s influencing human activity in ways that other games can only envy, taking in-game interaction to a whole new level.

And it’s popular.

But what is it learning about us as we do it?

This week questions have been asked about the depth of interaction that the app gets by accessing users’ log in credentials.

What I would like to know is what access goes in the other direction?

Google, heavily invested in AI and Machine intelligence research, has “learning systems placed at the core of interactive services in a fast changing and sometimes adversarial environment, combinations of techniques including deep learning and statistical models need to be combined with ideas from control and game theory.”

The app, which is free to download, has raised concerns over suggestions the app could access a user’s entire Google account, including email and passwords. Then it seemed it couldn’t. But Niantic is reported to have made changes to permissions to limit access to basic profile information anyway.

If Niantic gets access to data owned by Google through its use of google log in credentials, does Nantic’s investor, Google’s Alphabet, get the reverse: user data from the Google log in interaction with the app, and if so, what does Google learn through the interaction?

Who gets access to what data and why?

Brian Crecente writes that Apple, Google, Niantic likely making more on Pokémon Go than Nintendo, with 30 percent of revenue from in-app purchases on their online stores.

Next stop  is to make money from marketing deals between Niantic and the offline stores used as in-game focal points, gyms and more, according to Bryan Menegus at Gizmodo who reported Redditors had discovered decompiled code in the Android and iOS versions of Pokémon Go earlier this week “that indicated a potential sponsorship deal with global burger chain McDonald’s.”

The logical progressions of this, is that the offline store partners, i.e. McDonald’s and friends, will be making money from players, the people who get led to their shops, restaurants and cafes where players will hang out longer than the Pokéstop, because the human interaction with other humans, the battles between your collected creatures and teamwork, are at the heart of the game. Since you can’t visit gyms until you are level 5 and have chosen a team, players are building up profiles over time and getting social in real life. Location data that may build up patterns about the players.

This evening the two players that I spoke to were already real-life friends on their way home from work (that now takes at least an hour longer every evening) and they’re finding the real-life location facts quite fun, including that thing they pass on the bus every day, and umm, the Scientology centre. Well, more about that later**.

Every player I spotted looking at the phone with that finger flick action gave themselves away with shared wry smiles. All 30 something men. There is possibly something of a legacy in this they said, since the initial Pokémon game released 20 years ago is drawing players who were tweens then.

Since the app is online and open to all, children can play too. What this might mean for them in the offline world, is something the NSPCC picked up on here before the UK launch. Its focus  of concern is the physical safety of young players, citing the risk of in-game lures misuse. I am not sure how much of an increased risk this is compared with existing scenarios and if children will be increasingly unsupervised or not. It’s not a totally new concept. Players of all ages must be mindful of where they are playing**. Some stories of people getting together in the small hours of the night has generated some stories which for now are mostly fun. (Go Red Team.) Others are worried about hacking. And it raises all sorts of questions if private and public space is has become a Pokestop.

While the NSPCC includes considerations on the approach to privacy in a recent more general review of apps, it hasn’t yet mentioned the less obvious considerations of privacy and ethics in Pokémon GO. Encouraging anyone, but particularly children, out of their home or protected environments and into commercial settings with the explicit aim of targeting their spending. This is big business.

Privacy in Pokémon GO

I think we are yet to see a really transparent discussion of the broader privacy implications of the game because the combination of multiple privacy policies involved is less than transparent. They are long, they seem complete, but are they meaningful?

We can’t see how they interact.

Google has crowd sourced the collection of real time traffic data via mobile phones.  Geolocation data from google maps using GPS data, as well as network provider data seem necessary to display the street data to players. Apparently you can download and use the maps offline since Pokémon GO uses the Google Maps API. Google goes to “great lengths to make sure that imagery is useful, and reflects the world our users explore.” In building a Google virtual reality copy of the real world, how data are also collected and will be used about all of us who live in it,  is a little wooly to the public.

U.S. Senator Al Franken is apparently already asking Niantic these questions. He points out that Pokémon GO has indicated it shares de-identified and aggregate data with other third parties for a multitude of purposes but does not describe the purposes for which Pokémon GO would share or sell those data [c].

It’s widely recognised that anonymisation in many cases fails so passing only anonymised data may be reassuring but fail in reality. Stripping out what are considered individual personal identifiers in terms of data protection, can leave individuals with unique characteristics or people profiled as groups.

Opt out he feels is inadequate as a consent model for the personal and geolocational data that the app is collecting and passing to others in the U.S.

While the app provider would I’m sure argue that the UK privacy model respects the European opt in requirement, I would be surprised if many have read it. Privacy policies fail.

Poor practices must be challenged if we are to preserve the integrity of controlling the use of our data and knowledge about ourselves. Being aware of who we have ceded control of marketing to us, or influencing how we might be interacting with our environment, is at least a step towards not blindly giving up control of free choice.

The Pokémon GO permissions “for the purpose of performing services on our behalf“, “third party service providers to work with us to administer and provide the Services” and  “also use location information to improve and personalize our Services for you (or your authorized child)” are so broad as they could mean almost anything. They can also be changed without any notice period. It’s therefore pretty meaningless. But it’s the third parties’ connection, data collection in passing, that is completely hidden from players.

If we are ever to use privacy policies as meaningful tools to enable consent, then they must be transparent to show how a chain of permissions between companies connect their services.

Otherwise they are no more than get out of jail free cards for the companies that trade our data behind the scenes, if we were ever to claim for its misuse.  Data collectors must improve transparency.

Behavioural tracking and trust

Covert data collection and interaction is not conducive to user trust, whether through a failure to communicate by design or not.

By combining location data and behavioural data, measuring footfall is described as “the holy grail for retailers and landlords alike” and it is valuable.  “Pavement Opportunity” data may be sent anonymously, but if its analysis and storage provides ways to pitch to people, even if not knowing who they are individually, or to groups of people, it is discriminatory and potentially invisibly predatory. The pedestrian, or the player, Jo Public, is a commercial opportunity.

Pokémon GO has potential to connect the opportunity for profit makers with our pockets like never before. But they’re not alone.

Who else is getting our location data that we don’t sign up for sharing “in 81 towns and cities across Great Britain?

Whether footfall outside the shops or packaged as a game that gets us inside them, public interest researchers and commercial companies alike both risk losing our trust if we feel used as pieces in a game that we didn’t knowingly sign up to. It’s creepy.

For children the ethical implications are even greater.

There are obligations to meet higher legal and ethical standards when processing children’s data and presenting them marketing. Parental consent requirements fail children for a range of reasons.

So far, the UK has said it will implement the EU GDPR. Clear and affirmative consent is needed. Parental consent will be required for the processing of personal data of children under age 16. EU Member States may lower the age requiring parental consent to 13, so what that will mean for children here in the UK is unknown.

The ethics of product placement and marketing rules to children of all ages go out the window however, when the whole game or programme is one long animated advert. On children’s television and YouTube, content producers have turned brand product placement into programmes: My Little Pony, Barbie, Playmobil and many more.

Alice Webb, Director of BBC Children’s and BBC North,  looked at some of the challenges in this as the BBC considers how to deliver content for children whilst adapting to technological advances in this LSE blog and the publication of a new policy brief about families and ‘screen time’, by Alicia Blum-Ross and Sonia Livingstone.

So is this augmented reality any different from other platforms?

Yes because you can’t play the game without accepting the use of the maps and by default some sacrifice of your privacy settings.

Yes because the ethics and implications of of putting kids not simply in front of a screen that pitches products to them, but puts them physically into the place where they can consume products – if the McDonalds story is correct and a taster of what will follow – is huge.

