If you were looking for some dark optimism
From a walk among the tower blocks, in the gloaming
What would you miss, in the long low seduction of the light
Waning pink behind the clouds, behind the towers?
The river moves; the air’s scent of flowers
Floats past as I hang on the concrete
(was it always so thick with lichen?)
The corner store is closed, shutters down.
No milk or old onions, no sweets.
I saw an ambulance there last week.
By the Thames a couple arm in arm
Springtime romance blooming, their masks fitted tight.
He jokes about throwing himself in the river
“But” she says, “you’ll be at work”.
In the yellow evening I want to hope
Passing through the square with the bunting
The open pub (landlord in gloves)
And the jolly blonde families in deck chairs
2 metres apart, on their front lawns,
The stylish young arrayed with plastic cups
Celebrating victory 75 years ago.
The dead are still dead.
And the living, us
This is the easy part.
Songs on the air in the flower scented evening
Barbecue and take-out beer.
Next week, tomorrow, the beer must be served
The trash taken out
The children taught.
To be alive is
Be alive, until
The spring is spring without you.
(In memory of Barbara Powell, November 1950-May 2002)
We’re deep in the mire of a pandemic, and what’s the promise to let us out? A contract with Palantir to process health data and a serious level of investment in AI systems that are meant to move materials between hospitals. An app whose data about your proximity to your neighbour will be processed to find and notify your contacts. Once again, decision-making machines are positioned as helpers.
How deep does it go, our fascination with machines? With numbers, data, the magic of calculation? And now that this fascination is both legitimate and embedded in the designs of social institutions, what are the consequences? This post summarizes the beginnings of my ongoing work on the politics of explanations, reflecting on how information asymmetries are often sustained by the provision of explanations by some for the benefit of others.
Historian of science Lorraine Daston’s work identifies that it might be deeply embedded indeed. She writes “the cults of communicability and impartiality – again, with or without accuracy – also have an almost unbroken history in the sciences as well as in public life from the seventeenth century to the present . . . even when the truth of the matter was not to be had, numbers could be invented, dispersed to correspondents at home and abroad, and, above all, mentally shared: you and I may disagree about the accuracy and the implications of a set of numbers, but we understand the same thing by them” (1995, p. 9).
In these days of disinformation, deep fakes, and governments who structure their decision-making to render it less easy to scrutinize, it seems worth revisiting Daston’s discussions of how and why numbers and expertise are positioned, valorized and legitimated in this way. Daston calls these processes moral economies – the webs of values that function in relation to each other to build up certain legitimate ways of thinking. Philosopher Charles Taylor and my colleague Robin Mansell use a similar notion of social imaginaries to describe the competing but coherent ways that groups imagine and create expectations (including about the ‘natural way’ to build technologies and social systems).
In my own work, I use the term moral orders to evoke the way that these webs of values and practices build up and gain legitimacy, and especially how they are sustained by being described in moral or ethical terms.
As the hot white heat of AI Ethics has irradiated all of the technology space for the past two years, it’s possible to see the debates about ‘tech for good’ and ‘ethical AI’ as evidence of these kinds of moral justification. What’s especially interesting is how these justifications, once they move out into the world, can become so obviously part of the status quo that they become embedded into the design of technologies.
Transparency, or a lack therof, has come to be seen as one of the main risks of a shift towards reliance on machines in automated decision making. We call for ‘design for fairness’ or ‘auditability’ or ‘transparent design’ as if adhering to certain design principles would produce better outcomes. But if it’s possible to see the biased quality of an automated system, it may not actually be possible to avoid using the system, or to otherwise respond to its failings. Transparency has been much discussed as a necessary, if not sufficient condition to enhance public understanding of how automated systems intervene in people’s access to information, capacity to exercise voice within democratic processes.
Here in the UK (as elsewhere) policy advocates struggle to align existing principles of accountability with the new dynamics of algorithmic or automated decision-making (ADM). In relation to public sector decision making, third-sector organization NESTA has recommended that
“every algorithm used by a public sector organisation should be accompanied by a description of its function, objectives and intended impact. He also called for every algorithm to have an identical sand-box version for auditors to test the impact of different input conditions.”
In a debate on this topic in the UK house of Lords in February 2020, the shadow Spokesperson (Digital, Culture, Media and Sport), Lord Griffiths of Burry Port (Lab) said ” We must have the general principles of what we want to do to regulate this area available to us, but be ready to act immediately—as and when circumstances require it—instead of taking cumbersome pieces of legislation through all stages in both Houses. ”
He asked whether the Information Commissioner’s Office was really the only regulator that can handle this multiplicity of tasks , including online harms and the ADM.
