children, confidentiality, data, engagement, Online harms, politics, privacy

Thoughts on the Online Harms White Paper (I)

“Whatever the social issue we want to grasp – the answer should always begin with family.”

Not my words, but David Cameron’s. Just five years ago, Conservative policy was all about “putting families at the centre of domestic policy-making.”

Debate on the Online Harms White Paper, thanks in part to media framing of its own departmental making, is almost all about children. But I struggle with the debate that leaves out our role as parents almost entirely, other than as bereft or helpless victims ourselves.

I am conscious wearing my other hat of defenddigitalme, that not all families are the same, and not all children have families. Yet it seems counter to conservative values,  for a party that places the family traditionally at the centre of policy, to leave out or abdicate parents of responsibility for their children’s actions and care online.

Parental responsibility cannot be outsourced to tech companies, or accept it’s too hard to police our children’s phones. If we as parents are concerned about harms, it is our responsibility to enable access to that which is not, and be aware and educate ourselves and our children on what is. We are aware of what they read in books. I cast an eye over what they borrow or buy. I play a supervisory role.

Brutal as it may be, the Internet is not responsible for suicide. It’s just not that simple. We cannot bring children back from the dead. We certainly can as society and policy makers, try and create the conditions that harms are not normalised, and do not become more common.  And seek to reduce risk. But few would suggest social media is a single source of children’s mental health issues.

What policy makers are trying to regulate is in essence, not a single source of online harms but 2.1 billion users’ online behaviours.

It follows that to see social media as a single source of attributable fault per se, is equally misplaced. A one-size-fits-all solution is going to be flawed, but everyone seems to have accepted its inevitability.

So how will we make the least bad law?

If we are to have sound law that can be applied around what is lawful,  we must reduce the substance of debate by removing what is already unlawful and has appropriate remedy and enforcement.

Debate must also try to be free from emotive content and language.

I strongly suspect the language around ‘our way of life’ and ‘values’ in the White Paper comes from the Home Office. So while it sounds fair and just, we must remember reality in the background of TOEIC, of Windrush, of children removed from school because their national records are being misused beyond educational purposes. The Home Office is no friend of child rights, and does not foster the societal values that break down discrimination and harm. It instead creates harms of its own making, and division by design.

I’m going to quote Graham Smith, for I cannot word it better.

“Harms to society, feature heavily in the White Paper, for example: content or activity that:

“threatens our way of life in the UK, either by undermining national security, or by reducing trust and undermining our shared rights, responsibilities and opportunities to foster integration.”

Similarly:

“undermine our democratic values and debate”;

“encouraging us to make decisions that could damage our health, undermining our respect and tolerance for each other and confusing our understanding of what is happening in the wider world.”

This kind of prose may befit the soapbox or an election manifesto, but has no place in or near legislation.”

[Cyberleagle, April 18, 2019,Users Behaving Badly – the Online Harms White Paper]

My key concern in this area is that through a feeling of ‘it is all awful’ stems the sense that ‘all regulation will be better than now’, and  comes with a real risk of increasing current practices that would not be better than now, and in fact need fixing.

More monitoring

The first, is today’s general monitoring of school children’s Internet content for risk and harms, which creates unintended consequences and very real harms of its own — at the moment, without oversight.

In yesterday’s House of Lords debate, Lord Haskel, said,

“This is the practicality of monitoring the internet. When the duty of care required by the White Paper becomes law, companies and regulators will have to do a lot more of it. ” [April 30, HOL]

The Brennan Centre yesterday published its research on the spend by US schools purchasing social media monitoring software from 2013-18, and highlighted some of the issues:

“Aside from anecdotes promoted by the companies that sell this software, there is no proof that these surveillance tools work [compared with other practices]. But there are plenty of risks. In any context, social media is ripe for misinterpretation and misuse.” [Brennan Centre for Justice, April 30, 209]

That monitoring software focuses on two things —

a) seeing children through the lens of terrorism and extremism, and b) harms caused by them to others, or as victims of harms by others, or self-harm.

It is the near same list of ‘harms’ topics that the White Paper covers. Co-driven by the same department interested in it in schools — the Home Office.

These concerns are set in the context of the direction of travel of law and policy making, its own loosening of accountability and process.

