Category Archives: datasharing

AI, care.data, children, communications, datasharing, engagement

Data-Driven Responses to COVID-19: Lessons Learned OMDDAC event

A slightly longer version of a talk I gave at the launch event of the OMDDAC Data-Driven Responses to COVID-19: Lessons Learned report on October 13, 2021. I was asked to respond to the findings presented on Young People, Covid-19 and Data-Driven Decision-Making by Dr Claire Bessant at Northumbria Law School.

[ ] indicates text I omitted for reasons of time, on the day.

Their final report is now available to download from the website.

You can also watch the full event here. The part on young people presented by Claire and that I follow, is at the start.

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I’m really pleased to congratulate Claire and her colleagues today at OMDDAC and hope that policy makers will recognise the value of this work and it will influence change.

I will reiterate three things they found or included in their work.

  1. Young people want to be heard.
  2. Young people’s views on data and trust, include concerns about conflated data purposes

and

3. The concept of being, “data driven under COVID conditions”.

This OMDDAC work together with Investing in Children,  is very timely as a rapid response, but I think it is also important to set it in context, and recognize that some of its significance is that it reflects a continuum of similar findings over time, largely unaffected by the pandemic.

Claire’s work comprehensively backs up the consistent findings of over ten years of public engagement, including with young people.

The 2010 study with young people conducted by The Royal Academy of Engineering supported by three Research Councils and Wellcome, discussed attitudes towards the use of medical records and concluded: These questions and concerns must be addressed by policy makers, regulators, developers and engineers before progressing with the design, and implementation of record keeping systems and the linking of any databases.

In 2014, the House of Commons Science and Technology Committee in their report, Responsible Use of Data, said the Government has a clear responsibility to explain to the public how personal data is being used. 

The same Committee’s Big Data Dilemma 2015-16 report, (p9) concluded “data (some collected many years before and no longer with a clear consent trail) […] is unsatisfactory left unaddressed by Government and without a clear public-policy position.”

Or see

2014, The Royal Statistical Society and Ipsos Mori work on the data trust deficit with lessons for policymakers, 2019  DotEveryone’s work on Public Attitudes or the 2020 The ICO Annual Track survey results.

There is also a growing body of literature to demonstrate what the implications are being a ‘data driven’ society, for the datafied child, as described by Deborah Lupton and Ben Williamson in their own research in 2017.

[This year our own work with young people, published in our report on data metaphors “the words we use in data policy”, found that young people want institutions to stop treating data about them as a commodity and start respecting data as extracts from the stories of their lives.]

The UK government and policy makers, are simply ignoring the inconvenient truth that legislation and governance frameworks such as the UN General Comment no 25 on Children in the Digital Environment, that exist today, demand people know what is done with data about them, and it must be applied to address children’s right to be heard and to enable them to exercise their data rights.

The public perceptions study within this new OMDDAC work, shows that it’s not only the views of children and young people that are being ignored, but adults too.

And perhaps it is worth reflecting here, that often people don’t tend to think about all this in terms of data rights and data protection, but rather human rights and protections for the human being from the use of data that gives other people power over our lives.

This project, found young people’s trust in use of their confidential personal data was affected by understanding who would use the data and why, and how people will be protected from prejudice and discrimination.

We could build easy-reporting mechanisms at public points of contact with state institutions; in education, in social care, in welfare and policing, to produce reports on demand of the information you hold about me and enable corrections. It would benefit institutions by having more accurate data, and make them more trustworthy if people can see here’s what you hold on me and here’s what you did with it.

Instead, we’re going in the opposite direction. New government proposals suggest making that process harder, by charging for Subject Access Requests.

This research shows that current policy is not what young people want. People want the ability to choose between granular levels of control in the data that is being shared. They value having autonomy and control, knowing who will have access, maintaining records accuracy, how people will be kept informed of changes, who will maintain and regulate the database, data security, anonymisation, and to have their views listened to.

Young people also fear the power of data to speak for them, that the data about them are taken at face value, listened to by those in authority more than the child in their own voice.

What do these findings mean for public policy? Without respect for what people want; for the fundamental human rights and freedoms for all, there is no social license for data policies.

Whether it’s confidential GP records or the school census expansion in 2016, when public trust collapses so does your data collection.

Yet the government stubbornly refuses to learn and seems to believe it’s all a communications issue, a bit like the ‘Yes Minister’ English approach to foreigners when they don’t understand: just shout louder.

No, this research shows data policy failures are not fixed by, “communicate the benefits”.

Nor is it fixed by changing Data Protection law. As a comment in the report says, UK data protection law offers a “how-to” not a “don’t-do”.

Data protection law is designed to be enabling of data flows. But that can mean that when state data processing rightly often avoids using the lawful basis of consent in data protection terms, the data use is not consensual.

[For the sake of time, I didn’t include this thought in the next two paragraphs in the talk, but I think it is important to mention that in our own work we find that this contradiction is not lost on young people. — Against the backdrop of the efforts after the MeToo movement and lots said by Ministers in Education and at the DCMS about the Everyone’s Invited work earlier this year to champion consent in relationships, sex and health education (RSHE) curriculum; adults in authority keep saying consent matters, but don’t demonstrate it, and when it comes to data, use people’s data in ways they do not want.

The report picks up that young people, and disproportionately those communities that experience harm from authorities, mistrust data sharing with the police. This is now set against the backdrop of not only the recent, Wayne Couzens case, but a series of very public misuses of police power, including COVID powers.]

The data powers used, “Under COVID conditions” are now being used as a cover for the attack on data protections in the future. The DCMS consultation on changing UK Data Protection law, open until November 19th, suggests that similarly reduced protections on data distribution in the emergency, should become the norm. While DP law is written expressly to permit things that are out of the ordinary in extraordinary circumstances, they are limited in time. The government is proposing that some things that were found convenient to do under COVID, now become commonplace.

But it includes things such as removing Article 22 from the UK GDPR with its protections for people in processes involving automated decision making.

Young people were those who felt first hand the risks and harms of those processes in the summer of 2020, and the “mutant algorithm” is something this Observatory Report work also addressed in their research. Again, it found young people felt left out of those decisions about them despite being the group that would feel its negative effects.

[Data protection law may be enabling increased lawful data distribution across the public sector, but it is not offering people, including young people, the protections they expect of their human right to privacy. We are on a dangerous trajectory for public interest research and for society, if the “new direction” this government goes in, for data and digital policy and practice, goes against prevailing public attitudes and undermines fundamental human rights and freedoms.]

The risks and benefits of the power obtained from the use of admin data are felt disproportionately across different communities including children, who are not a one size fits all, homogenous group.

[While views across groups will differ — and we must be careful to understand any popular context at any point in time on a single issue and unconscious bias in and between groups — policy must recognise where there are consistent findings across this research with that which has gone before it. There are red lines about data re-uses, especially on conflated purposes using the same data once collected by different people, like commercial re-use or sharing (health) data with police.]

The golden thread that runs through time and across different sectors’ data use, are the legal frameworks underpinned by democratic mandates, that uphold our human rights.

I hope the powers-at-be in the DCMS consultation, and wider policy makers in data and digital policy, take this work seriously and not only listen, but act on its recommendations.

data, datasharing, deregulation, politics, privacy

When the gold standard no longer exists: data protection and trust

Last week the DCMS announced that consultation on changes to Data Protection laws is coming soon.

  • UK announces intention for new multi-billion pound global data partnerships with the US, Australia and Republic of Korea
  • International privacy expert John Edwards named as preferred new Information Commissioner to oversee shake-up
  • Consultation to be launched shortly to look at ways to increase trade and innovation through data regime.

The Telegraph reported, “Mr Dowden argues that combined, they will enable Britain to set the “gold standard” in data regulation, “but do so in a way that is as light touch as possible”.

It’s an interesting mixture of metaphors. What is a gold standard? What is light touch? These rely on assumptions in the reader to assume meaning, but don’t convey any actual content. Whether there will be substantive changes or not, we need to wait for the full announcement this month.

Oliver Dowden’s recent briefing to the Telegraph (August 25) was not the first trailer for changes that are yet to be announced. He wrote in the FT in February this year, that, “the UK has an opportunity to be at the forefront of global, data-driven growth,” and it looks like he has tried to co-opt the rights’ framing as his own.  …”the beginning of a new era in the UK — one  where we start asking ourselves not just whether we have the right to use data, but whether,  given its potential for good, we have the right not to.”

There was nothing more on that in this week’s announcement, but the focus was on international trade. The Government says it is prioritising six international agreements with “the US, Australia, Colombia, Singapore, South Korea and Dubai…but in the future it also intends to target the world’s fastest growing economies, among them, India, Brazil, Kenya and Indonesia.” (my bold)

Notably absent from the ‘fastest growing’ among them mentions’ list is China. What those included in the list have in common, is that they are countries not especially renowned for protecting human rights.