Boundaries between platforms and people

Blum-Ross says, “To young people, the boundaries and distinctions that have traditionally been established between genres, platforms and devices mean nothing; ditto the reasoning behind the watershed system with its roots in decisions about suitability of content. “

She’s right. And if those boundaries and distinctions mean nothing to providers, then we must have that honest conversation with urgency. With our contrived consent, walking and running and driving without coercion, we are being packaged up and delivered right to the door of for-profit firms, paying for the game with our privacy. Smart cities are exploiting street sensors to do the same.

Freewill is at the very heart of who we are. “The ability to choose between different possible courses of action. It is closely linked to the concepts of responsibility, praise, guilt, sin, and other judgments which apply only to actions that are freely chosen.” Free choice of where we shop, what we buy and who we interact with is open to influence. Influence that is not entirely transparent presents opportunity for hidden manipulation, while the NSPCC might be worried about the risk of rare physical threat, the potential for the influencing of all children’s behaviour, both positive and negative, reaches everyone.

Some stories of how behaviour is affected, are heartbreakingly positive. And I met and chatted with complete strangers who shared the joy of something new and a mutual curiosity of the game. Pokémon GOis clearly a lot of fun. It’s also unclear on much more.

I would like to explicitly understand if Pokémon GO is gift packaging behavioural research by piggybacking on the Google platforms that underpin it, and providing linked data to Google or third parties.

Fishing for frequent Pokémon encourages players to ‘check in’ and keep that behaviour tracking live. 4pm caught a Krabby in the closet at work. 6pm another Krabby. Yup, still at work. 6.32pm Pidgey on the street outside ThatGreenCoffeeShop. Monday to Friday.

The Google privacy policies changed in the last year require ten clicks for opt out, and in part, the download of an add-on. Google has our contacts, calendar events, web searches, health data, has invested in our genetics, and all the ‘Things that make you “you”. They have our history, and are collecting our present. Machine intelligence work on prediction, is the future. For now, perhaps that will be pinging you with a ‘buy one get one free’ voucher at 6.20, or LCD adverts shifting as you drive back home.

Pokémon GO doesn’t have to include what data Google collects in its privacy policy. It’s in Google’s privacy policy. And who really read that when it came out months ago, or knows what it means in combination with new apps and games we connect it with today? Tracking and linking data on geolocation, behavioural patterns, footfall, whose other phones are close by,  who we contact, and potentially even our spend from Google wallet.

Have Google and friends of Niantic gotta know it all?

The illusion that might cheat us: ethical data science vision and practice

This blog post is also available as an audio file on soundcloud.


Anais Nin, wrote in her 1946 diary of the dangers she saw in the growth of technology to expand our potential for connectivity through machines, but diminish our genuine connectedness as people. She could hardly have been more contemporary for today:

“This is the illusion that might cheat us of being in touch deeply with the one breathing next to us. The dangerous time when mechanical voices, radios, telephone, take the place of human intimacies, and the concept of being in touch with millions brings a greater and greater poverty in intimacy and human vision.”
[Extract from volume IV 1944-1947]

Echoes from over 70 years ago, can be heard in the more recent comments of entrepreneur Elon Musk. Both are concerned with simulation, a lack of connection between the perceived, and reality, and the jeopardy this presents for humanity. But both also have a dream. A dream based on the positive potential society has.

How will we use our potential?

Data is the connection we all have between us as humans and what machines and their masters know about us. The values that masters underpin their machine design with, will determine the effect the machines and knowledge they deliver, have on society.

In seeking ever greater personalisation, a wider dragnet of data is putting together ever more detailed pieces of information about an individual person. At the same time data science is becoming ever more impersonal in how we treat people as individuals. We risk losing sight of how we respect and treat the very people whom the work should benefit.

Nin grasped the risk that a wider reach, can mean more superficial depth. Facebook might be a model today for the large circle of friends you might gather, but how few you trust with confidences, with personal knowledge about your own personal life, and the privilege it is when someone chooses to entrust that knowledge to you. Machine data mining increasingly tries to get an understanding of depth, and may also add new layers of meaning through profiling, comparing our characteristics with others in risk stratification.
Data science, research using data, is often talked about as if it is something separate from using information from individual people. Yet it is all about exploiting those confidences.

Today as the reach has grown in what is possible for a few people in institutions to gather about most people in the public, whether in scientific research, or in surveillance of different kinds, we hear experts repeatedly talk of the risk of losing the valuable part, the knowledge, the insights that benefit us as society if we can act upon them.

We might know more, but do we know any better? To use a well known quote from her contemporary, T S Eliot, ‘Where is the wisdom we have lost in knowledge? Where is the knowledge we have lost in information?’

What can humans achieve? We don’t yet know our own limits. What don’t we yet know?  We have future priorities we aren’t yet aware of.

To be able to explore the best of what Nin saw as ‘human vision’ and Musk sees in technology, the benefits we have from our connectivity; our collaboration, shared learning; need to be driven with an element of humility, accepting values that shape  boundaries of what we should do, while constantly evolving with what we could do.

The essence of this applied risk is that technology could harm you, more than it helps you. How do we avoid this and develop instead the best of what human vision makes possible? Can we also exceed our own expectations of today, to advance in moral progress?

Continue reading The illusion that might cheat us: ethical data science vision and practice

Can new datasharing laws win social legitimacy, public trust and support without public engagement?

I’ve been struck by stories I’ve heard on the datasharing consultation, on data science, and on data infrastructures as part of ‘government as a platform’ (#GaaPFuture) in recent weeks. The audio recorded by the Royal Statistical Society on March 17th is excellent, and there were some good questions asked.

There were even questions from insurance backed panels to open up more data for commercial users, and calls for journalists to be seen as accredited researchers, as well as to include health data sharing. Three things that some stakeholders, all users of data, feel are  missing from consultation, and possibly some of those with the most widespread public concern and lowest levels of public trust. [1]

What I feel is missing in consultation discussions are:

  1. a representative range of independent public voice
  2. a compelling story of needs – why tailored public services benefits citizens from whom data is taken, not only benefits data users
  3. the impacts we expect to see in local government
  4. any cost/risk/benefit assessment of those impacts, or for citizens
  5. how the changes will be independently evaluated – as some are to be reviewed

The Royal Statistical Society and ODI have good summaries here of their thoughts, more geared towards the statistical and research aspects of data,  infrastructure and the consultation.

I focus on the other strands that use identifiable data for targeted interventions. Tailored public services, Debt, Fraud, Energy Companies’ use. I think we talk too little of people, and real needs.

Why the State wants more datasharing is not yet a compelling story and public need and benefit seem weak.

So far the creation of new data intermediaries, giving copies of our personal data to other public bodies  – and let’s be clear that this often means through commercial representatives like G4S, Atos, Management consultancies and more –  is yet to convince me of true public needs for the people, versus wants from parts of the State.

What the consultation hopes to achieve, is new powers of law, to give increased data sharing increased legal authority. However this alone will not bring about the social legitimacy of datasharing that the consultation appears to seek through ‘open policy making’.

Legitimacy is badly needed if there is to be public and professional support for change and increased use of our personal data as held by the State, which is missing today,  as care.data starkly exposed. [2]

The gap between Social Legitimacy and the Law

Almost 8 months ago now, before I knew about the datasharing consultation work-in-progress, I suggested to BIS that there was an opportunity for the UK to drive excellence in public involvement in the use of public data by getting real engagement, through pro-active consent.

The carrot for this, is achieving the goal that government wants – greater legal clarity, the use of a significant number of consented people’s personal data for complex range of secondary uses as a secondary benefit.

It was ignored.

If some feel entitled to the right to infringe on citizens’ privacy through a new legal gateway because they believe the public benefit outweighs private rights, then they must also take on the increased balance of risk of doing so, and a responsibility to  do so safely. It is in principle a slippery slope. Any new safeguards and ethics for how this will be done are however unclear in those data strands which are for targeted individual interventions. Especially if predictive.