It was preceded by a House of Commons discussion on Social Media and Health, lead by the former Minister for Digital, Culture, Media and Sport who seems to feel more at home in that sphere, than in health.

His unilateral award of funds to the Samaritans for work with Google and Facebook on a duty of care, while the very same is still under public consultation, is surprising to say the least.

But it was his response to this question, which points to the slippery slope such regulations may lead. The Freedom of Speech champions should be most concerned not even by what is potentially in any legislation ahead, but in the direction of travel and debate around it.

“Will he look at whether tech giants such as Amazon can be brought into the remit of the Online Harms White Paper? ”

He replied, that “Amazon sells physical goods for the most part and surely has a duty of care to those who buy them, in the same way that a shop has a responsibility for what it sells. My hon. Friend makes an important point, which I will follow up.”

Mixed messages

The Center for Democracy and Technology recommended in its 2017 report, Mixed Messages? The Limits of Automated Social Media Content Analysis, that the use of automated content analysis tools to detect or remove illegal content should never be mandated in law.

Debate so far has demonstrated broad gaps between what is wanted, in knowledge, and what is possible. If behaviours are to be stopped because they are undesirable rather than unlawful, we open up a whole can of worms if not done with the greatest attention to  detail.

Lord Stevenson and Lord McNally both suggested that pre-legislative scrutiny of the Bill, and more discussion would be positive. Let’s hope it happens.

Here’s my personal first reflections on the Online Harms White Paper discussion so far.

Six suggestions:

Suggestion one: 

The Law Commission Review, mentioned in the House of Lords debate,  may provide what I have been thinking of crowd sourcing and now may not need to. A list of laws that the Online Harms White Paper related discussion reaches into, so that we can compare what is needed in debate versus what is being sucked in. We should aim to curtail emotive discussion of broad risk and threat that people experience online. This would enable the themes which are already covered in law to be avoided, and focus on the gaps.  It would make for much tighter and more effective legislation. For example, the Crown Prosecution Service offers Guidelines on prosecuting cases involving communications sent via social media, but a wider list of law is needed.

Suggestion two:
After (1) defining what legislation is lacking, definitions must be very clear, narrow, and consistent across other legislation. Not for the regulator to determine ad-hoc and alone.

Suggestion three:
If children’s rights are at to be so central in discussion on this paper, then their wider rights must including privacy and participation, access to information and freedom of speech must be included in debate. This should include academic research-based evidence of children’s experience online when making the regulations.

Suggestion four:
Internet surveillance software in schools should be publicly scrutinised. A review should establish the efficacy, boundaries and oversight of policy and practice regards Internet monitoring for harms and not embed even more, without it. Boundaries should be put into legislation for clarity and consistency.

Suggestion five:
Terrorist activity or child sexual exploitation and abuse (CSEA) online are already unlawful and should not need additional Home Office powers. Great caution must be exercised here.

Suggestion six: 
Legislation could and should encapsulate accountability and oversight for micro-targeting and algorithmic abuse.

More detail behind my thinking, follows below, after the break. [Structure rearranged on May 14, 2019]

Continue reading Thoughts on the Online Harms White Paper (I) →

AI, change, politics, privacy, surveillance, Tech, transparency, women

Women Leading in AI — Challenging the unaccountable and the inevitable

Notes [and my thoughts] from the Women Leading in AI launch event of the Ten Principles of Responsible AI report and recommendations, February 6, 2019.

Speakers included Ivana Bartoletti (GemServ), Jo Stevens MP, Professor Joanna J Bryson, Lord Tim Clement-Jones, Roger Taylor (Centre for Data Ethics and Innovation, Chair), Sue Daley (techUK), Reema Patel, Nuffield Foundation and Ada Lovelace Institute.

Challenging the unaccountable and the ‘inevitable’ is the title of the conclusion of the Women Leading in AI report Ten Principles of Responsible AI, launched this week, and this 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.”

Ivana Bartoletti, co-founder of Women Leading in AI, began the event, hosted at the House of Commons by Jo Stevens, MP for Cardiff Central, and spoke brilliantly of why it matters right now.

Everyone’s talking about ethics, she said, but it has limitations. I agree with that. This was by contrast very much a call to action.