Human rights like privacy. The GDPR and in turn the UK-GDPR recognised that rights matter.  Data Protection is not designed in other regimes to be about prioritising the protection of rights but harmonisation of data in trade, and that may be where we are headed. If so, it would be out of step with how the digital environment has changed since those older laws were seen as satisfactory. But weren’t.  And the reason why the EU countries moved towards both better harmonisation *and* rights protection.

At the same time, while data protection laws increasingly align towards a high interoperable and global standard, data sovereignty and protectionism is growing too where transfers to the US remain unprotected from government surveillance.

Some countries are establishing stricter rules on the cross-border transfer of personal information, in the name of digital sovereignty, security or business growth. such as Hessen’s decision on Microsoft and “bring the data home” moves to German-based data centres.

In the big focus on data-for-trade post-Brexit fire sale,  the DCMS appears to be ignoring these risks of data distribution, despite having a good domestic case study on its doorstep in 2020. The Department for Education has been giving data away sensitive pupil data since 2012. Millions of people, including my own children, have no idea where it’s gone. The lack of respect for current law makes me wonder how I will trust that our own government, and those others we trade with, will respect our rights and risks in future trade deals.

Dowden complains in the Telegraph about the ICO that, “you don’t know if you have done something wrong until after you’ve done it”.  Isn’t that the way that enforcement usually works? Should the 2019-20 ICO audit have turned a blind eye to  the Department for Education lack of prioritisation of the rights of the named records of over 21 million pupils? Don’t forget even gambling companies had access to learners’ records of which the Department for Education claimed to be unaware. To be ignorant of law that applies to you, is a choice.

Dowden claims the changes will enable Britain to set the “gold standard” in data regulation. It’s an ironic analogy to use, since the gold standard while once a measure of global trust between countries, isn’t used by any country today. Our government sold off our physical gold over 20 years ago, after being the centre of the global gold market for over 300 years. The gold standard is a meaningless thing of the past that sounds good. A true international gold standard existed for fewer than 50 years (1871 to 1914). Why did we even need it? Because we needed a consistent trusted measure of monetary value, backed by trust in a commodity. “We have gold because we cannot trust governments,” President Herbert Hoover famously said in 1933 in his statement to Franklin D. Roosevelt. The gold standard was all about trust.

At defenddigitalme we’ve very recently been talking with young people about politicians’ use of language in debating national data policy.  Specifically, data metaphors. They object to being used as the new “oil” to “power 21st century Britain” as Dowden described it.

A sustainable national data strategy must respect human rights to be in step with what young people want. It must not go back to old-fashioned data laws only  shaped by trade and not also by human rights; laws that are not fit for purpose even in the current digital environment. Any national strategy must be forward-thinking. It otherwise wastes time in what should be an urgent debate.

In fact, such a strategy is the wrong end of the telescope from which to look at personal data at all— government should be focussing on the delivery of quality public services to support people’s interactions with the State and managing the administrative data that comes out of digital services as a by-product and externality. Accuracy. Interoperability. Registers. Audit. Rights’ management infrastructure. Admin data quality is quietly ignored while we package it up hoping no one will notice it’s really. not. good.

Perhaps Dowden is doing nothing innovative at all. If these deals are to be about admin data given away in international trade deals he is simply continuing a long tradition of selling off the family silver. The government may have got to the point where there is little left to sell. The question now would be whose family does it come from?

To use another bad metaphor, Dowden is playing with fire here if they don’t fix the issue of the future of trust. Oil and fire don’t mix well. Increased data transfers—without meaningful safeguards including minimized data collection to start with—will increase risk, and transfer that risk to you and me.

Risks of a lifetime of identity fraud are not just minor personal externalities in short term trade. They affect nation state security. Digital statecraft. Knowledge of your public services is business intelligence. Loss of trust in data collection creates lasting collective harm to data quality, with additional risk and harm as a result passed on to public health programmes and public interest research.

I’ll wait and see what the details of the plans are when announced. We might find it does little more than package up recommendations on Codes of Practice, Binding Corporate Contracts and other guidance that the EDPB has issued in the last 12 months. But whatever it looks like, so far we are yet to see any intention to put in place the necessary infrastructure of rights management that admin data requires. While we need data registers, those we had have been axed. Few new ones under the Digital Economy Act replaced them. Transparency and controls for people to exercise rights are needed if the government wants our personal data to be part of new deals.

 

img: René Magritte The False Mirror Paris 1929

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Join me at the upcoming lunchtime online event, on September 17th from 13:00 to talk about the effect of policy makers’ language in the context of the National Data Strategy: ODI Fridays: Data is not an avocado – why it matters to Gen Z https://theodi.org/event/odi-fridays-data-is-not-an-avocado-why-it-matters-to-gen-z/

datasharing, politics, privacy

Mutant algorithms, roadmaps and reports: getting real with public sector data

The CDEI has published ‘new analysis on the use of data in local government during the COVID-19 crisis’ (the Report) and it features some similarities in discussing data that the Office for AI roadmap (the Roadmap) did in January on machine learning.

A notable feature is that the CDEI work includes a public poll. Nearly a quarter of 2,000 adults said that the most important thing for them, to trust the council’s use of data, would be “a guarantee that information is anonymised before being shared, so your data can’t be linked back to you.”

Both the Report and the Roadmap shy away from or avoid that problematic gap in their conclusions, between public expectations and reality in the application of data used at scale in public service provision, especially in identifying vulnerability and risk prediction.

Both seek to provide vision and aims around the future development of data governance in the UK.

The fact is that everyone must take off their rose-tinted spectacles on data governance to accept this gap, and get basics fixed in existing practice to address it. In fact, as academic Michael Veale wrote, often the public sector is looking for the wrong solution entirely. “The focus should be on taking off the ‘tech goggles’ to identify problems, challenges and needs, and to not be afraid to discover that other policy options are superior to a technology investment.”

But used as it is, the public sector procurement and use of big data at scale, whether in AI and Machine Learning or other systems, require significant changes in approach.

The CDEI poll asked, If an organisation is using an algorithmic tool to make decisions, what do you think are the most important safeguards that they should put in place  68% rated, that humans have a key role in overseeing the decision-making process, for example reviewing automated decisions and making the final decision, in their top three safeguards.

So what is this post about? Why our arms length bodies and various organisations’ work on data strategy are hindering the attainment of the goals they claim to promote, and what needs fixed to get back on track. Accountability.

Framing the future governance of data

On Data Infrastructure and Public Trust, the AI Council Roadmap stated an ambition to, “Lead the development of data governance options and its uses. The UK should lead in developing appropriate standards to frame the future governance of data.”

To suggest we not only should be a world leader but imagine that there is the capability to do so, suggests a disconnect with current reality, none of which was mentioned in the Roadmap but is drawn out a little more in the CDEI Report from local authority workshops.

When it comes to data policy and Artificial Intelligence (AI) or Machine Learning (ML) based on data processing and therefore dependent on its infrastructure, suggesting we should lead on data governance, as if separate from the existing standards and frameworks set out in law, would be disastrous for the UK and businesses in it.  Exports need to meet standards in the receiving countries. You cannot just ‘choose your own’ adventure here.

The CDEI Report says both that participants in their workshops found a lack of legal clarity “in the collection and use of data” and, “Participants finished the Forum by discussing ways of overcoming the barriers to effective and ethical data use.”

Lack of understanding of the law is a lack of competence and capability that I have seen and heard time and time and time again in participants at workshops, events, webinars, some of whom are in charge of deciding what tools are procured and how to implement public policy using administrative data, over the last 5 years. The law on data processing is accessible and generally straightforward.

If your work involves “overcoming barriers” then either there is not competence to understand what is lawful to proceed with confidence using data protections appropriately, or you are trying to avoid doing so. Neither is a good place to be in for public authorities, and bodes badly for the safe, fair, transparent and lawful use of our personal data by them.

But it is also lack of data infrastructure that increases the skills gap and leaves a bigger need to know what is lawful or not, because if your data is held in “excessive use of excel spreadsheets” then you need to make decisions about ‘sharing’ done through distribution of data. Data access can be more easily controlled through role-based access models, that make it clear when someone is working around their assigned security role, and creates an audit trail of access. You reduce risk by distributing access, not distributing data.

The CDEI Report quotes as a ‘concern’ that data access granted under emergency powers in the pandemic will be taken away. This is a mistaken view that should be challenged. That access was *always* conditional and time limited. It is not something that will be ‘taken away’ but an exceptional use only granted because it was temporary, for exceptional purposes in exceptional times. Had it not been time limited, you wouldn’t have had access. Emergency powers in law are not ‘taken away’, but can only be granted at all in an emergency. So let’s not get caught up in artificial imaginings of what could change and what ifs, but change what we know is necessary.