Upcoming discussions on codes of practice [which have still to be shared] should demonstrate how this is to happen in practice, but codes are not sufficient. Laws which enable will be pushed to their borderline of legal and beyond that of ethical.

In England who would have thought that the 2013 changes that permitted individual children’s data to be given to third parties [3] for educational purposes, would mean giving highly sensitive, identifiable data to journalists without pupils or parental consent? The wording allows it. It is legal. However it fails the DPA Act legal requirement of fair processing.  Above all, it lacks social legitimacy and common sense.

In Scotland, there is current anger over the intrusive ‘named person’ laws which lack both professional and public support and intrude on privacy. Concerns raised should be lessons to learn from in England.

Common sense says laws must take into account social legitimacy.

We have been told at the open policy meetings that this change will not remove the need for informed consent. To be informed, means creating the opportunity for proper communications, and also knowing how you can use the service without coercion, i.e. not having to consent to secondary data uses in order to get the service, and knowing to withdraw consent at any later date. How will that be offered with ways of achieving the removal of data after sharing?

The stick for change, is the legal duty that the recent 2015 CJEU ruling reiterating the legal duty to fair processing [4] waved about. Not just a nice to have, but State bodies’ responsibility to inform citizens when their personal data are used for purposes other than those for which those data had initially been consented and given. New legislation will not  remove this legal duty.

How will it be achieved without public engagement?

Engagement is not PR

Failure to act on what you hear from listening to the public is costly.

Engagement is not done *to* people, don’t think explain why we need the data and its public benefit’ will work. Policy makers must engage with fears and not seek to dismiss or diminish them, but acknowledge and mitigate them by designing technically acceptable solutions. Solutions that enable data sharing in a strong framework of privacy and ethics, not that sees these concepts as barriers. Solutions that have social legitimacy because people support them.

Mr Hunt’s promised February 2014 opt out of anonymised data being used in health research, has yet to be put in place and has had immeasurable costs for delayed public research, and public trust.

How long before people consider suing the DH as data controller for misuse? From where does the arrogance stem that decides to ignore legal rights, moral rights and public opinion of more people than those who voted for the Minister responsible for its delay?

 

This attitude is what fails care.data and the harm is ongoing to public trust and to confidence for researchers’ continued access to data.

The same failure was pointed out by the public members of the tiny Genomics England public engagement meeting two years ago in March 2014, called to respond to concerns over the lack of engagement and potential harm for existing research. The comms lead made a suggestion that the new model of the commercialisation of the human genome in England, to be embedded in the NHS by 2017 as standard clinical practice, was like steam trains in Victorian England opening up the country to new commercial markets. The analogy was felt by the lay attendees to be, and I quote, ‘ridiculous.’

Exploiting confidential personal data for public good must have support and good two-way engagement if it is to get that support, and what is said and agreed must be acted on to be trustworthy.

Policy makers must take into account broad public opinion, and that is unlikely to be submitted to a Parliamentary consultation. (Personally, I first knew such  processes existed only when care.data was brought before the Select Committee in 2014.) We already know what many in the public think about sharing their confidential data from the work with care.data and objections to third party access, to lack of consent. Just because some policy makers don’t like what was said, doesn’t make that public opinion any less valid.

We must bring to the table the public voice from past but recent public engagement work on administrative datasharing [5], the voice of the non-research community, and from those who are not stakeholders who will use the data but the ‘data subjects’, the public  whose data are to be used.

Policy Making must be built on Public Trust

Open policy making is not open just because it says it is. Who has been invited, participated, and how their views actually make a difference on content and implementation is what matters.

Adding controversial ideas at the last minute is terrible engagement, its makes the process less trustworthy and diminishes its legitimacy.

This last minute change suggests some datasharing will be dictated despite critical views in the policy making and without any public engagement. If so, we should ask policy makers on what mandate?

Democracy depends on social legitimacy. Once you lose public trust, it is not easy to restore.

Can new datasharing laws win social legitimacy, public trust and support without public engagement?

In my next post I’ll post look at some of the public engagement work done on datasharing to date, and think about ethics in how data are applied.

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References:

[1] The Royal Statistical Society data trust deficit

[2] “The social licence for research: why care.data ran into trouble,” by Carter et al.

[3] FAQs: Campaign for safe and ethical National Pupil Data

[4] CJEU Bara 2015 Ruling – fair processing between public bodies

[5] Public Dialogues using Administrative data (ESRC / ADRN)

img credit: flickr.com/photos/internetarchivebookimages/

On the Boundaries of Being Human and Big Data

Atlas, the Boston Dynamics created robot, won hearts and minds this week as it stoically survived man being mean.  Our collective human response was an emotional defence of the machine, and criticism of its unfair treatment by its tester.

Some on Twitter recalled the incident of Lord of The Flies style bullying by children in Japan that led the programmers to create an algorithm for ‘abuse avoidance’.

The concepts of fairness and of decision making algorithms for ‘abuse avoidance’ are interesting from perspectives of data mining, AI and the wider access to and use of tech in general, and in health specifically.

If the decision to avoid abuse can be taken out of an individual’s human hands and are based on unfathomable amounts of big data, where are its limits applied to human behaviour and activity?

When it is decided that an individual’s decision making capability is impaired or has been forfeited their consent may be revoked in their best interest.

Who has oversight of the boundaries of what is acceptable for one person, or for an organisation, to decide what is in someone else’s best interest, or indeed, the public interest?

Where these boundaries overlap – personal abuse avoidance, individual best interest and the public interest – and how society manage them, with what oversight, is yet to be widely debated.

The public will shortly be given the opportunity to respond to plans for the expansion of administrative datasharing in England through consultation.

We must get involved and it must be the start of a debate and dialogue not simply a tick-box to a done-deal, if data derived from us are to be used as a platform for future to “achieve great results for the NHS and everyone who depends on it.”

Administering applied “abuse avoidance” and Restraining Abilities

Administrative uses and secondary research using the public’s personal data are applied not only in health, but across the board of public bodies, including big plans for tech in the justice system.

An example in the news this week of applied tech and its restraint on human behaviour was ankle monitors.  While one type was abandoned by the MOJ at a cost of £23m on the same day more funding for transdermal tags was announced in London.

The use of this technology as a monitoring tool, should not of itself be a punishment. It is said compliance is not intended to affect the dignity of individuals who are being monitored, but through the collection of personal and health data  will ensure the deprivation of alcohol – avoiding its abuse for a person’s own good and in the public interest. Is it fair?

Abstinence orders might be applied to those convicted of crimes such as assault, being drunk and disorderly and drunk driving.

We’re yet to see much discussion of how these varying degrees of integration of tech with the human body, and human enhancement will happen through robot elements in our human lives.

How will the boundaries of what is possible and desirable be determined and by whom with what oversight?

What else might be considered as harmful as alcohol to individuals and to  society? Drugs? Nictotine? Excess sugar?

As we wonder about the ethics of how humanoids will act and the aesthetics of how human they look, I wonder how humane are we being, in all our ‘public’ tech design and deployment?

Umberto Eco who died on Friday wrote in ‘The birth of ethics’ that there are universal ideas on constraints, effectively that people should not harm other people, through deprivation, restrictions or psychological torture. And that we should not impose anything on others that “diminishes or stifles our capacity to think.”

How will we as a society collectively agree what that should look like, how far some can impose on others, without consent?

Enhancing the Boundaries of Being Human

Technology might be used to impose bodily boundaries on some people, but tech can also be used for the enhancement of others. retweeted this week, the brilliant Angel Giuffria’s arm.

While the technology in this case is literally hands-on in its application, increasingly it is not the technology itself but the data that it creates or captures which enables action through data-based decision making.

Robots that are tiny may be given big responsibilities to monitor and report massive amounts of data. What if we could swallow them?