Perhaps a greater risk than a lack of transparency is a problem in relation to explainability. Designing a system so that it’s decision-making process can be explained has now become viewed as an important goal within some of the fields of computer science and analytic philosophy. The expanding field of Fairness, Accountability and Transparency in machine learning (and the associated FaCCT conference) show how much attention is paid to creating ways to structure principles of transparency, bias reduction or well-specified aspects of fairness into computer systems.
These principled, structured interventions go some way to addressing specific forms of bias and transparency. However there is much that they can’t address – including the aspects of automated systems that cannot be effectively explained, including forms of machine learning where the associations made between different elements are dynamic , modulating and based on mathematical abstractions and principles that are not amenable to straightforward causal explanations. This means that ‘explanation’ as commonly understood, cannot apply to all of the aspects of certain types of automated systems. This is one of the challenges in building ‘explainable AI’ and one reason why I have argued that questions about data governance need to be part of the discussion; rather than focusing only on explanation and narrow interpretations of transparency.
Furthermore, the existing research on explanations overlooks an important element of explanation and explainability: the way that revealing or obscuring information operates to direct explanatory power to some actors rather than others. Are designers of machine learning systems the beneficiaries of explanations advocated by researchers who thought they were advocating for public understanding of technology?
This is one among several important questions to consider when looking at the politics of explanation. Others might concern what’s normatively valuable about explanation, the the ways that the history and culture of machine learning systems illuminate values.
Daston’s view of the history of science identifis that what counts as a fact depends on which historical moment you find yourself in. In the current moment, when scientifically verified facts are framed as debatable in part as a means of undermining their influence, and when not only quantifiable but machine-processed information is held as decisive (even when it is not), what can be made of our fascination with AI?
When I twisted my ankle
During the permitted morning run
On Westminster Bridge
(the sound of the tide rushing out with no boats)
I delicately walked past
The hospital where the prime minister
(don’t say dying).
Police at the gates
Panic on the faces of people rushing in
ID cards held aloft, to face the day.
In front, a rainbow floral display
Perpetual plastic flowers
Reads I [heart] NHS
A worker gives it a glance, rushing.
Does she think, like me
That this effusion seems too close
To a funeral display?
Behind, three ambulances
Are lined up
In the emergency bay.
Across the road, a dozen cameras
A dozen operators
Anchors in suits
Producers on the phone
Later their broadcasts speak
Of war and “fighting spirits”
Of bravery and sacrifice.
Down below, in the playground
Of the hospital daycare
A woman runs with a stroller
Mask on her face
Through the doors
With the child
On her way to work.
Every day, rope in hand, I
Open the door.
First thing, the soft smell of flowers
And new greening.
Second thing, the birds
Cooing, calling, tussling,
Floating, blasting like torpedoes
Over treetops, above the flats.
Third thing, breathe in
Cool in the morning, and no sound
But swish of rope and slap of feet.
Step step step
At eight thirty
The man from Number Seven comes
Newspaper under his arm and
Fog of cigarette smoke over
In an ancient oiled jacket
“Good morning, y’all right?”
“As well as can be”
“You’re making progress, girl”
“Well – we have to stop meeting this way”
Every day, I hold out hope that
I’ll see him tomorrow walking
Share thirty seconds of Cockney greetings,
Keep him alive.
“No eggs, you can get them at Lidl but only two”
Says the butcher, handing over bags of chops and mince.
He wonders why I’m not buying more.
No eggs in the supermarket
Someone heard there were eggs at M&S
At Blackfriars, someone’s mum in Lincolnshire had eggs.
We always have eggs.
Eggs in a Tupperware, blanketed in paper towel
Set on the
wall on the patio.
Eggs in a box with a decoration drawn by a young friend
Pushed over the road in a doll’s carriage.
“There were no eggs”, my friend says, then
“Eggs from my mum
Eggs offered when I walked down the street”
Eggs at the wholesalers: we can buy them as a group.
Egg discussions in mobile chat groups
Along with stories of coping in a tiny flat
Being worried about health, work, pay, the future.
Standing in the backyard with applause bouncing off the tower block, watching Venus hanging in the air, clapping and yelling for people who can’t hear because they are inside tending the sick, sheltering the dying.
There are no eggs, they say.
We always have eggs.
The foxes are yelling. The neighbours let out the bath water at the same time as me. But no cars. No planes. The lockdown is coming; the schools are closed now (but my daughter decided this morning that she couldn’t go to school. I could not have forced her, not with the safety of everyone else at school in mind) and soon we will be required by law to stay at home.
The silence has come. Eastenders has stopped filming. There is no Eurovision song contest. No plays performed, no orchestras filling halls with people rustling their sweet wrappers in the moment before the downbeat. This withdrawing is painful, and the silence in central London is both thrilling and terrifying. What fills that silence? Opportunistic crime? Internal mourning?