We would do well to get away from the hyperbole of being world-leading, and aim for a minimum high standard of competence and capability in all staff who have any data decision-making roles and invest in the basic data infrastructure they need to do a good job.

Appropriate standards to frame the future governance of data

The AI Council Roadmap suggested that, “The UK should lead in developing appropriate standards to frame the future governance of data.”  Let’s stop and really think for a minute, what did the Roadmap writers think they meant by that?

Because we have law that frames ‘appropriate standards.’ The UK government just seems unable or unwilling to meet it. And not only in these examples, in fact I’d challenge all the business owners on the AI Council to prove their own products meet it.

You could start with the Guidelines on Automated individual decision-making and Profiling for the purposes of Regulation 2016/679 (wp251rev.01). Or consider any of the Policy, recommendations, declarations, guidelines and other legal instruments issued by Council of Europe bodies or committees on artificial intelligence. Or valuable for export standards, ensure respect for the Convention 108  standards to which we are a signed up State party among its over 50 countries, and growing. That’s all before the simplicity of the UK Data Protection Act 2018 and the GDPR.

You could start with auditing current practice for lawfulness. The CDEI Roadmap says, “The CDEI is now working in partnership with local authorities, including Bristol City Council, to help them maximise the benefits of data and data-driven technologies.” I might suggest that includes a good legal team, as I think the Council needs one.

The UK is already involved in supporting the development of guidelines (as I was alongside UK representatives of government and the data regulator the ICO among hundreds of participants in drawing out Convention 108 Guidelines on data processing in education) but to suggest as a nation state that we have the authority to speak on the future governance of data without acknowledging what we should already be doing and where we get it wrong, is an odd place to start.

The current state of reality in various sectors

Take for example the ICO audit of the Department for Education.

Failures to meet basic principles of data protection law include knowing what data they’ve got, appropriate controls on distribution and failure to fair process (tell people you process their data). This is no small stuff. And it’s only highlights from the eight page summary.

The DfE don’t adequately understand what data they hold and not having a record of processing leads to a direct breach of #GDPR. Did you know the Department is not able to tell you to which third parties your own or your child’s sensitive, identifying personal data (from over 21m records) was sent, among 1000s of releases?

The approach on data releases has been to find a way to fit the law to suit data requests, rather than assess if data distribution should be approved at all. This ICO assessment was of only 400 applications — there’s been closer to 2,000 approved since 2012. One refusal was to the US. Another the MOD.


For too long, the DfE ‘internal cultural barriers and attitudes’ has meant it hasn’t cared about your rights and freedoms or meeting its lawful obligations. That is a national government Department in charge of over fifty such mega databases, the NPD is only one of. This is a systemic and structural set of problems, as a direct result of Ministerial decisions that changed the law in 2012 to give our personal data away from state education. It was a choice made not to tell the people whom the data were about. This continues to be in breach of the law. And that is the same across many government departments.

Why does it even matter some still ask? Because there is harm to people today. There is harm in history that must not be possible to repeat. And some of the data held could be used in dangerous ways.

You only need to glance at other applications in government departments and public services to see bad policy, bad data and bad AI or machine learning outcomes. And all of those lead to breakdowns in trust and relations between people and the systems meant to support them, that in turn lead to bad data, and policy.

Unless government changes its approach, the direction of travel is towards less trust, and for public health for example, we see the consequences in disastrous responses from not attending for vaccination based on mistrust of proven data sharing, to COVID conspiracy theories.

Commercial reuse of pubic admin data is a huge mistake and the direction of travel is damaging.

“Survey responses collected from more than 3,000 people across the UK and US show that in late 2018, some 95% of people were not willing to share their medical data with commercial industries. This contrasts with a Wellcome study conducted in 2016 which found that half of UK respondents were willing to do so.” (July 2020, Imperial College)

Mutant algorithms

Summer 2020 first saw no human accountability for grades “derailed by a mutant #algorithm” — then the resignation of two  Ofqual executives. What aspects of the data governance failures will be addressed this year? Where’s the *fairness* —there is a legal duty to tell people how what data is used especially in its automated aspects.

Misplaced data and misplaced policy aims

In June 2020 The DWP argued in a court case that, “to change the way the benefit’s online computer calculation system worked in line with the original court ruling would undermine the principle of universal credit” — Not only does it fail its public interest purpose, and does harm, but is lax on its own #data governance controls. World leading is far, far, far away.

Entrenched racism

In August 2020 “The Home Office [has] agreed to stop using a computer algorithm to help decide visa applications after allegations that it contained “entrenched racism”. How did it ever get approved for use?

That entrenched racism is found in policing too. The Gangs Matrix use of data required an Enforcement Notice from the ICO and how it continues to operate at all, given its recognised discrimination and harm to young lives, is shocking.

Policy makers seem fixated on quick fixes that for the most part exist only in the marketing speak of the sellers of the products, while ignoring real problems in ethics and law, and denying harm.

“Now is a good time to stop.”

The most obvious case for me, where the Office for AI should step in, and where the CDEI Report from workshops with Local Authorities was most glaringly remiss, is where there is evidence of failure of efficacy and proven risk of danger to life through the procurement of technology in public policy. Don’t forget to ask what doesn’t work.

In January 2020  a report from researchers at The Turing institute, Rees Centre and What Works Centre published a report on ethics in Machine Learning in Children’s Social Care (CSC) and raised the “dangerous blind spots” and “lurking biases” in application of machine learning in UK children’s social care— totally unsuitable for life and death situations. Its later evidence showed models that do not work or wuld reach the threshold they set for defining ‘success’.

Out of the thirty four councils who had said they had acute difficulties in recruiting children’s social workers in December 2020 Local Government survey, 50 per cent said they had both difficulty recruiting generally and difficulty recruiting the required expertise, experience or qualification. Can staff in such challenging circumstances really have capacity to understand the limitations of developing technology on top of their every day expertise?

And when it comes to focussing on the data, there are problems too. By focusing on the data held, and using only that to make policy decisions rather than on the ground expertise, we end up in situations where only “those who get measured, get helped”.

As Michael Sanders wrote, on CSC, “Now is a good time to stop. With the global coronavirus pandemic, everything has been changed, all our data scrambled to the point of uselessness in any case.“

There is no short cut

If the Office for AI Roadmap is to be taken seriously outside its own bubble, the board need to be and be seen to be independent of government. It must engage with reality of applied AI in practice in public services, getting basics fixed first.  Otherwise all its talk of “doubling down” and suggesting the UK government can build public trust and position the UK as a ‘global leader’ on Data Governance is misleading and a waste of everyone’s time and capacity.

I appreciate that it says, “This Roadmap and its recommendations reflects the views of the Council as well as 100+ additional experts.” All of whom I imagine are more expert than me. If so, which of them is working on fixing the basic underlying problems with data governance within public sector data, how and by when? If they are not, why are they not, and who is?

The CDEI report published today identified in local authorities that, “public consultation can be a ‘nice to have’, as it often involves significant costs where budgets are already limited.” If it’s a position the CDEI does not say is flawed, it may as well pack up and go home. On page 27 it reports, “When asked about their understanding of how their local council is currently using personal data and presented with a list of possible uses, 39% of respondents reported that they do not know how their personal data is being used.” The CDEI should be flagging this with a great big red pen as an indicator of unlawful practice.

The CDEI Report also draws on the GDS Ethical Framework but that will be forever flawed as long as its own users, not the used, are the leading principle focus, underpinning the aims. It starts with “Define and understand public benefit and user need.” There’s very little about ethics and it’s much more about “justifying our project”.

The Report did not appear to have asked the attendees what impact they think their processes have on everyday lives, and social justice.

Without fixes in these approaches, we will never be world leading, but will lag behind because we haven’t built the safe infrastructure necessitated by our vast public administrative data troves. We must end bad data practice which includes getting right the basic principles on retention and data minimisation, and security (all of which would be helped if we started by reducing those ‘vast public administrative data troves’ much of which ranges from poor to abysmal data quality anyway). Start proper governance and oversight procedures. And put in place all the communication channels, tools, policy and training to make telling people how data are used and fair processing happen. It is not, a ‘nice to have’ but is required in all data processing laws around the world.

Any genuine “barriers” to data use in data protection law,  are designed as protections for people; the people the public sector, its staff and these arms length bodies are supposed to serve.

Blaming algorithms, blaming lack of clarity in the law, blaming “barriers” is avoidance of one thing. Accountability. Accountability for bad policy, bad data and bad applications of tools is a human responsibility. The systems you apply to human lives affect people, sometimes forever and in the most harmful ways.

What would I love to see led from any of these arms length bodies?