Data if analysed and understood, become knowledge.

Knowledge can be used to inform decisions and take action.

So where are the boundaries of what data may be extracted,  information collated, and applied as individual interventions?

Defining the Boundaries of “in the Public Interest”

Where are boundaries of what data may be created, stored, and linked to create a detailed picture about us as individuals, if the purpose is determined to be in the public interest?

Who decides which purposes are in the public interest? What qualifies as research purposes? Who qualifies as meeting the criteria of ‘researcher’?

How far can research and interventions go without consent?

Should security services and law enforcement agencies always be entitled to get access to individuals’ data ‘in the public interest’?

That’s something Apple is currently testing in the US.

Should research bodies always be entitled to get access to individuals’ data ‘in the public interest’?

That’s something care.data tried and failed to assume the public supported and has yet to re-test. Impossible before respecting the opt out that was promised over two years ago in March 2014.

The question how much data research bodies may be ‘entitled to’ will be tested again in the datasharing consultation in the UK.

How data already gathered are used in research may be used differently from it is when we consent to its use at colllection. How this changes over time and its potential for scope creep is seen in Education. Pupil data has gone from passive collection of name to giving it out to third parties, to use in national surveys, so far.

And what of the future?

Where is the boundary between access and use of data not in enforcement of acts already committed but in their prediction and prevention?

If you believe there should be an assumption of law enforcement access to data when data are used for prediction and prevention, what about health?

Should there be any difference between researchers’ access to data when data are used for past analysis and for use in prediction?

If ethics define the boundary between what is acceptable and where actions by one person may impose something on another that “diminishes or stifles our capacity to think” – that takes away our decision making capacity – that nudges behaviour, or acts on behaviour that has not yet happened, who decides what is ethical?

How does a public that is poorly informed about current data practices, become well enough informed to participate in the debate of how data management should be designed today for their future?

How Deeply Mined should our Personal Data be?

The application of technology, non-specific but not yet AI, was also announced this week in the Google DeepMind work in the NHS.

Its first key launch app co-founder provided a report that established the operating framework for the Behavioural Insights Team established by Prime Minister David Cameron.

A number of highly respected public figures have been engaged to act in the public interest as unpaid Independent Reviewers of Google DeepMind Health. It will be interesting to see what their role is and how transparent its workings and public engagement will be.

The recent consultation on the NHS gave overwhelming feedback that the public does not support the direction of current NHS change. Even having removed all responses associated with ‘lefty’ campaigns, concerns listed on page 11, are consistent including a request the Government “should end further involvement of the private sector in healthcare”. It appears from the response that this engagement exercise will feed little into practice.

The strength of feeling should however be a clear message to new projects that people are passionate that equal access to healthcare for all matters and that the public wants to be informed and have their voices heard.

How will public involvement be ensured as complexity increases in these healthcare add-ons and changing technology?

Will Google DeepMind pave the way to a new approach to health research? A combination of ‘nudge’ behavioural insights, advanced neural networks, Big Data and technology is powerful. How will that power be used?

I was recently told that if new research is not pushing the boundaries of what is possible and permissible then it may not be worth doing, as it’s probably been done before.

Should anything that is new that becomes possible be realised?

I wonder how the balance will be weighted in requests for patient data and their application, in such a high profile project.

Will NHS Research Ethics Committees turn down research proposals in-house in hospitals that benefit the institution or advance their reputation, or the HSCIC, ever feel able to say no to data use by Google DeepMind?

Ethics committees safeguard the rights, safety, dignity and well-being of research participants, independently of research sponsors whereas these representatives are not all independent of commercial supporters. And it has not claimed it’s trying to be an ethics panel. But oversight is certainly needed.

The boundaries of ownership between what is seen to benefit commercial and state in modern health investment is perhaps more than blurred to an untrained eye. Genomics England – the government’s flagship programme giving commercial access to the genome of 100K people –  stockholding companies, data analytics companies, genome analytic companies, genome collection, and human tissue research, commercial and academic research,  often share directors, working partnerships and funders. That’s perhaps unsurprising given such a specialist small world.

It’s exciting to think of the possibilities if, “through a focus on patient outcomes, effective oversight, and the highest ethical principles, we can achieve great results for the NHS and everyone who depends on it.”

Where will an ageing society go, if medics can successfully treat more cancer for example? What diseases will be prioritised and others left behind in what is economically most viable to prevent? How much investment will be made in diseases of the poor or in countries where governments cannot afford to fund programmes?

What will we die from instead? What happens when some causes of ‘preventative death’ are deemed more socially acceptable than others? Where might prevention become socially enforced through nudging behaviour into new socially acceptable or ethical norms?

Don’t be Evil

Given the leading edge of the company and its curiosity-by-design to see how far “can we” will reach, “don’t be evil” may be very important. But “be good” might be better. Where is that boundary?

The boundaries of what ‘being human’ means and how Big Data will decide and influence that, are unclear and changing. How will the law and regulation keep up and society be engaged in support?

Data principles such as fairness, keeping data accurate, complete and up-to-date and ensuring data are not excessive retained for no longer than necessary for the purpose are being widely ignored or exempted under the banner of ‘research’.

Can data use retain a principled approach despite this and if we accept commercial users, profit making based on public data, will those principles from academic research remain in practice?

Exempt from the obligation to give a copy of personal data to an individual on request if data are for ‘research’ purposes, data about us and our children, are extracted and stored ‘without us’. Forever. That means in a future that we cannot see, but Google DeepMind among others, is designing.

Lay understanding, and that of many climical professionals is likely to be left far behind if advanced technologies and use of big data decision-making algorithms are hidden in black boxes.

Public transparency of the use of our data and future planned purposes are needed to create trust that these purposes are wise.

Data are increasingly linked and more valuable when identifiable.

Any organisation that wants to future-proof its reputational risk will make sure data collection and use today is with consent, since future outcomes derived are likely to be in interventions for individuals or society. Catching up consent will be hard unless designed in now.

A Dialogue on the Boundaries of Being Human and Big Data

Where the commercial, personal, and public interests are blurred, the highest ethical principles are going to be needed to ensure ‘abuse avoidance’ in the use of new technology, in increased data linkage and resultant data use in research of many different kinds.

How we as a society achieve the benefits of tech and datasharing and where its boundaries lie in “the public interest” needs public debate to co-design the direction we collectively want to partake in.

Once that is over, change needs supported by a method of oversight that is responsive to new technology, data use, and its challenges.

What a channel for ongoing public dialogue, challenge and potentially recourse might look like, should be part of that debate.

Destination smart-cities: design, desire and democracy (Part four)

Who is using all this Big Data? What decisions are being made on the back of it that we never see?

In the everyday and press it often seems that the general public does not understand data, and can easily be told things which we misinterpret.

There are tools in social media influencing public discussions and leading conversations in a different direction from that it had taken, and they operate without regulation.

It is perhaps meaningful that pro-reform Wellington School last week opted out of some of the greatest uses of Big Data sharing in the UK. League tables. Citing their failures. Deciding they werein fact, a key driver for poor educational practice.”

Most often we cannot tell from the data provided what we are told those Big Data should be telling us. And we can’t tell if the data are accurate, genuine and reliable.

Yet big companies are making big money selling the dream that Big Data is the key to decision making. Cumulatively through lack of skills to spot inaccuracy, and inability to do necessary interpretation, we’re being misled by what we find in Big Data.

Being misled is devastating for public trust, as the botched beginnings of care.data found in 2014. Trust has come to be understood as vital for future based on datasharing. Public involvement in how we are used in Big Data in the future, needs to include how our data are used in order to trust they are used well. And interpreting those data well is vital. Those lessons of the past and present must be learned, and not forgotten.