It was nearly impossible not to cheer, as she set out without any of the usual bullshit, the reasons why we need to stop “churning out algorithms which discriminate against women and minorities.”

Professor Joanna J Bryson took up multiple issues, such as why

  • innovation, ‘flashes in the pan’ are not sustainable and not what we’re looking for things in that work for us [society].
  • The power dynamics of data, noting Facebook, Google et al are global assets, and are also global problems, and flagged the UK consultation on taxation open now.
  • And that it is critical that we do not have another nation with access to all of our data.

She challenged the audience to think about the fact that inequality is higher now than it has been since World War I. That the rich are getting richer and that imbalance of not only wealth, but of the control individuals have in their own lives, is failing us all.

This big picture thinking while zooming in on detailed social, cultural, political and tech issues, fascinated me most that evening. It frustrated the man next to me apparently, who said to me at the end, ‘but they haven’t addressed anything on the technology.’

[I wondered if that summed up neatly, some of why fixing AI cannot be a male dominated debate. Because many of these issues for AI, are not of the technology, but of people and power.] 

Jo Stevens, MP for Cardiff Central, hosted the event and was candid about politicians’ level of knowledge and the need to catch up on some of what matters in the tech sector.

We grapple with the speed of tech, she said. We’re slow at doing things and tech moves quickly. It means that we have to learn quickly.

While discussing how regulation is not something AI tech companies should fear, she suggested that a constructive framework whilst protecting society against some of the problems we see is necessary and just, because self-regulation has failed.

She talked about their enquiry which began about “fake news” and disinformation, but has grown to include:

  • wider behavioural economics,
  • how it affects democracy.
  • understanding the power of data.
  • disappointment with social media companies, who understand the power they have, and fail to be accountable.

She wants to see something that changes the way big business works, in the way that employment regulation challenged exploitation of the workforce and unsafe practices in the past.

The bias (conscious or unconscious) and power imbalance has some similarity with the effects on marginalised communities — women, BAME, disabilities — and she was looking forward to see the proposed solutions, and welcomed the principles.

Lord Clement-Jones, as Chair of the Select Committee on Artificial Intelligence, picked up the values they had highlighted in the March 2018 report, Artificial Intelligence, AI in the UK: ready, willing and able?

Right now there are so many different bodies, groups in parliament and others looking at this [AI / Internet / The Digital World] he said, so it was good that the topic is timely, front and centre with a focus on women, diversity and bias.

He highlighted, the importance of maintaining public trust. How do you understand bias? How do you know how algorithms are trained and understand the issues? He fessed up to being a big fan of DotEveryone and their drive for better ‘digital understanding’.

[Though sometimes this point is over complicated by suggesting individuals must understand how the AI works, the consensus of the evening was common sensed — and aligned with the Working Party 29 guidance — that data controllers must ensure they explain clearly and simply to individuals, how the profiling or automated decision-making process works, and what its effect is for them.]

The way forward he said includes:

  • Designing ethics into algorithms up front.
  • Data audits need to be diverse in order to embody fairness and diversity in the AI.
  • Questions of the job market and re-skilling.
  • The enforcement of ethical frameworks.

He also asked how far bodies will act, in different debates. Deciding who decides on that is still a debate to be had.

For example, aware of the social credit agenda and scoring in China, we should avoid the same issues. He also agreed with Joanna, that international cooperation is vital, and said it is important that we are not disadvantaged in this global technology. He expected that we [the Government Office for AI] will soon promote a common set of AI ethics, at the G20.

Facial recognition and AI are examples of areas that require regulation for safe use of the tech and to weed out those using it for the wrong purposes, he suggested.

However, on regulation he held back. We need to be careful about too many regulators he said. We’ve got the ICO, FCA, CMA, OFCOM, you name it, we’ve already got it, and they risk tripping over one another. [What I thought as CDEI was created para 31.]

We [the Lords Committee] didn’t suggest yet another regulator for AI, he said and instead the CDEI should grapple with those issues and encourage ethical design in micro-targeting for example.

Roger Taylor (Chair of the CDEI), — after saying it felt as if the WLinAI report was like someone had left their homework on his desk, — supported the concept of the WLinAI principles are important, and  agreed it was time for practical things, and what needs done.