  1. An audit of existing public admin data held, by national and local government, and consistent published registers of databases and algorithms / AI / ML currently in use.
  2. Expose where your data system is nothing more than excel spreadsheets and demand better infrastructure.
  3. Identify the lawful basis for each set of data processes, their earliest records dates and content.
  4. Publish that resulting ROPA and the retention schedule.
  5. Assign accountable owners to databases, tools and the registers.
  6. Sort out how you will communicate with people whose data you unlawfully process to meet the law, or stop processing it.
  7. And above all, publish a timeline for data quality processes and show that you understand how the degradation of data accuracy, quality, and storage limitations all affect the rights and responsibilities in law that change over time, as a result.

There is no short cut, to doing a good job, but a bad one.

If organisations and bodies are serious about “good data” use in the UK, they must stop passing the buck and spreading the hype. Let’s get on with what needs fixed.

In the words of Gavin Freeguard, then let’s see how it goes.

care.data, change, change management, children, datasharing, empowerment, human rights

A fresh start for edtech? Maybe. But I wouldn’t start from here.

In 1924 the Hibbert Journal published what is accepted as the first printed copy of a well-known joke.

A genial Irishman, cutting peat in the wilds of Connemara, was once asked by a pedestrian Englishman to direct him on his way to Letterfrack. With the wonted enthusiasm of his race the Irishman flung himself into the problem and, taking the wayfarer to the top of a hill commanding a wide prospect of bogs, lakes, and mountains, proceeded to give him, with more eloquence than precision, a copious account of the route to be taken. He then concluded as follows: ‘Tis the divil’s own country, sorr, to find your way in. But a gintleman with a face like your honour’s can’t miss the road; though, if it was meself that was going to Letterfrack, faith, I wouldn’t start from here.’

Ty Goddard asked some sensible questions in TES on April 4 on the UK edTech strategy, under the overarching question, ‘A fresh start for edtech? Maybe. But the road is bumpy.’

We’d hope so, since he’s on the DfE edTech board and aims “to accelerate the edtech sector in Britain and globally.”

“The questions now being asked are whether you can protect learning at a time of national emergency? Can you truly connect educators working from home with their pupils?”

and he rightly noted that,

“One problem schools are now attempting to overcome is that many lack the infrastructure, experience and training to use digital resources to support a wholesale move to online teaching at short notice.”

He calls for “bold investment and co-ordination across Whitehall led by Downing Street to really set a sprint towards super-fast connectivity to schools, pupils’ homes and investment in actual devices for students. The Department for Education, too, has done much to think through our recent national edtech strategy – now it needs to own and explain it.”

But the own and explain it, is the same problematic starting point as care-data had in the NHS in 2014. And we know how that went.

The edTech demands and drive for the UK are not a communications issue. Nor are they simply problems of infrastructure, or the age-old idea of shipping suitable tech at scale. The ‘fresh start’ isn’t going to be what anyone wants, least of all the edTech evangelists if we start from where they are.

Demonstrators of certain programmes, platforms, and products to promote to others and drive adoption, is ‘the divil’s own country‘.

The edTech UK strategy in effect avoided online learning, and the reasons for that were not public knowledge but likely well founded. They’re mostly unevidenced and often any available research comes from the companies themselves or their partners and promoter think tanks and related, or self interested bodies.

I’ve not seen anyone yet talk about disadvantage and deprivation from not issuing course curriculum standard text books to every child.  Why on earth can secondary schools not afford to give each child their text book home? A darn sight cheaper than tech, independent of data costs and a guide to exactly what the exams will demand. Should we not seek to champion the most appropriate and equitable learning solutions, in addition to, rather than exclusively, the digital ones? GSCE children I support(ed) in foreign languages each improved once they had written materials. Getting out Chromebooks by contrast, simply interfered in the process, and wasted valuable classroom time.

Technology can deliver most vital communications, at speed and scale. It can support admin, expand learning and level the playing field through accessible tools. But done wrongly, it makes things worse than without.

Its procurement must assess any potential harmful consequences and safeguard against them, and not accept short term benefits, at the cost of long term harm. It should be safe, fair, and transparent.

“Responsible technology is no longer a nice thing to do to look good, it’s becoming a fundamental pillar of corporate business models. In a post-Cambridge Analytica world, consumers are demanding better technology and more transparency. Companies that do create those services are the ones that will have a better, brighter future.”

Kriti Sharma, VP of AI, Sage, (Doteveryone 2019 event, Responsible Technology)

The hype of ‘edTech’ achievement in the classroom so far, far outweighs the evidence of delivery. Neil Selwyn, Professor in the Faculty of Education, Monash University, Australia, writing in the Impact magazine of the Chartered College in January 2019 summed up:

“the impacts of technology use on teaching and learning remain uncertain. Andreas Schleicher – the OECD’s director of education – caused some upset in 2015 when suggesting that ICT has negligible impact on classrooms. Yet he was simply voicing what many teachers have long known: good technology use in education is very tricky to pin down.”

That won’t stop edTech being part of the mainstay of the UK export strategy post-Brexit whenever that may now be. But let’s be very clear that if the Department wants to be a world leader it shouldn’t promote products whose founders were last most notably interviewing fellow students online about their porn preferences. Or who are based in offshore organisations with very odd financial structures. Do your due diligence. Work with reputable people and organisations and build a trustworthy network of trustworthy products framed by the rule of law, that is rights’ respecting and appropriate to children. But don’t start with the products.

Above all build a strategy for education, for administrative support, for respecting rights, and for teaching in which tools that may or may not be technology-based add value; but don’t start with the product promotion.

To date the aims are to serve two masters. Our children’s education, and the UK edTech export strategy. You can if you’re prepared to do the proper groundwork, but it’s lacking right now. What is certain, is that if you get it wrong for UK children, the other will inevitably fail.

Covid19 must not be misused to direct our national edTech strategy. I wouldn’t start from here isn’t a joke, it’s a national call for change.

Here’s ten reasons where, why, and how to start instead.

1. The national edTech strategy board should start by demonstrating what it wants to see from others, with full transparency of its members, aims, terms of reference, partners and meeting minutes. There should be no need FOI to ask for them. There are much more sensitive subjects that operate in the open. It unfortunately emulates other DfE strategy, and the UK edTech network which has an in-crowd, and long standing controlling members. Both would be the richer for transparency and openness.

2. Stop bigging up the ‘Big Three’  and doing their market monopolisation for them, unless you want people to see you simply as promoting your friends’-on-the-board/foundation/ethics committee’s products. Yes,” many [educational settings] lack the infrastructure” but that should never mean encouraging ownership and delivery by only closed commercial partners.  That is the route to losing control of your state education curriculum, staff training  and (e)quality,  its delivery, risk management, data,  and cost control.

3. Start with designing for fairness in public sector systems. Minimum acceptable ethical standards could be framed around for example, accessibility, design, and restrictions on commercial exploitation and in-product advertising. This needs to be in place first, before fitting products ‘on top’ of an existing unfair, and imbalanced system, to avoid embedding disadvantage and the commodification of children in education, even further.

5. Accessibility and Internet access is a social justice issue.  Again as we’ve argued for at defenddigitalme for some time, these come *before* you promote products on top of the delivery systems:

  • Accessibility standards for all products used in state education should be defined and made compulsory in procurement processes, to ensure access for all and reduce digital exclusion.
  • All schools must be able to connect to high-speed broadband services to ensure equality of access and participation in the educational, economic, cultural and social opportunities of the world wide web.
  • Ensure a substantial improvement in support available to public and school library networks. CILIP has pointed to CIPFA figures of a net reduction of 178 libraries in England between 2009-10 and 2014-15.

6. Core national education infrastructure must be put on the national risk register, as we’ve argued for previously at defenddigitalme (see 6.6). Dependence such as MS Office 365, major cashless payment systems, and Google for Education all need assessed and to be part of the assessment for regular and exceptional delivery of education. We currently operate in the dark. And it should be unthinkable that companies get seats at the national UK edTech strategy table without full transparency over questions on their practices, policy and meeting the rule of law.

7. Shift the power balance back to schools and families, where they can trust an approved procurement route, and children and legal guardians can trust school staff to only be working with suppliers that are not overstepping the boundaries of lawful processing. Incorporate (1) the Recommendation CM/Rec(2018)7 of the Committee of Ministers to member States on Guidelines to respect, protect and fulfil the rights of the child in the digital environment  and (2) respect the UN General comment No. 16 (2013) on State obligations regarding the impact of the business sector on children’s rights, across the education and wider public sector.

8. Start with teacher training. Why on earth is the national strategy all about products, when it should be starting with people?

  • Introduce data protection and pupil privacy into basic teacher training, to support a rights-respecting environment in policy and practice, using edTech and broader data processing, to give staff the clarity, consistency and confidence in applying the high standards they need.
  • Ensure ongoing training is available and accessible to all staff for continuous professional development.
  • A focus on people, nor products, will deliver fundamental basics needed for good tech use.

9. Safe data by design and default. I’m tired of hearing from CEOs of companies that claim to be social entrepreneurs, or non-profit, or teachers who’ve designed apps, how well intentioned their products are. Show me instead. Meet the requirements of the rule of law.