It’s time to invest some time in thinking about safeguarding trust in the future, in the unknown, and the unseen.

We need to be told which private companies like Cinven and FFT have copies of datasets like HES, the entire 62m national hospital records, or the NPD, our entire schools database population of 20 million, or even just its current cohort of 8+ million.

If the public is to trust the government and public bodies to use our data well, we need to know exactly how those data are used today and all these future plans that others have for our personal data.

When we talk about public bodies sharing data they hold for administrative purposes, do we know which private companies this may mean in reality?

The UK government has big plans for big data sharing, sharing across all public bodies, some tailored for individual interventions.

While there are interesting opportunities for public benefit from at-scale systems, the public benefit is at risk not only from lack of trust in how systems gather data and use them, but that interoperability gets lost in market competition.

Openness and transparency can be absent in public-private partnerships until things go wrong. Given the scale of smart-cities, we must have more than hope that data management and security will not be one of those things.

But how will we know if new plans design well, or not?

Who exactly holds and manages those data and where is the oversight of how they are being used?

Using Big Data to be predictive and personal

How do we definde “best use of data” in “public services” right across the board in a world in which boundaries between private and public in the provision of services have become increasingly blurred?

UK researchers and police are already analysing big data for predictive factors at postcode level for those at risk or harm, for example in combining health and education data.

What has grown across the Atlantic is now spreading here. When I lived there I could already see some of what is deeply flawed.

When your system has been as racist in its policing and equity of punishment as institutionally systemic as it is in the US, years of cumulative data bias translates into ‘heat lists’ and means “communities of color will be systematically penalized by any risk assessment tool that uses criminal history as a legitimate criterion.”

How can we ensure British policing does not pursue flawed predictive policies and methodologies, without seeing them?

What transparency have our use of predictive prisons and justice data?

What oversight will the planned new increase in use of satellite tags, and biometrics access in prisons have?

What policies can we have in place to hold data-driven decision-making processes accountable?<

What tools do we need to seek redress for decisions made using flawed algorithms that are apparently indisputable?

Is government truly committed to being open and talking about how far the nudge unit work is incorporated into any government predictive data use? If not, why not?

There is a need for a broad debate on the direction of big data and predictive technology and whether the public understands and wants it.If we don’t understand, it’s time someone explained it.

If I can’t opt out of O2 picking up my travel data ad infinitum on the Tube, I will opt out of their business model and try to find a less invasive provider. If I can’t opt out of EE picking up my personal data as I move around Hyde park, it won’t be them.

Most people just want to be left alone and their space is personal.

A public consultation on smart-technology, and its growth into public space and effect on privacy could be insightful.

Feed me Seymour?

With the encroachment of integrated smart technology over our cities – our roads, our parking, our shopping, our parks, our classrooms, our TV and our entertainment, even our children’s toys – surveillance and sharing information from systems we cannot see  start defining what others may view, or decide about us, behind the scenes in everything we do.

As it expands city wide, it will be watched closely if data are to be open for public benefit, but not invade privacy if “The data stored in this infrastructure won’t be confidential.”

If the destination of digital in all parts of our lives is smart-cities then we have to collectively decide, what do we want, what do we design, and how do we keep it democratic?

What price is our freedom to decide how far its growth should reach into public space and private lives?

The cost of smart cities to individuals and the public is not what it costs in investment made by private conglomerates.

Already the cost of smart technology is privacy inside our homes, our finances, and autonomy of decision making.

Facebook and social media may run algorithms we never see that influence our mood or decision making. Influencing that decision making is significant enough when it’s done through advertising encouraging us to decide which sausages to buy for your kids tea.

It is even more significant when you’re talking about influencing voting.

Who influences most voters wins an election. If we can’t see the technology behind the influence, have we also lost sight of how democracy is decided? The power behind the mechanics of the cogs of Whitehall may weaken inexplicably as computer driven decision from the tech companies’ hidden tools takes hold.

What opportunity and risk to “every part of government” does ever expanding digital bring?

The design and development of smart technology that makes decisions for us and about us, lies in in the hands of large private corporations, not government.

The means the public-interest values that could be built by design and their protection and oversight are currently outside our control.

There is no disincentive for companies that have taken private information that is none of their business, and quite literally, made it their business to not want to collect ever more data about us. It is outside our control.

We must plan by-design for the values we hope for, for ethics, to be embedded in systems, in policies, embedded in public planning and oversight of service provision by all providers. And that the a fair framework of values is used when giving permission to private providers who operate in public spaces.

We must plan for transparency and interoperability.

We must plan by-design for the safe use of data that does not choke creativity and innovation but both protects and champions privacy as a fundamental building block of trust for these new relationships between providers of private and public services, private and public things, in private and public space.

If “digital is changing how we deliver every part of government,” and we want to “harness the best of digital and technology, and the best use of data to improve public services right across the board” then we must see integration in the planning of policy and its application.

Across the board “the best use of data” must truly value privacy, and enable us to keep our autonomy as individuals.

Without this, the cost of smart cities growing unchecked, will be an ever growing transfer of power to the funders behind corporations and campaign politics.

The ultimate price of this loss of privacy, will be democracy itself.

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This is the conclusion to a four part set of thoughts: On smart technology and data from the Sprint16 session (part one). I thought about this more in depth on “Smart systems and Public Services” here (part two), and the design and development of smart technology making “The Best Use of Data” here looking at today in a UK company case study (part three) and this part four, “The Best Use of Data” used in predictions and the Future.

Destination smart-cities: design, desire and democracy (Part three)

Smart Technology we have now: A UK Case Study

In places today, where climate surveillance sensors are used to predict and decide which smog-days cars should be banned from cities, automatic number-plate recognition (ANPR) can identify cars driving on the wrong days and send automatic penalties.

Similarly ANPR technology is used in our UK tunnels and congestion charging systems. One British company encouraging installation of ANPR in India is the same provider of a most significant part of our British public administrative data and surveillance softwares in a range of sectors.

About themselves that company says:

“Northgate Public Services has a unique experience of delivering ANPR software to all Home Office police forces. We developed and managed the NADC, the mission critical solution providing continuous surveillance of the UK’s road network.  The NADC is integrated with other databases, including the Police National Computer, and supports more than 30 million reads a day across the country.”

30 million snapshots from ‘continuous surveillance of the UK’s road network‘. That’s surprised me. That’s half the population in England, not all of whom drive. 30 million every day. It’s massive, unreasonable, and risks backlash.

Northgate Public Services’ clients also include 80% of UK water companies, as well as many other energy and utility suppliers.

And in the social housing market they stretch to debt collection, or ‘income management’.

So who I wondered, who is this company that owns all this data-driven access to our homes, our roads, our utilities, life insurance, hospital records and registeries, half of all UK calls to emergency services?

Northgate Information Solutions announced the sale of its Public Services division in December 2014 to venture capital firm Cinven. Cinven that also owns a 62% shareholding in the UK private healthcare provider Spire with all sorts of influence given their active share of services and markets. 

Not only does this private equity firm hold these vast range of data systems across a wide range of sectors, but it’s making decisions about how our public policies and money are being driven.

Using health screening data they’re even making decisions that affect our future and our behaviour and affect our private lives: software provides the information and tools that housing officers need to proactively support residents, such as sending emails, letters or rent reminders by SMS and freeing up time for face-to-face support.”

Of their ANPR systems, Northgate says the data should be even more widely used “to turn CONNECT: ANPR into a critical source of intelligence for proactive policing.”

If the company were to start to ‘proactively’ use all the data it owns across the sectors we should be asking, is ‘smart’ sensible and safe?

Where is the boundary between proactive and predictive? Or public and private?

Where do companies draw the line between public and personal space?

The public services provided by the company seem to encroach into our private lives in many ways, In Northgate’s own words, “It’s also deeply personal.”