Can our existing regulators do their job, and cover AI? he asked, suggesting new regulators will not be necessary. Bias he rightly recognised, already exists in our laws and bodies with public obligations, and in how AI is already operating;

  • CVs sorting. [problematic IMO > See Amazon, US teachers]
  • Policing.
  • Creditworthiness.

What evidence is needed, what process is required, what is needed to assure that we know how it is actually operating? Who gets to decide to know if this is fair or not? While these are complex decisions, they are ultimately not for technicians, but a decision for society, he said.

[So far so good.]

Then he made some statements which were rather more ambiguous. The standards expected of the police will not be the same as those for marketeers micro targeting adverts at you, for example.

[I wondered how and why.]

Start up industries pay more to Google and Facebook than in taxes he said.

[I wondered how and why.]

When we think about a knowledge economy, the output of our most valuable companies is increasingly ‘what is our collective truth? Do you have this diagnosis or not? Are you a good credit risk or not? Even who you think you are — your identity will be controlled by machines.’

What can we do as one country [to influence these questions on AI], in what is a global industry? He believes, a huge amount. We are active in the financial sector, the health service, education, and social care — and while we are at the mercy of large corporations, even large corporations obey the law, he said.

[Hmm, I thought, considering the Google DeepMind-Royal Free agreement that didn’t, and venture capitalists not renowned for their ethics, and yet advise on some of the current data / tech / AI boards. I am sceptical of corporate capture in UK policy making.]

The power to use systems to nudge our decisions, he suggested, is one that needs careful thought. The desire to use the tech to help make decisions is inbuilt into what is actually wrong with the technology that enables us to do so. [With this I strongly agree, and there is too little protection from nudge in data protection law.]

The real question here is, “What is OK to be owned in that kind of economy?” he asked.

This was arguably the neatest and most important question of the evening, and I vigorously agreed with him asking it, but then I worry about his conclusion in passing, that he was, “very keen to hear from anyone attempting to use AI effectively, and encountering difficulties because of regulatory structures.“

[And unpopular or contradictory a view as it may be, I find it deeply ethically problematic for the Chair of the CDEI to be held by someone who had a joint-venture that commercially exploited confidential data from the NHS without public knowledge, and its sale to the Department of Health was described by the Public Accounts Committee, as a “hole and corner deal”. That was the route towards care.data, that his co-founder later led for NHS England. The company was then bought by Telstra, where Mr Kelsey went next on leaving NHS Engalnd. The whole commodification of confidentiality of public data, without regard for public trust, is still a barrier to sustainable UK data policy.]

Sue Daley (Tech UK) agreed this year needs to be the year we see action, and the report is a call to action on issues that warrant further discussion.

  • Business wants to do the right thing, and we need to promote it.
  • We need two things — confidence and vigilance.
  • We’re not starting from scratch, and talked about GDPR as the floor not the ceiling. A starting point.

[I’m not quite sure what she was after here, but perhaps it was the suggestion that data regulation is fundamental in AI regulation, with which I would agree.]

What is the gap that needs filled she asked? Gap analysis is what we need next and avoid duplication of effort —need to avoid complexity and duplicity of work with other bodies. If we can answer some of the big, profound questions need to be addressed to position the UK as the place where companies want to come to.

Sue was the only speaker that went on to talk about the education system that needs to frame what skills are needed for a future world for a generation, ‘to thrive in the world we are building for them.’

[The Silicon Valley driven entrepreneur narrative that the education system is broken, is not an uncontroversial position.]

She finished with the hope that young people watching BBC icons the night before would see, Alan Turing [winner of the title] and say yes, I want to be part of that.

Listening to Reema Patel, representative of the Ada Lovelace Institute, was the reason I didn’t leave early and missed my evening class. Everything she said resonated, and was some of the best I have heard in the recent UK debate on AI.

  • Civic engagement, the role of the public is as yet unclear with not one homogeneous, but many publics.
  • The sense of disempowerment is important, with disconnect between policy and decisions made about people’s lives.
  • Transparency and literacy are key.
  • Accountability is vague but vital.
  • What does the social contract look like on people using data?
  • Data may not only be about an individual and under their own responsibility, but about others and what does that mean for data rights, data stewardship and articulation of how they connect with one another, which is lacking in the debate.
  • Legitimacy; If people don’t believe it is working for them, it won’t work at all.
  • Ensuring tech design is responsive to societal values.