  • Local systems must stop shipping out (often sensitive) pupil data at scale and speed to companies, and instead stay in control of terms and conditions, data purposes, and ban product developments for example.
  • Companies must stop using pupil data for their own purposes for profit, or to make inferences about autism or dyslexia for example, if that’s not your stated product aim, it’s likely unlawful.
  • Stop national pupil data distribution for third-party reuse. Start safe access instead.  And get the Home Office out of education.
  • Establish fair and independent oversight mechanisms of national pupil data, so that transparency and trust are consistently maintained across the public sector, and throughout the chain of data use, from collection, to the end of its life cycle, including annual data usage reports for each child.

10. We need a law that works for children’s rights. Develop a legislative framework for the fair use of a child’s digital footprint from the classroom for direct educational and administrative purposes at local level, including commercial acceptable use policies.  Build the national edTech strategy with a rights’ based framework and lawful basis in an Education and Privacy Act. Without this, you are building on sand.

AI, change management, datasharing, deregulation, ethics, GDPR, politics, privacy, trust

Policy shapers, product makers, and profit takers (1)

In 2018, ethics became the new fashion in UK data circles.

The launch of the Women Leading in AI principles of responsible AI, has prompted me to try and finish and post these thoughts, which have been on my mind for some time. If two parts of 1K is tl:dr for you, then in summary, we need more action on:

  • Ethics as a route to regulatory avoidance.
  • Framing AI and data debates as a cost to the Economy.
  • Reframing the debate around imbalance of risk.
  • Challenging the unaccountable and the ‘inevitable’.

And in the next post on:

  • Corporate Capture.
  • Corporate Accountability, and
  • Creating Authentic Accountability.

Ethics as a route to regulatory avoidance

In 2019, the calls to push aside old wisdoms for new, for everyone to focus on the value-laden words of ‘innovation’ and ‘ethics’, appears an ever louder attempt to reframe regulation and law as barriers to business, asking to cast them aside.

On Wednesday evening, at the launch of the Women Leading in AI principles of responsible AI, the chair of the CDEI said in closing, he was keen to hear from companies where, “they were attempting to use AI effectively and encountering difficulties due to regulatory structures.”

In IBM’s own words to government recently,

“A rush to further regulation can have the effect of chilling innovation and missing out on the societal and economic benefits that AI can bring.”

The vague threat is very clear, if you regulate, you’ll lose. But the the societal and economic benefits are just as vague.

So far, many talking about ethics are trying to find a route to regulatory avoidance. ‘We’ll do better,’ they promise.

In Ben Wagner’s recent paper, “Ethics as an Escape from Regulation: From ethics-washing to ethics-shopping,” he asks how to ensure this does not become the default engagement with ethical frameworks or rights-based design. He sums up, “In this world, ‘ethics’ is the new ‘industry self-regulation.”

Perhaps it’s ingenious PR to make sure that what is in effect self-regulation, right across the business model, looks like it comes imposed from others, from the very bodies set up to fix it.

But as I think about in part 2, is this healthy for UK public policy and the future not of an industry sector, but a whole technology, when it comes to AI?

Framing AI and data debates as a cost to the Economy

Companies, organisations and individuals arguing against regulation are framing the debate as if it would come at a great cost to society and the economy. But we rarely hear, what effect do they expect on their company. What’s the cost/benefit expected for them. It’s disingenuous to have only part of that conversation. In fact the AI debate would be richer were it to be included. If companies think their innovation or profits are at risk from non-use, or regulated use, and there is risk to the national good associated with these products, we should be talking about all of that.

And in addition, we can talk about use and non-use in society. Too often, the whole debate is intangible. Show me real costs, real benefits. Real risk assessments. Real explanations that speak human. Industry should show society what’s in it for them.

You don’t want it to ‘turn out like GM crops’? Then learn their lessons on transparency, trustworthiness, and avoid the hype. And understand sometimes there is simply tech, people do not want.

Reframing the debate around imbalance of risk

And while we often hear about the imbalance of power associated with using AI, we also need to talk about the imbalance of risk.

While a small false positive rate for a company product may be a great success for them, or for a Local Authority buying the service, it might at the same time, mean lives forever changed, children removed from families, and individual reputations ruined.

And where company owners may see no risk from the product they assure is safe, there are intangible risks that need factored in, for example in education where a child’s learning pathway is determined by patterns of behaviour, and how tools shape individualised learning, as well as the model of education.

Companies may change business model, ownership, and move on to other sectors after failure. But with the levels of unfairness already felt in the relationship between the citizen and State — in programmes like Troubled Families, Universal Credit, Policing, and Prevent — where use of algorithms and ever larger datasets is increasing, long term harm from unaccountable failure will grow.

Society needs a rebalance of the system urgently to promote transparent fairness in interactions, including but not only those with new applications of technology.

We must find ways to reframe how this imbalance of risk is assessed, and is distributed between companies and the individual, or between companies and state and society, and enable access to meaningful redress when risks turn into harm.

If we are to do that, we need first to separate truth from hype, public good from self-interest and have a real discussion of risk across the full range from individual, to state, to society at large.

That’s not easy against a non-neutral backdrop and scant sources of unbiased evidence and corporate capture.

Challenging the unaccountable and the ‘inevitable’.

In 2017 the Care Quality Commission reported into online services in the NHS, and found serious concerns of unsafe and ineffective care. They have a cross-regulatory working group.

By contrast, no one appears to oversee that risk and the embedded use of automated tools involved in decision-making or decision support, in children’s services, or education. Areas where AI and cognitive behavioural science and neuroscience are already in use, without ethical approval, without parental knowledge or any transparency.

Meanwhile, as all this goes on, academics many are busy debating fixing algorithmic bias, accountability and its transparency.

Few are challenging the narrative of the ‘inevitability’ of AI.

Julia Powles and Helen Nissenbaum recently wrote that many of these current debates are an academic distraction, removed from reality. It is under appreciated how deeply these tools are already embedded in UK public policy. “Trying to “fix” A.I. distracts from the more urgent questions about the technology. It also denies us the possibility of asking: Should we be building these systems at all?”

Challenging the unaccountable and the ‘inevitable’ is the title of the conclusion of the Women Leading in AI report on principles, and makes me hopeful.

“There is nothing inevitable about how we choose to use this disruptive technology. […] And there is no excuse for failing to set clear rules so that it remains accountable, fosters our civic values and allows humanity to be stronger and better.”

[1] Powles, Nissenbaum, 2018,The Seductive Diversion of ‘Solving’ Bias in Artificial Intelligence, Medium

Next: Part  2– Policy shapers, product makers, and profit takers on

  • Corporate Capture.
  • Corporate Accountability, and
  • Creating Authentic Accountability.
commercial, datasharing, deregulation, ethics, privacy, Tech, transparency, trust

Policy shapers, product makers, and profit takers (2)

Corporate capture

Companies are increasingly in controlling positions of the tech narrative in the press. They are funding neutral third-sector orgs’ and think tanks’ research. Supporting organisations advising on online education. Closely involved in politics. And sit increasingly, within the organisations set up to lead the technology vision, advising government on policy and UK data analytics, or on social media, AI and ethics.

It is all subject to corporate capture.

But is this healthy for UK public policy and the future not of an industry sector, but a whole technology, when it comes to AI?

If a company’s vital business interests seem unfazed by the risk and harm they cause to individuals — from people who no longer trust the confidentiality of the system to measurable harms — why should those companies sit on public policy boards set up to shape the ethics they claim we need, to solve the problems and restore loss of trust that these very same companies are causing?

We laud people in these companies as co-founders and forward thinkers on new data ethics institutes. They are invited to sit on our national boards, or create new ones.

What does that say about the entire board’s respect for the law which the company breached? It is hard not to see it signal acceptance of the company’s excuses or lack of accountability.

Corporate accountability

The same companies whose work has breached data protection law, multiple ways, seemingly ‘by accident’ on national data extractions, are those companies that cross the t’s and dot the i’s on even the simplest conference call, and demand everything is said in strictest confidence. Meanwhile their everyday business practices ignore millions of people’s lawful rights to confidentiality.

The extent of commercial companies’ influence on these boards is  opaque. To allow this ethics bandwagon to be driven by the corporate giants surely eschews genuine rights-based values, and long-term integrity of the body they appear to serve.

I am told that these global orgs must be in the room and at the table, to use the opportunity to make the world a better place.

These companies already have *all* the opportunity. Not only monopoly positions on their own technology, but the datasets at scale which underpin it, excluding new entrants to the market. Their pick of new hires from universities. The sponsorship of events. The political lobbying. Access to the media. The lawyers. Bottomless pockets to pay for it all. And seats at board tables set up to shape UK policy responses.