Who’s driving decision making is clear. The source of their decision making is data. And it’s data about us.

Today already whether collected by companies proactively like ANPR or through managing data we give them with consent for direct administrative purpose, private companies are the guardians of massive amounts of our personal and public data.

What is shocking to me, is how collected data in one area of public services are also used for entirely different secondary purposes without informed consent or an FYI, for example in schools.

If we don’t know which companies manage our data, how can we trust that it is looked after well and that we are told if things go wrong?

Steps must be taken in administrative personal data security, transparency and public engagement to shore up public trust as the foundation for future datasharing as part of the critical infrastructure for any future strategy, for public or commercial application. Strategy must include more transparency of the processing of our data and public involvement, not the minimum, if ‘digital citizenship’ is to be meaningful.

How would our understanding of data improve if anyone using personal data were required to put in place clear public statements about their collection, use and analysis of data?  If the principles of data protection were actually upheld, in particular that individuals should be informed? How would our understanding of data improve especially regards automated decision making and monitoring technology? Not ninety page privacy policies. Plain English. If you need ninety pages, you’re doing too much with my data.

Independent privacy impact assessments should be mandatory and published before data are collected and shared with any party other than that to which it was given for a specific purpose. Extensions broadening that purpose should require consultation and consent. If that’s a street, then make it public in plain sight.

Above all, planning committees in local government, in policy making and practical application, need to think of data in every public decision they make and its ethical implications. We need some more robust decision-making in the face of corporate data grabs, to defend data collected in public space safe, and to keep some private.

How much less fun is a summer’s picnic spent smooching, if you feel watched? How much more anxious will we make our children if they’re not allowed to ever have their own time to themselves, and every word they type in a school computer is monitored?

How much individual creativity and innovation does that stifle? We are effectively censoring children before they have written a word.

Large corporations have played historically significant and often shadowy roles in surveillance that retrospectively were seen as unethical.

We should consider sooner rather than later, if corporations such as BAE systems, Siemens and the IMSs of the world act in ways worthy of our trust in such massive reach into our lives, with little transparency and oversight.

“Big data is big opportunity but Government should tackle misuse”

The Select Committee warned in its recent report on Big Data that distrust arising from concerns about privacy and security is often well-founded and must be resolved by industry and Government.

If ‘digital’ means smart technology in the future is used in “every part of government” as announced at #Sprint16, what will its effects be on the involvement and influence these massive corporations on democracy itself?

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I thought about this more in depth on Part one here,  “Smart systems and Public Services” here (part two), and continue after this by looking at “The Best Use of Data” used in predictions and the Future (part four).

Destination smart-cities: design, desire and democracy (Part two)

Smart cities: private reach in public space and personal lives

Smart-cities are growing in the UK through private investment and encroachment on public space. They are being built by design at home, and supported by UK money abroad, with enormous expansion plans in India for example, in almost 100 cities.

With this rapid expansion of “smart” technology not only within our living rooms but my living space and indeed across all areas of life, how do we ensure equitable service delivery, (what citizens generally want, as demonstrated by strength of feeling on the NHS) continues in public ownership, when the boundary in current policy is ever more blurred between public and private corporate ownership?

How can we know and plan by-design that the values we hope for, are good values, and that they will be embedded in systems, in policies and planning? Values that most people really care about. How do we ensure “smart” does not ultimately mean less good? That “smart” does not in the end mean, less human.

Economic benefits seem to be the key driver in current government thinking around technology – more efficient = costs less.

While using technology progressing towards replacing repetitive work may be positive, how will we accommodate for those whose skills will no longer be needed? In particular its gendered aspect, and the more vulnerable in the workforce, since it is women and other minorities who work disproportionately in our part-time, low skill jobs. Jobs that are mainly held by women, even what we think of as intrinsically human, such as carers, are being trialed for outsourcing or assistance by technology. These robots monitor people, in their own homes and reduce staffing levels and care home occupancy. We’ll no doubt hear how good it is we need fewer carers because after all, we have a shortage of care staff. We’ll find out whether it is positive for the cared, or whether they find it it less ‘human'[e]. How will we measure those costs?

The ideal future of us all therefore having more leisure time sounds fab, but if we can’t afford it, we won’t be spending more of our time employed in leisure. Some think we’ll simply be unemployed. And more people live in the slums of Calcutta than in Soho.

One of the greatest benefits of technology is how more connected the world can be, but will it also be more equitable?

There are benefits in remote sensors monitoring changes in the atmosphere that dictate when cars should be taken off the roads on smog-days, or indicators when asthma risk-factors are high.

Crowd sourcing information about things which are broken, like fix-my-street, or lifts out-of-order are invaluable in cities for wheelchair users.

Innovative thinking and building things through technology can create things which solve simple problems and add value to the person using the tool.

But what of the people that cannot afford data, cannot be included in the skilled workforce, or will not navigate apps on a phone?

How this dis-incentivises the person using the technology has not only an effect on their disappointment with the tool, but the service delivery, and potentially wider still even to societal exclusion or stigma.These were the findings of the e-red book in Glasgow explained at the Digital event in health, held at the King’s Fund in summer 2015.

Further along the scale of systems and potential for negative user experience, how do we expect citizens to react to finding punishments handed out by unseen monitoring systems, finding out our behaviour was ‘nudged’ or find decisions taken about us, without us?

And what is the oversight and system of redress for people using systems, or whose data are used but inaccurate in a system, and cause injustice?

And wider still, while we encourage big money spent on big data in our part of the world how is it contributing to solving problems for millions for whom they will never matter? Digital and social media makes increasingly transparent our one connected world, with even less excuse for closing our eyes.

Approximately 15 million girls worldwide are married each year – that’s one girl, aged under 18, married off against her will every two seconds. [Huff Post, 2015]

Tinder-type apps are luxury optional extras for many in the world.

Without embedding values and oversight into some of what we do through digital tools implemented by private corporations for profit, ‘smart’ could mean less fair, less inclusive, less kind. Less global.

If digital becomes a destination, and how much it is implemented is seen as a measure of success, by measuring how “smart” we become risks losing sight of seeing technology as solutions and steps towards solving real problems for real people.

We need to be both clever and sensible, in our ‘smart’.

Are public oversight and regulation built in to make ‘smart’ also be safe?

If there were public consultation on how “smart” society will look would we all agree if and how we want it?

Thinking globally, we need to ask if we are prioritising the wrong problems? Are we creating more tech that we already have invented solutions for place where governments are willing to spend on them? And will it in those places make the society more connected across class and improve it for all, or enhance the lives of the ‘haves’ by having more, and the ‘have-nots’ be excluded?

Does it matter how smart your TV gets, or carer, or car, if you cannot afford any of these convenient add-ons to Life v1.1?

As we are ever more connected, we are a global society, and being ‘smart’ in one area may be reckless if at the expense or ignorance of another.

People need to Understand what “Smart” means

“Consistent with the wider global discourse on ‘smart’ cities, in India urban problems are constructed in specific ways to facilitate the adoption of “smart hi-tech solutions”. ‘Smart’ is thus likely to mean technocratic and centralized, undergirded by alliances between the Indian government and hi-technology corporations.”  [Saurabh Arora, Senior Lecturer in Technology and Innovation for Development at SPRU]

Those investing in both countries are often the same large corporations. Very often, venture capitalists.

Systems designed and owned by private companies provide the information technology infrastructure that i:

the basis for providing essential services to residents. There are many technological platforms involved, including but not limited to automated sensor networks and data centres.’

What happens when the commercial and public interest conflict and who decides that they do?

Decision making, Mining and Value

Massive amounts of data generated are being mined for making predictions, decisions and influencing public policy: in effect using Big Data for research purposes.