2018 was a terrible year she thought. Let’s make 2019 better. [Yes!]

Comments from the floor and questions included Professor Noel Sharkey, who spoke about the reasons why it is urgent to act especially where technology is unfair and unsafe and already in use. He pointed to Compass (Durham police), and predictive policing using AI and facial recognition, with 5% accuracy, and that the Met was not taking these flaws seriously. Liberty produced a strong report on it out this week.

Caroline, from Women in AI echoed my own comments on the need to get urgent review in place of these technologies used with children in education and social care. [in particular where used for prediction of child abuse and interventions in family life].

Joanna J Bryson added to the conversation on accountability, to say people are not following existing software and audit protocols,  someone just needs to go and see if people did the right thing.

The basic question of accountability, is to ask if any flaw is the fault of a corporation, of due diligence, or of the users of the tool? Telling people that this is the same problem as any other software, makes it much easier to find solutions to accountability.

Tim Clement-Jones asked, on how many fronts can we fight on at the same time? If government has appeared to exempt itself from some of these issues, and created a weak framework for itself on handing data, in the Data Protection Act — critically he also asked, is the ICO adequately enforcing on government and public accountability, at local and national levels?

Sue Daley also reminded us that politicians need not know everything, but need to know what the right questions are to be asking? What are the effects that this has on my constituents, in employment, my family? And while she also suggested that not using the technology could be unethical, a participant countered that it’s not the worst the thing to have to slow technology down and ensure it is safe before we all go along with it.

My takeaways of the evening, included that there is a very large body of women, of whom attendees were only a small part, who are thinking, building and engineering solutions to some of these societal issues embedded in policy, practice and technology. They need heard.

It was genuinely electric and empowering, to be in a room dominated by women, women reflecting diversity of a variety of publics, ages, and backgrounds, and who listened to one another. It was certainly something out of the ordinary.

There was a subtle but tangible tension on whether or not  regulation beyond what we have today is needed.

While regulating the human behaviour that becomes encoded in AI, we need to ensure ethics of human behaviour, reasonable expectations and fairness are not conflated with the technology [ie a question of, is AI good or bad] but how it is designed, trained, employed, audited, and assess whether it should be used at all.

This was the most effective group challenge I have heard to date, counter the usual assumed inevitability of a mythical omnipotence. Perhaps Julia Powles, this is the beginnings of a robust, bold, imaginative response.

Why there’s not more women or people from minorities working in the sector, was a really interesting if short, part of the discussion. Why should young women and minorities want to go into an environment that they can see is hostile, in which they may not be heard, and we still hold *them* responsible for making work work?

And while there were many voices lamenting the skills and education gaps, there were probably fewer who might see the solution more simply, as I do. Schools are foreshortening Key Stage 3 by a year, replacing a breadth of subjects, with an earlier compulsory 3 year GCSE curriculum which includes RE, and PSHE, but means that at 12, many children are having to choose to do GCSE courses in computer science / coding, or a consumer-style iMedia, or no IT at all, for the rest of their school life. This either-or content, is incredibly short-sighted and surely some blend of non-examined digital skills should be offered through to 16 to all, at least in parallel importance with RE or PSHE.

I also still wonder, about all that incredibly bright and engaged people are not talking about and solving, and missing in policy making, while caught up in AI. We need to keep thinking broadly, and keep human rights at the centre of our thinking on machines. Anaïs Nin wrote over 70 years ago about the risks of growth in technology to expand our potential for connectivity through machines, but diminish our genuine connectedness as people.

“I don’t think the [American] obsession with politics and economics has improved anything. I am tired of this constant drafting of everyone, to think only of present day events”.

And as I wrote about nearly 3 years ago, we still seem to have no vision for sustainable public policy on data, or establishing a social contract for its use as Reema said, which underpins the UK AI debate. Meanwhile, the current changing national public policies in England on identity and technology, are becoming catastrophic.

Challenging the unaccountable and the ‘inevitable’ in today’s technology and AI debate, is an urgent call to action.

I look forward to hearing how Women Leading in AI plan to make it happen.