It’s a struggle for power, and a stake in our collective future. The status quo is not good enough for many parts of society, and to enable Big Tech or big government to maintain that simply through the latest tools, is a missed chance to reshape for good.

You can see it in many tech boards’ make up, and pervasive white male bias. We hear it echoed in London think tank conferences, even independent tech design agencies, or set out in some Big Tech reports. All seemingly unconnected, but often funded by the same driving sources.

These companies are often those that made it worse to start with, and the very ethics issues the boards have been set up to deal with, are at the core of their business models and of their making.

The deliberate infiltration of influence on online safety policy for children, or global privacy efforts is very real, explicitly set out in the #FacebookEmails, for example.

We will not resolve these fundamental questions, as long as the companies whose business depend on them, steer national policy. The odds will be ever in their favour.

At the same time, some of these individuals are brilliant. In all senses.

So what’s the answer. If they are around the table, what should the UK public expect of their involvement, and ensure in whose best interests it is? How do we achieve authentic accountability?

Whether it be social media, data analytics, or AI in public policy, can companies be safely permitted to be policy shapers if they wear all the hats; product maker, profit taker, *and* process or product auditor?

Creating Authentic Accountability

At minimum we must demand responsibility for their own actions from board members who represent or are funded by companies.

  1. They must deliver on their own product problems first before being allowed to suggest solutions to societal problems.
  2. There should be credible separation between informing policy makers, and shaping policy.
  3. There must be total transparency of funding sources across any public sector boards, of members, and those lobbying them.
  4. Board members must be meaningfully held accountable for continued company transgressions on rights and freedoms, not only harms.
  5. Oversight of board decision making must be decentralised, transparent and available to scrutiny and meaningful challenge.

While these new bodies may propose solutions that include public engagement strategies, transparency, and standards, few propose meaningful oversight. The real test is not what companies say in their ethical frameworks, but in what they continue to do.

If they fail to meet legal or regulatory frameworks, minimum accountability should mean no more access to public data sets and losing positions of policy influence.

Their behaviour needs to go above and beyond meeting the letter of the law, scraping by or working around rights based protections. They need to put people ahead of profit and self interests. That’s what ethics should mean, not be a PR route to avoid regulation.

As long as companies think the consequences of their platforms and actions are tolerable and a minimal disruption to their business model, society will be expected to live with their transgressions, and our most vulnerable will continue to pay the cost.

This is part 2 of thoughts on Policy shapers, product makers, and profit takers — data and AI. Part 1 is here.

AI, change management, children, datasharing, deregulation, engagement, ethics, politics, privacy, pupils, research, surveillance, Tech, transparency, trust

The power of imagination in public policy

“A new, a vast, and a powerful language is developed for the future use of analysis, in which to wield its truths so that these may become of more speedy and accurate practical application for the purposes of mankind than the means hitherto in our possession have rendered possible.” [on Ada Lovelace, The First tech Visionary, New Yorker, 2013]

What would Ada Lovelace have argued for in today’s AI debates? I think she may have used her voice not only to call for the good use of data analysis, but for her second strength.The power of her imagination.

James Ball recently wrote in The European [1]:

“It is becoming increasingly clear that the modern political war isn’t one against poverty, or against crime, or drugs, or even the tech giants – our modern political era is dominated by a war against reality.”

My overriding take away from three days spent at the Conservative Party Conference this week, was similar. It reaffirmed the title of a school debate I lost at age 15, ‘We only believe what we want to believe.’

James writes that it is, “easy to deny something that’s a few years in the future“, and that Conservatives, “especially pro-Brexit Conservatives – are sticking to that tried-and-tested formula: denying the facts, telling a story of the world as you’d like it to be, and waiting for the votes and applause to roll in.”

These positions are not confined to one party’s politics, or speeches of future hopes, but define perception of current reality.

I spent a lot of time listening to MPs. To Ministers, to Councillors, and to party members. At fringe events, in coffee queues, on the exhibition floor. I had conversations pressed against corridor walls as small press-illuminated swarms of people passed by with Queen Johnson or Rees-Mogg at their centre.

In one panel I heard a primary school teacher deny that child poverty really exists, or affects learning in the classroom.

In another, in passing, a digital Minister suggested that Pupil Referral Units (PRU) are where most of society’s ills start, but as a Birmingham head wrote this week, “They’ll blame the housing crisis on PRUs soon!” and “for the record, there aren’t gang recruiters outside our gates.”

This is no tirade on failings of public policymakers however. While it is easy to suspect malicious intent when you are at, or feel, the sharp end of policies which do harm, success is subjective.

It is clear that an overwhelming sense of self-belief exists in those responsible, in the intent of any given policy to do good.

Where policies include technology, this is underpinned by a self re-affirming belief in its power. Power waiting to be harnessed by government and the public sector. Even more appealing where it is sold as a cost-saving tool in cash strapped councils. Many that have cut away human staff are now trying to use machine power to make decisions. Some of the unintended consequences of taking humans out of the process, are catastrophic for human rights.

Sweeping human assumptions behind such thinking on social issues and their causes, are becoming hard coded into algorithmic solutions that involve identifying young people who are in danger of becoming involved in crime using “risk factors” such as truancy, school exclusion, domestic violence and gang membership.

The disconnect between perception of risk, the reality of risk, and real harm, whether perceived or felt from these applied policies in real-life, is not so much, ‘easy to deny something that’s a few years in the future‘ as Ball writes, but a denial of the reality now.

Concerningly, there is lack of imagination of what real harms look like.There is no discussion where sometimes these predictive policies have no positive, or even a negative effect, and make things worse.

I’m deeply concerned that there is an unwillingness to recognise any failures in current data processing in the public sector, particularly at scale, and where it regards the well-known poor quality of administrative data. Or to be accountable for its failures.

Harms, existing harms to individuals, are perceived as outliers. Any broad sweep of harms across policy like Universal Credit, seem perceived as political criticism, which makes the measurable failures less meaningful, less real, and less necessary to change.

There is a worrying growing trend of finger-pointing exclusively at others’ tech failures instead. In particular, social media companies.

Imagination and mistaken ideas are reinforced where the idea is plausible, and shared. An oft heard and self-affirming belief was repeated in many fora between policymakers, media, NGOs regards children’s online safety. “There is no regulation online”. In fact, much that applies offline applies online. The Crown Prosecution Service Social Media Guidelines is a good place to start. [2] But no one discusses where children’s lives may be put at risk or less safe, through the use of state information about them.

Policymakers want data to give us certainty. But many uses of big data, and new tools appear to do little more than quantify moral fears, and yet still guide real-life interventions in real-lives.

Child abuse prediction, and school exclusion interventions should not be test-beds for technology the public cannot scrutinise or understand.

In one trial attempting to predict exclusion, this recent UK research project in 2013-16 linked children’s school records of 800 children in 40 London schools, with Metropolitan Police arrest records of all the participants. It found interventions created no benefit, and may have caused harm. [3]

“Anecdotal evidence from the EiE-L core workers indicated that in some instances schools informed students that they were enrolled on the intervention because they were the “worst kids”.”

“Keeping students in education, by providing them with an inclusive school environment, which would facilitate school bonds in the context of supportive student–teacher relationships, should be seen as a key goal for educators and policy makers in this area,” researchers suggested.

But policy makers seem intent to use systems that tick boxes, and create triggers to single people out, with quantifiable impact.

Some of these systems are known to be poor, or harmful.

When it comes to predicting and preventing child abuse, there is concern with the harms in US programmes ahead of us, such as both Pittsburgh, and Chicago that has scrapped its programme.

The Illinois Department of Children and Family Services ended a high-profile program that used computer data mining to identify children at risk for serious injury or death after the agency’s top official called the technology unreliable, and children still died.

“We are not doing the predictive analytics because it didn’t seem to be predicting much,” DCFS Director Beverly “B.J.” Walker told the Tribune.

Many professionals in the UK share these concerns. How long will they be ignored and children be guinea pigs without transparent error rates, or recognition of the potential harmful effects?

Helen Margetts, Director of the Oxford Internet Institute and Programme Director for Public Policy at the Alan Turing Institute, suggested at the IGF event this week, that stopping the use of these AI in the public sector is impossible. We could not decide that, “we’re not doing this until we’ve decided how it’s going to be.” It can’t work like that.” [45:30]

Why on earth not? At least for these high risk projects.

How long should children be the test subjects of machine learning tools at scale, without transparent error rates, audit, or scrutiny of their systems and understanding of unintended consequences?

Is harm to any child a price you’re willing to pay to keep using these systems to perhaps identify others, while we don’t know?

Is there an acceptable positive versus negative outcome rate?

The evidence so far of AI in child abuse prediction is not clearly showing that more children are helped than harmed.

Surely it’s time to stop thinking, and demand action on this.

It doesn’t take much imagination, to see the harms. Safe technology, and safe use of data, does not prevent the imagination or innovation, employed for good.