The silence is also the premonition of death. The very fact that London will soon be under lockdown is because the deaths have outpaced the models. The hospitals are full, and the doctors are struggling. I read the Imperial paper too, and I can see myself, my neighbourhood, on that curve.
Southwark has the most (recorded) cases in the country, and it looks from the numbers (as I understand) that the doubling of the case rate is happening within 48 hours. Mathematically speaking that is f**ing terrifying. I hope my math skills are poor and the reality is not that the healthcare system is already dangerously overloaded and about to collapse.
The silence is an oddity in this busy place. It seems almost shocking. I want to write that it bodes ill, because it does. Because being locked down without people, without song, without solidarity is dangerous. However, the silence is also a space for something else to grow. We stay away, stay in, stay quiet as a huge effort to spare those we love. Our neighours, our friends, our people.
And we hope. We hope that out of the silence will emerge a quieter life, an easier life. This is my hope, although so far I feel far from being able to achieve it.
Today was the first day of teaching online, and between the many online meetings with students and those with research team members here, there, and everywhere I spent the entire day at my desk, facing my small screen!
Into my day, and my house, passed a number of people: a delivery person dropping off a package. The BT engineer who was tasked with fixing my jittery broadband, who alternated between crawling around under my desk and pulling out wires from the cabinet at the corner of the block. My friend, who is a builder and was finishing the tiling and carpentry in my kitchen. Into my house they come, still working (because still needing to be paid, and because the jobs were still on their docket). The engineer asked me at the door, before he came in, whether anyone in the house had the corona virus. No, I said. Well, as far as I know. That I didn’t say. He washed his hands before he left.
My friend finished his work swiftly, drank a cup of tea while I sputtered on Skype and then vanished with a wave. His wife is home, but his work can’t be done remotely. In usual times, he renovates fancy kitchens for clients in Kensington and Chelsea. This week, he’s mostly sorting out the jobs for friends that he usually fits in on evenings and weekends.
Picking up my daughter at school the head teacher is nervous. He is not a nervous man. There has been no information he said, on when they are to close. The school is half empty, with many staff at home, already unable to come to work because of failing immune systems or sick relatives. He’s worried about keeping them safe, about continued access to the right equipment and supplies to keep the school clean.
As my work shifts to being undertaken in different areas of an 11-inch optical screen, these men sustain the physical, digital and social infrastructure of my life. And in the current moment they put themselves at risk to do so. We think of caring work as women’s work, but sustaining infrastructure, caring for the physical environment and the strategic level of the social environment is also care. And right now those carers are at risk.
On the other side of the world, my brother is taking unpaid days off from work, to avoid being on building sites and in busy buildings in his immune-compromised state. Is he too a care worker? In his case, the risk seems too high, for this virus could kill.
Care, risk, sustaining. These acts, these jobs, these responsibilities and relationships seemed so easy to take for granted. Before.
The sun in the early afternoon is very warm. BBC 3 is playing lieder music and dimly I can hear the toddlers who live next door fussing before their afternoon nap. Outside I see birds and some brazen field mice foraging on the bits I dropped in the garden. It is as if everything were normal. Abnormally normal.
And yet. A stillness hangs in the air. An airplane has just passed by, an ordinary thing here in Central London. And yet. Reading the news has informed me that airlines are massively cutting back their flights, so perhaps this ordinary tearing of the air will become more extraordinary.
The UK’s official government policy has not yet enforced the closures of schools nor workplaces. It is however informing individuals to self-isolate, and this, bit by bit, takes apart the fragile infrastructure of society. As privileged folks like me, with jobs done at a laptop start working at home, stop travelling, the numbers of people circulating around this busy city start to drop.
It would be tempting to think of this time of waiting, this gathering stillness as the defining experience of this time of viral spread.
What is happening now is not the story of this crisis. This is not a narrative of this time, but of several other times. In one sense, what is happening now is the preparation for future viral times. Mutual Assistance groups are forming, loosely, gathering together the well-intentioned. The one I’m following seems largely to generate influence in the here and now by informing the well-intentioned about how much work their neighbours are already doing running food banks, community organizations and support networks – as well as linking up individuals who have been isolated and need someone to run to the pharmacy.
In truth though, these mutual aid networks are not for now. They are building capacity for the time when the real narrative of the pandemic begins: the time when many people are infected, and so many are sick that seeing doctors is impossible. When the privilege of being healthy also embeds the responsibility to care for others – and not by adding to a spreadsheet or getting a prescription but by feeding the hungry, washing the feverish, cleaning the floor. Add to this the terrifying realization that many people who are immuno-compromised may not be with us when we emerge on the other side.