References:

Women Leading in AI website: http://womenleadinginai.org/
WLiAI Report: 10 Principles of Responsible AI
@WLinAI #WLinAI

image credits 
post: creative commons Mark Dodds/Flickr
event photo:  / GemServ
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.

ethics, politics, research

When is a profile no longer personal data

This is bothering me in current and future data protection.

When is a profile no longer personal?

I’m thinking of a class, or even a year group of school children.

If you strip off enough identifiers or aggregate data so that individuals are no longer recognisable and could not be identified from other data — directly or indirectly — that is in your control or may come into your control, you no longer process personal data.

How far does Article 4(1) go to the boundary of what is identifiable on economic, cultural or social identity?

There is a growing number of research projects using public sector data (including education but often in conjunction and linkage with various others) in which personal data are used to profile and identify sets of characteristics, with a view to intervention.

Let’s take a case study.

Exclusions and absence, poverty, ethnicity, language, SEN and health, attainment indicators, their birth year and postcode areas are all profiled on individual level data in a data set of 100 London schools all to identify the characteristics of children more likely than others to drop out.

It’s a research project, with a view to shaping a NEET intervention program in early education (Not in Education, Employment or Training). There is no consent sought for using the education, health, probation, Police National Computer, and HMRC data like this, because it’s research, and enjoys an exemption.

Among the data collected BAME ethnicity and non-English language students in certain home postcodes are more prevalent. The names of pupils and DOB and their school address have been removed.

In what is in effect a training dataset, to teach the researchers, “what does a potential NEET look like?” pupils with characteristics like Mohammed Jones, are more likely than others to be prevalent.

It does not permit the identification of the data subject as himself, but the data knows exactly what a pupil like MJ looks like.

Armed with these profiles of what potential NEETs look like, researchers now work with the 100 London schools, to give the resulting knowledge, to help teachers identify their children at risk of potential drop out, or exclusion, or of becoming a NEET.

In one London school, MJ, is a perfect match for the profile. The teacher is relieved from any active judgement who should join the program, he’s a perfect match for what to look for.  He’s asked to attend a special intervention group, to identify and work on his risk factors.

The data are accurate. His profile does match. But would he have gone on to become NEET?

Is this research, or was it a targeted intervention?

Are the tests for research exemptions met?

Is this profiling and automated decision-making?

If the teacher is asked to “OK” the list, but will not in practice edit it, does that make it exempt from the profiling restriction for children?

The GDPR also sets out the rules (at Article 6(4)) on factors a controller must take into account to assess whether a new processing purpose is compatible with the purpose for which the data were initially collected.

But if the processing is done only after the identifiers are removed that could identify MJ, not just someone like him, does it apply?

In a world that talks about ever greater personalisation, we are in fact being treated less and less as an individual, but instead we’re constantly assessed by comparison, and probability, how we measure up against other profiles of other people built up from historical data.

Then it is used to predict what someone with a similar profile would do, and therefore by inference, what we the individual would do.

What is the difference in reality, of having given the researchers all the education, health, probation, Police National Computer, and HMRC — as they had it — and then giving them the identifying school datasets with pupils’ named data, and saying “match them up.”

I worry that we are at great risk, in risk prediction, of not using the word research, to mean what we think it means.

And our children are unprotected from bias and unexpected consequences as a result.

engagement, transparency, trust

The Trouble with Boards at the Ministry of Magic

Peter Riddell, the Commissioner for Public Appointments, has completed his investigation into the recent appointments to the Board of the Office for Students and published his report.

From the “Number 10 Googlers,”  that NUS affiliation — an interest in student union representation was seen as undesirable, to “undermining the policy goals” and what the SpAds supported, the whole report is worth a read.

Perception of the process

The concern that the Commissioner raises, over the harm  done to the public’s perception of the public appointments process means more needs done to fix these problems, before and after appointments.

This process reinforces what people think already. Jobs for the [white Oxford] boys, and yes-men.  And so what, why should I get involved anyway, and what can we hope to change?

Possibilities for improvement

What should the Department for Education (DfE) now offer and what should be required after the appointments process, for the OfS and other bodies, boards and groups et al?

  • Every board at the Department for Education, its name, aim, and members — internal and external — should be published.
  • Every board at the Department for Education should be required to publish its Terms of Appointment, and Terms of Reference.
  • Every board at the Department for Education should be required to publish agendas before meetings and meaningful meeting minutes promptly.