If we continue to ignore views from Patrick Brown, Ruth Gilbert, Rachel Pearson and Gene Feder, Charmaine Fletcher, Mike Stein, Tina Shaw and John Simmonds I want to know why.

Where you are willing to sacrifice certainty of human safety for the machine decision, I want someone to be accountable for why.

 

References

[1] James Ball, The European, Those waging war against reality are doomed to failure, October 4, 2018.

[2] Thanks to Graham Smith for the link. “Social Media – Guidelines on prosecuting cases involving communications sent via social media. The Crown Prosecution Service (CPS) , August 2018.”

[3] Obsuth, I., Sutherland, A., Cope, A. et al. J Youth Adolescence (2017) 46: 538. https://doi.org/10.1007/s10964-016-0468-4 London Education and Inclusion Project (LEIP): Results from a Cluster-Randomized Controlled Trial of an Intervention to Reduce School Exclusion and Antisocial Behavior (March 2016)

care.data, change, confidentiality, data, datasharing, empowerment, ethics, GDPR, National Pupil Database

Can Data Trusts be trustworthy?

The Lords Select Committee report on AI in the UK in March 2018, suggested that,“the Government plans to adopt the Hall-Pesenti Review recommendation that ‘data trusts’ be established to facilitate the ethical sharing of data between organisations.”

Since data distribution already happens, what difference would a Data Trust model make to ‘ethical sharing‘?

A ‘set of relationships underpinned by a repeatable framework, compliant with parties’ obligations’ seems little better than what we have today, with all its problems including deeply unethical policy and practice.

The ODI set out some of the characteristics Data Trusts might have or share. As importantly, we should define what Data Trusts are not. They should not simply be a new name for pooling content and a new single distribution point. Click and collect.

But is a Data Trust little more than a new description for what goes on already? Either a physical space or legal agreements for data users to pass around the personal data from the unsuspecting, and sometimes unwilling, public. Friends-with-benefits who each bring something to the party to share with the others?

As with any communal risk, it is the standards of the weakest link, the least ethical, the one that pees in the pool, that will increase reputational risk for all who take part, and spoil it for everyone.

Importantly, the Lords AI Committee report recognised that there is an inherent risk how the public would react to Data Trusts, because there is no social license for this new data sharing.

“Under the current proposals, individuals who have their personal data contained within these trusts would have no means by which they could make their views heard, or shape the decisions of these trusts.”

Views those keen on Data Trusts seem keen to ignore.

When the Administrative Data Research Network was set up in 2013, a new infrastructure for “deidentified” data linkage, extensive public dialogue was carried across across the UK. It concluded in a report with very similar findings as was apparent at dozens of care.data engagement events in 2014-15;

There is not public support for

  • “Creating large databases containing many variables/data from a large number of public sector sources,
  • Establishing greater permanency of datasets,
  • Allowing administrative data to be linked with business data, or
  • Linking of passively collected administrative data, in particular geo-location data”

The other ‘red-line’ for some participants was allowing “researchers for private companies to access data, either to deliver a public service or in order to make profit. Trust in private companies’ motivations were low.”

All of the above could be central to Data Trusts. All of the above highlight that in any new push to exploit personal data, the public must not be the last to know. And until all of the above are resolved, that social-license underpinning the work will always be missing.

Take the National Pupil Database (NPD) as a case study in a Data Trust done wrong.

It is a mega-database of over 20 other datasets. Raw data has been farmed out for years under terms and conditions to third parties, including users who hold an entire copy of the database, such as the somewhat secretive and unaccountable Fischer Family Trust, and others, who don’t answer to Freedom-of-Information, and whose terms are hidden under commercial confidentilaity. Buying and benchmarking data from schools and selling it back to some, profiling is hidden from parents and pupils, yet the FFT predictive risk scoring can shape a child’s school experience from age 2. They don’t really want to answer how staff tell if a child’s FFT profile and risk score predictions are accurate, or of they can spot errors or a wrong data input somewhere.

Even as the NPD moves towards risk reduction, its issues remain. When will children be told how data about them are used?

Is it any wonder that many people in the UK feel a resentment of institutions and orgs who feel entitled to exploit them, or nudge their behaviour, and a need to ‘take back control’?

It is naïve for those working in data policy and research to think that it does not apply to them.

We already have safe infrastructures in the UK for excellent data access. What users are missing, is the social license to do so.

Some of today’s data uses are ethically problematic.

No one should be talking about increasing access to public data, before delivering increased public understanding. Data users must get over their fear of what if the public found out.

If your data use being on the front pages would make you nervous, maybe it’s a clue you should be doing something differently. If you don’t trust the public would support it, then perhaps it doesn’t deserve to be trusted. Respect individuals’ dignity and human rights. Stop doing stupid things that undermine everything.

Build the social license that care.data was missing. Be honest. Respect our right to know, and right to object. Build them into a public UK data strategy to be understood and be proud of.

Part 1. Ethically problematic
Ethics is dissolving into little more than a buzzword. Can we find solutions underpinned by law, and ethics, and put the person first?

Part 2. Can Data Trusts be trustworthy?
As long as data users ignore data subjects rights, Data Trusts have no social license.

AI, care.data, change management, data, datasharing, engagement, ethics

Ethically problematic

Five years ago, researchers at the Manchester University School of Social Sciences wrote, “It will no longer be possible to assume that secondary data use is ethically unproblematic.”

Five years on, other people’s use of the language of data ethics puts social science at risk. Event after event, we are witnessing the gradual dissolution of the value and meaning of ‘ethics’, into little more than a buzzword.

Companies and organisations are using the language of ‘ethical’ behaviour blended with ‘corporate responsibility’ modelled after their own values, as a way to present competitive advantage.

Ethics is becoming shorthand for, ‘we’re the good guys’. It is being subverted by personal data users’ self-interest. Not to address concerns over the effects of data processing on individuals or communities, but to justify doing it anyway.

An ethics race

There’s certainly a race on for who gets to define what data ethics will mean. We have at least three new UK institutes competing for a voice in the space. Digital Catapult has formed an AI ethics committee. Data charities abound. Even Google has developed an ethical AI strategy of its own, in the wake of their Project Maven.

Lessons learned in public data policy should be clear by now. There should be no surprises how administrative data about us are used by others. We should expect fairness. Yet these basics still seem hard for some to accept.

The NHS Royal Free Hospital in 2015 was rightly criticised – because they tried “to commercialise personal confidentiality without personal consent,” as reported in Wired recently.

“The shortcomings we found were avoidable,” wrote Elizabeth Denham in 2017 when the ICO found six ways the Google DeepMind — Royal Free deal did not comply with the Data Protection Act. The price of innovation, she said, didn’t need to be the erosion of fundamental privacy rights underpinned by the law.

If the Centre for Data Ethics and Innovation is put on a statutory footing where does that leave the ICO, when their views differ?

It’s why the idea of DeepMind funding work in Ethics and Society seems incongruous to me. I wait to be proven wrong. In their own words, “technologists must take responsibility for the ethical and social impact of their work“. Breaking the law however, is conspicuous by its absence, and the Centre must not be used by companies, to generate pseudo lawful or ethical acceptability.

Do we need new digital ethics?

Admittedly, not all laws are good laws. But if recognising and acting under the authority of the rule-of-law is now an optional extra, it will undermine the ICO, sink public trust, and destroy any hope of achieving the research ambitions of UK social science.

I am not convinced there is any such thing as digital ethics. The claimed gap in an ability to get things right in this complex area, is too often after people simply get caught doing something wrong. Technologists abdicate accountability saying “we’re just developers,” and sociologists say, “we’re not tech people.”

These shrugs of the shoulders by third-parties, should not be rewarded with more data access, or new contracts. Get it wrong, get out of our data.

This lack of acceptance of responsibility creates a sense of helplessness. We can’t make it work, so let’s make the technology do more. But even the most transparent algorithms will never be accountable. People can be accountable, and it must be possible to hold leaders to account for the outcomes of their decisions.

But it shouldn’t be surprising no one wants to be held to account. The consequences of some of these data uses are catastrophic.

Accountability is the number one problem to be solved right now. It includes openness of data errors, uses, outcomes, and policy. Are commercial companies, with public sector contracts, checking data are accurate and corrected from people who the data are about, before applying in predictive tools?

Unethical practice

As Tim Harford in the FT once asked about Big Data uses in general: “Who cares about causation or sampling bias, though, when there is money to be made?”

Problem area number two, whether researchers are are working towards a profit model, or chasing grant funding is this:

How data users can make unbiased decisions whether they should use the data? We have all the same bodies deciding on data access, that oversee its governance. Conflict of self interest is built-in by default, and the allure of new data territory is tempting.

But perhaps the UK key public data ethics problem, is that the policy is currently too often about the system goal, not about improving the experience of the people using systems. Not using technology as a tool, as if people mattered. Harmful policy, can generate harmful data.