Using population-wide datasets for social and economic research today, is done in safe settings, using deidentified data, in the public interest, and has independent analysis of the risks and benefits of projects as part of the data access process.

Each project goes before an ethics committee review to assess its considerations for privacy and not only if the project can be done, but should be done, before it comes for central review.

Similarly our smart-cities need ethics committee review assessing the privacy impact and potential of projects before commissioning or approving smart-technology. Not only assessing if they are they feasible, and that we ‘can’ do it, but ‘should’ we do it. Not only assessing the use of the data generated from the projects, but assessing the ethical and privacy implications of the technology implementation itself.

The Committee recommendations on Big Data recently proposed that a ‘Council of Data Ethics’ should be created to explicitly address these consent and trust issues head on. But how?

Unseen smart-technology continues to grow unchecked often taking root in the cracks between public-private partnerships.

We keep hearing about Big Data improving public services but that “public” data is often held by private companies. In fact our personal data for public administration has been widely outsourced to private companies of which we have little oversight.

We’re told we paid the price in terms of skills and are catching up.

But if we simply roll forward in first gear into the connected city that sees all, we may find we arrive at a destination that was neither designed nor desired by the majority.

We may find that the “revolution, not evolution”, hoped for in digital services will be of the unwanted kind if companies keep pushing more and more for more data without the individual’s consent and our collective public buy-in to decisions made about data use.

Having written all this, I’ve now read the Royal Statistical Society’s publication which eloquently summarises their recent work and thinking. But I wonder how we tie all this into practical application?

How we do governance and regulation is tied tightly into the practicality of public-private relationships but also into deciding what should society look like? That is what our collective and policy decisions about what smart-cities should be and may do, is ultimately defining.

I don’t think we are addressing in depth yet the complexity of regulation and governance that will be sufficient to make Big Data and Public Spaces safe because companies say too much regulation risks choking off innovation and creativity.

But that risk must not be realised if it is managed well.

Rather we must see action to manage the application of smart-technology in a thoughtful way quickly, because if we do not, very soon, we’ll have lost any say in how our service providers deliver.

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I began my thoughts about this in Part one, on smart technology and data from the Sprint16 session and after this (Part two), continue to look at the design and development of smart technology making “The Best Use of Data” with a UK company case study (Part three) and “The Best Use of Data” used in predictions and the Future (Part four).

Breaking up is hard to do. Restructuring education in England.

This Valentine’s I was thinking about the restructuring of education in England and its wide ranging effects. It’s all about the break up.

The US EdTech market is very keen to break into the UK, and our front door is open.

We have adopted the model of Teach First partnered with Teach America, while some worry we do not ask “What is education for?

Now we hear the next chair of Oftsed is to be sought from the US, someone who is renowned as “the scourge of the unions.”

Should we wonder how long until the management of schools themselves is US-sourced?

The education system in England has been broken up in recent years into manageable parcels  – for private organisations, schools within schools, charity arms of commercial companies, and multi-school chains to take over – in effect, recent governments have made reforms that have dismantled state education as I knew it.

Just as the future vision of education outlined in the 2005 Direct Democracy co-authored by Michael Gove said, “The first thing to do is to make existing state schools genuinely independent of the state.”

Free schools touted as giving parents the ultimate in choice, are in effect another way to nod approval to the outsourcing of the state, into private hands, and into big chains. Despite seeing the model fail spectacularly abroad, the government seems set on the same here.

Academies, the route that finagles private corporations into running public-education is the preferred model, says Mr Cameron. While there are no plans to force schools to become academies, the legislation currently in ping-pong under the theme of coasting schools enables just that. The Secretary of State can impose academisation. Albeit only on Ofsted labeled ‘failing’ schools.

What fails appears sometimes to be a school that staff and parents cannot understand as anything less than good, but small. While small can be what parents want, small pupil-teacher ratios, mean higher pupil-per teacher costs. But the direction of growth is towards ‘big’ is better’.

“There are now 87 primary schools with more than 800 pupils, up from 77 in 2014 and 58 in 2013. The number of infants in classes above the limit of 30 pupils has increased again – with 100,800 pupils in these over-sized classes, an increase of 8% compared with 2014.” [BBC]

All this restructuring creates costs about which the Department wants to be less than transparent.  And has lost track of.

If only we could see that these new structures raised standards?  But,” while some chains have clearly raised attainment, others achieve worse outcomes creating huge disparities within the academy sector.”

If not delivering better results for children, then what is the goal?

A Valentine’s view of Public Service Delivery: the Big Break up

Breaking up the State system, once perhaps unthinkable is possible through the creation of ‘acceptable’ public-private partnerships (as opposed to outright privatisation per se). Schools become academies through a range of providers and different pathways, at least to start with, and as they fail, the most successful become the market leaders in an oligopoly. Ultimately perhaps, this could become a near monopoly. Delivering ‘better’. Perhaps a new model, a new beginning, a new provider offering salvation from the flood of ‘failing’ schools coming to the State’s rescue.

In order to achieve this entry to the market by outsiders, you must first remove conditions seen as restrictive, giving more ‘freedom’ to providers; to cut corners make efficiency savings on things like food standards, required curriculum, and numbers of staff, or their pay.

And what if, as a result, staff leave, or are hard to recruit?

Convincing people that “tech” and “digital” will deliver cash savings and teach required skills through educational machine learning is key if staff costs are to be reduced, which in times of austerity and if all else has been cut, is the only budget left to slash.

Self-taught systems’ providers are convincing in their arguments that tech is the solution.

Sadly I remember when a similar thing was tried on paper. My first year of GCSE maths aged 13-14  was ‘taught’ at our secondary comp by working through booklets in a series that we self-selected from the workbench in the classroom. Then we picked up the master marking-copy once done. Many of the boys didn’t need long to work out the first step was an unnecessary waste of time. The teacher had no role in the classroom. We were bored to bits. By the final week at end of the year they sellotaped the teacher to his chair.

I kid you not.

Teachers are so much more than knowledge transfer tools, and yet by some today seem to be considered replaceable by technology.

The US is ahead of us in this model, which has grown hand-in-hand with commercialism in schools. Many parents are unhappy.

So is the DfE setting us up for future heartbreak if it wants us to go down the US route of more MOOCs, more tech, and less funding and fewer staff? Where’s the cost benefit risk analysis and transparency?

We risk losing the best of what is human from the classroom, if we will remove the values they model and inspire. Unions and teachers and educationalists are I am sure, more than aware of all these cumulative changes. However the wider public seems little engaged.

For anyone ‘in education’ these changes will all be self-evident and their balance of risks and benefits a matter of experience, and political persuasion. As a parent I’ve only come to understand these changes, through researching how our pupils’ personal and school data have been commercialised,  given away from the National Pupil Database without our consent, since legislation changed in 2013; and the Higher Education student and staff data sold.

Will more legislative change be needed to keep our private data accessible in public services operating in an increasingly privately-run delivery model? And who will oversee that?

The Education Market is sometimes referred to as ‘The Wild West’. Is it getting a sheriff?

The news that the next chair of Oftsed is to be sought from the US did set alarm bells ringing for some in the press, who fear US standards and US-led organisations in British schools.

“The scourge of unions” means not supportive of staff-based power and in health our junior doctors have clocked exactly what breaking their ‘union’ bargaining power is all about.  So who is driving all this change in education today?

Some ed providers might be seen as profiting individuals from the State break up. Some were accused of ‘questionable practices‘. Oversight has been lacking others said. Margaret Hodge in 2014 was reported to have said: “It is just wrong to hand money to a company in which you have a financial interest if you are a trustee.”

I wonder if she has an opinion on a lead non-executive board member at the Department for Education also being the director of one of the biggest school chains? Or the ex Minister now employed by the same chain? Or that his campaign was funded by the same Director?  Why this register of interests is not transparent is a wonder.