The other time of the virus is far longer, encompassing both the recent past and the longer future. This time of the virus includes its origins in animals whose habitats were encroached upon and who became (like people too) enmeshed in a persistent logic of capitalism that has destroyed the regenerative capacities of the earth’s ecosystem, and perhaps the regenerative capacities of people too. I talked a little bit about this in an interview here – but in my hopeful moments I like to entertain the thought that the practice of a quieter, slower pace of work may begin to set the groundwork for the changes of practice that have been necessary for so long – to assuage the climate crisis and to create the capacity for a society capable of regeneration and survival.
There are darker ends to the narrative of course. A country destroyed. A country in mourning for people it failed to save. Individual sadness, anxiety and grief brought on by social separation. Further distress for the people least capable of sustaining it: people living in refugee camps, recent arrivals who don’t feel at home, people struggling to feed their children or who are experiencing violence at home.
As the sun slants away and the animals flit in and out of view, I feel the change of times.
I’m very excited, and a little nervous, to be starting a network focused on understanding and reframing justice and flourishing in the age of AI. Here, I build on the work that we did at VIRT-EU developing ideas about virtue, capability and care to focusing on the idea of flourishing in relation to sustainability (both in terms of accessibility and repairability of technologies and systems) and justice (encompassing both the capabilities of technology developers and an ethical orientation towards care in terms of its consequences). My aim in this network is to begin by understanding the current positions researchers have taken towards ethics, and by focusing on some specific tricky problem areas, to develop new capabilities to work differently, across disciplines. As I wrote below, this is daunting, hence my call for bravery and creativity.
The UK’s Arts and Humanities Research Council (AHRC) and the Ada Lovelace Institute are partnering to establish a network of researchers and practitioners to join up the study of AI and data-driven technologies with understandings of social and ethical values, impacts and interests. The JUST AI (Joining Up Society and Technology in AI) network will build upon research into AI ethics, orienting it around practical issues of social justice, distribution, governance and design. Using a collaborative approach, it will investigate and create research capacity around ‘just AI’ – AI that is ethical and works for the common good and is effectively governed and regulated. The network’s name also points to the need for work on the social and ethical facets of AI to cut through the ‘hype’ or techno-solutionism that often accompanies AI research.
Instigating the JUST AI network
I’ve recently agreed to instigate the formation of the network to convene people working across disciplines and find new ways of linking research and artistic communities together.
In my work, I have been interested in how it’s possible to shift organisational structures and patterns of work (especially in technology development) towards modes focused on collective benefit, regeneration and mutual support. The acronym Joining Up Society and Technology in AI resonates with my longstanding interest in how people create technologies in relation to the values they hold, and how we all respond to their influences. Using AI in the title gestures to the influence of discussions about AI, data and automated systems, and as a general term gives us lots of space to work across the span of techno-social systems in these areas.
Ethics in practice
Looking across tech cultures, doing the right thing or doing good is often evoked as a core value. The network presents an amazing opportunity to develop research into how ethics is practised, as well as to shift the ways that research, policy and practice on ethics are performed.
We are bound up in an ideology of progress through technological development – and want to use our power to shift this progress in a particular direction. But there are important questions to answer about whether aiming for virtuous self-improvement can influence technology within a broader setting of powerful companies, venture capital expectations and continuing injustice often worsened by the adoption of data-based technology.
In this context, we need to begin thinking more of ethics as a practice, and consider how practices intersect with power, and how both may be changed. The end goal of any of these changes, challenges and directions of travel is to enhance the capacity for what philosophers call eudaimonia – human flourishing.
Lots of areas of flourishing are impacted by new data/AI systems, such as health, care, transport and the physical environments of our cities. Of course, in the climate emergency, flourishing isn’t only a human concern; environmental justice and the actions needed to bring forward regenerative culture are important for ensuring long-term flourishing for all living beings.
We need to understand how to enable people to engage with the opportunities and constraints that their life situation presents, and to not only develop themselves but to support others in creating new conditions. Philosophically, taking care and creating capability are also part of the conversation.
The JUST AI network seeks to move work on ethics away from discussions of consequence and towards consideration of practices in relation to long-term flourishing, care and development of capability.
Bravery, creativity and change
In my work I gather empirical evidence that shows the challenges presented by data/AI technologies; for our systems of care, for the places we work and live, and for the living environment of which we are a part. Addressing these challenges requires bravery and creativity, a commitment to connecting and respecting different expertise and ways of working, and open-mindedness about possibilities. I have been accused of being an optimist – and exploring ‘just AI’ with researchers and practitioners will, I hope, provide some new ways forward. I’m so excited to start.