Secondary uses of data are intrinsically dependent on the ethics of the data’s operational purpose at collection. Damage-by-design is evident right now across a range of UK commercial and administrative systems. Metrics of policy success and associated data may be just wrong.

Some of the damage is done by collecting data for one purpose and using it operationally for another in secret. Until these modus operandi change no one should think that “data ethics will save us”.

Some of the most ethical research aims try to reveal these problems. But we need to also recognise not all research would be welcomed by the people the research is about, and few researchers want to talk about it. Among hundreds of already-approved university research ethics board applications I’ve read, some were desperately lacking. An organisation is no more ethical than the people who make decisions in its name. People disagree on what is morally right. People can game data input and outcomes and fail reproducibility. Markets and monopolies of power bias aims. Trying to support the next cohort of PhDs and impact for the REF, shapes priorities and values.

“Individuals turn into data, and data become regnant.” Data are often lacking in quality and completeness and given authority they do not deserve.

It is still rare to find informed discussion among the brightest and best of our leading data institutions, about the extensive everyday real world secondary data use across public authorities, including where that use may be unlawful and unethical, like buying from data brokers. Research users are pushing those boundaries for more and more without public debate. Who says what’s too far?

The only way is ethics? Where next?

The latest academic-commercial mash-ups on why we need new data ethics in a new regulatory landscape where the established is seen as past it, is a dangerous catch-all ‘get out of jail free card’.

Ethical barriers are out of step with some of today’s data politics. The law is being sidestepped and regulation diminished by lack of enforcement of gratuitous data grabs from the Internet of Things, and social media data are seen as a free-for-all. Data access barriers are unwanted. What is left to prevent harm?

I’m certain that we first need to take a step back if we are to move forward. Ethical values are founded on human rights that existed before data protection law. Fundamental human decency, rights to privacy, and to freedom from interference, common law confidentiality, tort, and professional codes of conduct on conflict of interest, and confidentiality.

Data protection law emphasises data use. But too often its first principles of necessity and proportionality are ignored. Ethical practice would ask more often, should we collect the data at all?

Although GDPR requires new necessary safeguards to ensure that technical and organisational measures are met to control and process data, and there is a clearly defined Right to Object, I am yet to see a single event thought giving this any thought.

Let’s not pretend secondary use of data is unproblematic, while uses are decided in secret. Calls for a new infrastructure actually seek workarounds of regulation. And human rights are dismissed.

Building a social license between data subjects and data users is unavoidable if use of data about people hopes to be ethical.

The lasting solutions are underpinned by law, and ethics. Accountability for risk and harm. Put the person first in all things.

We need more than hopes and dreams and talk of ethics.

We need realism if we are to get a future UK data strategy that enables human flourishing, with public support.

Notes of desperation or exasperation are increasingly evident in discourse on data policy, and start to sound little better than ‘we want more data at all costs’. If so, the true costs would be lasting.

Perhaps then it is unsurprising that there are calls for a new infrastructure to make it happen, in the form of Data Trusts. Some thoughts on that follow too.

Part 1. Ethically problematic

Ethics is dissolving into little more than a buzzword. Can we find solutions underpinned by law, and ethics, and put the person first?

Part 2. Can Data Trusts be trustworthy?

As long as data users ignore data subjects rights, Data Trusts have no social license.

Data Horizons: New Forms of Data For Social Research,

Elliot, M., Purdam, K., Mackey, E., School of Social Sciences, The University Of Manchester, CCSR Report 2013-312/6/2013
care.data, children, datasharing, ethics, privacy

Leaving Facebook and flaws in Face Recognition

This Facebook ad was the final straw for me this week.

I’m finally leaving.

When I saw Facebook’s disingenuous appropriation of new data law as-a-good-thing I decided time’s up. While Zuckerberg talks about giving users more control, what they are doing is steering users away from better privacy and putting users outside the reach of new protections rather than stepping up to meet its obligations.

After eleven years, I’m done. I’ve used Facebook to run a business.  I’ve used it to keep in touch with real-life family and friends. I’ve had more positive than negative experiences on the site. But I’ve packed in my personal account.

I hadn’t actively used it since 2015. My final post that year was about Acxiom’s data broker agreement with Facebook. It has taken 3 hours to download  any remaining data, to review and remove others’ tags, posts and shared content linking me. I had already deactivated 18 apps, and have now used each individual ID that the Facebook-App link provided, to make Subject Access requests (SAR) and object to processing. Some were easy. Some weren’t.

Pinterest and Hootsuite were painful circular loops of online ‘support’ that didn’t offer any easy way to contact them.  But to their credit Hootsuite Twitter message support was ultra fast and suggested an email to hootsuite-dpa [at] hootsuite.com. Amazon required a log in to the Amazon account. Apple’s Aperture goes into a huge general page impossible to find any easy link to contact.  Ditto Networked Blogs.

Another app that has no name offered a link direct to a pre-filled form with no contact details and no option for free text you can send only the message please delete any data you hold about me — not make a SAR.

Another has a policy but no Data Controller listed. Who is http://a.pgtb.me/privacy ? Ideas welcome.

What about our personal data rights?

The Facebook ad says, you will be able to access, download or delete your data at any time. Not according to the definition of personal data we won’t.  And Facebook knows it. As Facebook’s new terms and condition says, some things that you do on Facebook aren’t stored in your account. For example, a friend may have messages from you after deletion. They don’t even mention data inferred. This information remains after you delete your account. It’s not ‘your’ data because it belongs to the poster, it seems according to Facebook. But it’s ‘your’ data because the data are about or related to you according to data protection law.

Rights are not about ownership.

That’s what Facebook appears to want to fail to understand. Or perhaps wants the reader to fail to understand. Subject Access requests should reveal this kind of data, and we all have a right to know what the Facebook user interface limits-by-design. But Facebook still keeps this hidden, while saying we have control.

Meanwhile, what is it doing?  Facebook appears to be running scared and removing  recourse to better rights.

Facebook, GDPR and flaws in Face Recognition

They’ve also started running Face Recognition. With the new feature enabled, you’re notified if you appear in a photo even if not tagged.

How will we be notified if we’re not tagged? Presumably Facebook uses previously stored facial images that were tagged, and is matching them using an image library behind the scenes.

In the past I have been mildly annoyed when friends who should know me better, have posted photos of my children on Facebook.

Moments like children’s birthday parties can mean a photo posted of ten fun-filled faces in which ten parents are tagged. Until everyone knew I’d rather they didn’t, I was often  tagged in photos of my young children.  Or rather my children were tagged as me.

Depending on your settings, you’ll receive a notification when someone tags a photo with your name.  Sure I can go and untag it, to change the audience that can see it, but cannot have control over it.

Facebook meanwhile pushes this back as if it is a flaw with the user and in a classic victim-blaming move suggests it’s your fault you don’t like it, not their failure to meet privacy-by-design, by saying,  If you don’t like something you’re tagged in, you can remove the tag or ask the person who tagged you to remove the post.

There is an illusion of control being given to the user, by companies and government at the moment. We must not let that illusion become the accepted norm.

Children whose parents are not on the site cannot get notifications. A parent may have no Facebook account.  (A child under 13 should no Facebook account, although Facebook has tried to grab those too.) The child with no account may never know, but Facebook is certainly processing, and might be building up a shadow profile about, the nameless child with face X anyway.

What happens next?

As GDPR requires a share of accountability for controller and processing responsibilities, what will it mean for posters who do so without consent of the people in photos? For Facebook it should mean they cannot process using biometric profiling, and its significant effects may be hidden or, especially for children, only appear in the future.

Does Facebook process across photos held on other platforms?

Since it was founded, Facebook has taken over several social media companies, the most familiar of which are Instagram in 2012 and WhatsApp in 2014. Facebook has also bought Oculus VR [VR headsets], Ascenta [drones], and ProtoGeo Oy [fitness trackers].

Bloomberg reported at the end of February that  a lawsuit alleging Facebook Inc. photo scanning technology flouts users’ privacy rights can proceed.

As TechCrunch summarised, when asked to clear a higher bar for privacy, Facebook has instead delved into design tricks to keep from losing our data.

Facebook needs to axe Face Recognition, or make it work in ways that are lawful, to face up to its responsibilities, and fast.

The Cambridge Analytica scandal has also brought personalised content targeting into the spotlight, but we are yet to see really constructive steps to row back to more straightfoward advertising, and away from todays’s highly invasive models of data collection and content micro-targeting designed to to grab your personalised attention.

Meanwhile policy makers and media are obsessed with screen time limits as a misplaced, over-simplified solution to complex problems, in young people using social media, which are more commonly likely to be exacerbating existing conditions and demonstrate correlations rather than cause.

Children are stuck in the middle.

Their rights to protection, privacy, reputation and participation must not become a political playground.