It could appear to an outsider that the private-public revolving door is well oiled with sweetheart deals.

Are the reforms begun by Mr Gove simply to be executed until their end goal, whatever that may be, through Nikky Morgan or she driving her own new policies?

If Ofsted were  to become US-experience led, will the Wild West be tamed or US providers invited to join the action, reshaping a new frontier? What is the end game?

Breaking up is not hard to do, but in whose best interest is it?

We need only look to health to see the similar pattern.

The structures are freed up, and boundaries opened up (if you make the other criteria) in the name of ‘choice’. The organisational barriers to break up are removed in the name of ‘direct accountability’. And enabling plans through more ‘business intelligence’ gathered from data sharing, well, those plans abound.

Done well, new efficient systems and structures might bring public benefits, the right technology can certainly bring great things, but have we first understood what made the old less efficient if indeed it was and where are those baselines to look back on?

Where is the transparency of the end goal and what’s the price the Department is prepared to pay in order to reach it?

Is reform in education, transparent in its ideology and how its success is being measured if not by improved attainment?

The results of change can also be damaging. In health we see failing systems and staff shortages and their knock-on effects into patient care. In schools, these failures damage children’s start in life, it’s not just a ‘system’.

Can we assess if and how these reforms are changing the right things for the right reasons? Where is the transparency of what problems we are trying to solve, to assess what solutions work?

How is change impact for good and bad being measured, with what values embedded, with what oversight, and with whose best interests at its heart?

2005’s Direct Democracy could be read as a blueprint for co-author Mr Gove’s education reforms less than a decade later.

Debate over the restructuring of education and its marketisation seems to have bypassed most of us in the public, in a way health has not.

Underperformance as measured by new and often hard to discern criteria, means takeover at unprecedented pace.

And what does this mean for our most vulnerable children? SEN children are not required to be offered places by academies. The 2005 plans co-authored by Mr Gove also included: “killing the government’s inclusion policy stone dead,” without an alternative.

Is this the direction of travel our teachers and society supports?

What happens when breakups happen and relationship goals fail?

Who picks up the pieces? I fear the state is paying heavily for the break up deals, investing heavily in new relationships, and yet will pay again for failure. And so will our teaching staff, and children.

While Mr Hunt is taking all the heat right now, for his part in writing Direct Democracy and its proposals to privatise health – set against the current health reforms and restructuring of junior doctors contracts – we should perhaps also look to Mr Gove co-author, and ask to better understand the current impact of his recent education reforms, compare them with what he proposed in 2005, and prepare for the expected outcomes of change before it happens (see p74).

One outcome was that failure was to be encouraged in this new system, and Sweden held up as an exemplary model:

“Liberating state schools would also allow the all-important freedom to fail.”

As Anita Kettunen, principal of JB Akersberga in Sweden reportedly said when the free schools chain funded by a private equity firm failed:

“if you’re going to have a system where you have a market, you have to be ready for this.”

Breaking up can be hard to do. Failure hurts. Are we ready for this?
******

 

Abbreviated on Feb 18th.

 

Monitoring software in schools: the Department for Education’s digital dream or nightmare? (2)

“Children do not lose their human rights by virtue of passing through the school gates” (UN Committee on the Rights of the Child, General Comment on ‘The aims of education’, 2001).

The Digital Skills in Schools inquiry [1] is examining the gap in education of our children to enable them to be citizens fit for the future.

We have an “educational gap” in digital skills and I have suggested it should not be seen only as functional or analytical, but should also address a gap in ethical skills and framework to equip our young people to understand their digital rights, as well as responsibilities.

Children must be enabled in education with opportunity to understand how they can grow “to develop physically, mentally, morally, spiritually and socially in a healthy and normal manner and in conditions of freedom and dignity”. [2]

Freedom to use the internet in privacy does not mean having to expose children to risks, but we should ask, are there ways of implementing practices which are more proportionate, and less intrusive than monitoring and logging keywords [3] for every child in the country? What problem is the DfE trying to solve and how?

Nicky Morgan’s “fantastic” GPS tracking App

The second technology tool Nicky Morgan mentioned in her BETT speech on January 22nd, is an app with GPS tracking and alerts creation. Her app verdict was “excellent” and “fantastic”:

“There are excellent examples at the moment such as the Family First app by Group Call. It uses GPS in mobile phones to help parents keep track of their children’s whereabouts, allowing them to check that they have arrived safely to school, alerting them if they stray from their usual schedule.” [4]

I’m not convinced tracking every child’s every move is either excellent or fantastic. Primarily because it will foster a nation of young people who feel untrusted, and I see a risk it could create a lower sense of self-reliance, self-confidence and self-responsibility.

Just as with the school software monitoring [see part one], there will be a chilling effect on children’s freedom if these technologies become the norm. If you fear misusing a word in an online search, or worry over stigma what others think, would you not change your behaviour? Our young people need to feel both secure and trusted at school.

How we use digital in schools shapes our future society

A population that trusts one another and trusts its government and organisations and press, is vital to a well functioning society.

If we want the benefits of a global society, datasharing for example to contribute to medical advance, people must understand how their own data and digital footprint fits into a bigger picture to support it.

In schools today pupils and parents are not informed that their personal confidential data are given to commercial third parties by the Department for Education at national level [5]. Preventing public engagement, hiding current practices, downplaying the risks of how data are misused, also prevents fair and transparent discussion of its benefits and how to do it better. Better, like making it accessible only in a secure setting not handing data out to Fleet Street.

For children this holds back public involvement in the discussion of the roles of technology in their own future. Fear of public backlash over poor practices must not hold back empowering our children’s understanding of digital skills and how their digital identity matters.

Digital skills are not shorthand for coding, but critical life skills

Skills our society will need must simultaneously manage the benefits to society and deal with great risks that will come with these advances in technology; advances in artificial intelligence, genomics, and autonomous robots, to select only three examples.

There is a glaring gap in their education how their own confidential personal data and digital footprint fit a globally connected society, and how they are used by commercial business and third parties.

There are concerns how apps could be misused by others too.

If we are to consider what is missing in our children’s preparations for life in which digital will no longer be a label but a way of life, then to identify the gap, we must first consider what we see as whole.

Rather than keeping children safe in education, as regards data sharing and digital privacy, the DfE seems happy to keep them ignorant. This is no way to treat our young people and develop their digital skills, just as giving their data away is not good cyber security.

What does a Dream for a  great ‘digital’ Society look like?

Had Martin Luther King lived to be 87 he would have continued to inspire hope and to challenge us to fulfill his dream for society – where everyone would have an equal opportunity for “life, liberty and the pursuit of happiness.”

Moving towards that goal, supported with technology, with ethical codes of practice, my dream is we see a more inclusive, fulfilled, sustainable and happier society. We must educate our children as fully rounded digital and data savvy individuals, who trust themselves and systems they use, and are well treated by others.

Sadly, introductions of these types of freedom limiting technologies for our children, risk instead that it may be a society in which many people do not feel comfortable, that lost sight of the value of privacy.

References:

[1] Digital Skills Inquiry: http://www.parliament.uk/business/committees/committees-a-z/commons-select/science-and-technology-committee/inquiries/parliament-2015/digital-skills-inquiry-15-16/

[2] UN Convention of the Rights of the Child

[3] Consultation: Keeping Children Safe in Education – closing Feb 16thThe “opportunities to teach safeguarding” section (para 77-78) has been updated and now says governing bodies and proprieties “should ensure” rather than “should consider” that children are taught about safeguarding, including online, through teaching and learning opportunities.

The Consultation Guidance: most relevant paragraphs 75 and 77 p 22

[4] Nicky Morgan’s full speech at BETT

[5] The defenddigitalme campaign to ask the Department forEducation to change practices and policy around The National Pupil Database