Why? Because there’s all sorts of boards around and their transparency is frankly non-existent. I know because I sit on one. Foolishly I did not make it a requirement to publish minutes before I agreed to join. But in a year it has only met twice, so you’ve not missed much. Who else sits where, on what policy, and why?

In another I used to sit on I got increasingly frustrated that the minutes were not reflective of the substance of discussion. This does the public a disservice twice over. The purpose of the boards look insipid and the evidence for what challenge they are intended to offer,  their very reason for being, is washed away. Show the public what’s hard, that there’s debate, that risks are analysed and balanced, and then decisions taken. Be open to scrutiny.

The public has a right to know

When scrutiny really matters, it is wrong — just as the Commissioner report reads — for any Department or body to try to hide the truth.

The purpose of transparency must be to hold to account and ensure checks-and-balances are upheld in a democratic system.

The DfE withdrew from a legal hearing scheduled at the First Tier Information Rights Tribunal last year a couple of weeks beforehand, and finally accepted an ICO decision notice in my favour. I had gone through a year of the Freedom-of-Information appeal process to get hold of the meeting minutes of the Department for Education Star Chamber Scrutiny Board, from November 2015.

It was the meeting in which I had been told members approved the collection of nationality and country of birth in the school census.

“The Star Chamber Scrutiny Board”.  Not out of Harry Potter and the Ministry of Magic but appointed by the DfE.

It’s a board that mentions actively seeking members of certain teaching unions but omits others. It publishes no meeting minutes. Its terms of reference are 38 words long, and it was not told the whole truth before one of the most important and widely criticised decisions it ever made affecting the lives of millions of children across England and harm and division in the classroom.

Its annual report doesn’t mention the controversy at all.

After sixteen months, the DfE finally admitted it had kept the Star Chamber Scrutiny Board in the dark on at least one of the purposes of expanding the school census. And on its pre-existing active, related data policy passing pupil data over to the Home Office.

The minutes revealed the Board did not know anything about the data sharing agreement already in place between the DfE and Home Office or that “(once collected) nationality data” [para 15.2.6] was intended to share with the Border Force Casework Removals Team.

Truth that the DfE was forced to reveal, and only came out two years after the meeting, and a full year after the change in law.

If the truth, transparency, diversity of political opinion on boards are allowed to die so does democracy

I spoke to Board members in 2016. They were shocked to find out what the MOU purposes were for the new data,  and that regular data transfers had already begun without their knowledge, when they were asked to sign off the nationality data collection.

Their lack of concerns raised was given in written evidence to the House of Lords Secondary Legislation Scrutiny Committee that it had been properly reviewed.

How trustworthy is anything that the Star Chamber now “approves” and our law making process to expand school data? How trustworthy is the Statutory Instrument scrutiny process?

“there was no need for DfE to discuss with SCSB the sharing of data with Home Office as: a.) none of the data being considered by the SCSB as part of the proposal supporting this SI has been, or will be, shared with any third-party (including other government departments);

[omits it “was planned to be”]

and b.) even if the data was to be shared externally, those decisions are outside the SCSB terms of reference.”

Outside the terms of reference that are 38 words long and should scrutinise but not too closely or reject on the basis of what exactly?

Not only is the public not being told the full truth about how these boards are created, and what their purpose is, it seems board members are not always told the full truth they deserve either.

Who is invited to the meeting, and who is left out? What reports are generated with what recommendations? What facts or opinion cannot be listened to, scrutinised and countered, that could be so damaging as to not even allow people to bring the truth to the table?

If the meeting minutes would be so controversial and damaging to making public policy by publishing them, then who the heck are these unelected people making such significant decisions and how? Are they qualified, are they independent, and are they accountable?

If alternately, what should be ‘independent’ boards, or panels, or meetings set up to offer scrutiny and challenge, are in fact being manipulated to manoeuvre policy and ready-made political opinions of the day,  it is a disaster for public engagement and democracy.

It should end with this ex- OfS hiring process at DfE, today.

The appointments process and the ongoing work by boards must have full transparency, if they are ever to be seen as trustworthy.

Thinking to some purpose