Review
AI
Art
Culture
5 min read

Art, AI and apocalypse: Michael Takeo Magruder addresses our fears and questions

The digital artist talks about the possibilities and challenges of artificial intelligence.

Jonathan is Team Rector for Wickford and Runwell. He is co-author of The Secret Chord, and writes on the arts.

A darkened art gallery displays images and screens on three walls.
Takeo.org.

In the current fractured debate about the future development of Artificial Intelligence (AI) systems, artists are among those informing our understanding of the issues through their creative use of technologies. British-American visual artist Michael Takeo Magruder is one such, with his current exhibition Un/familiar Terrain{s} infusing leading-edge AI systems with traditional artistic practices to reimagine the world anew. In so doing, this exhibition pushes visitors to question the organic nature of their own memories and the unsettling notions of automatic processing, misattribution, and reconstruction. 

The exhibition uses personal footage of specific places of renowned natural beauty that has been captured on first generation AI-enabled smartphones. Every single frame of the source material has then been revised, reworked, and rebuilt into digital prints and algorithmic videos which recast these captured moments as uncanny encounters. In this exhibition at Washington DC’s Henry Luce III Center for the Arts & Religion, the invisible work of the AI allows people to experience more than there ever was, expanding both time and space. 

Magruder has been using Information Age technologies and systems to examine our networked, media-rich world for over 25 years. A residency in the Department of Theology and Religious Studies at King’s College London resulted in De/coding the Apocalypse, an exhibition exploring contemporary creative visions inspired by and based on the Book of Revelation. Imaginary Cities explored the British Library’s digital collection of historic urban maps to create provocative fictional cityscapes for the Information Age. 

JE: You are a visual artist who works with emerging media including real-time data, digital archives, VR environments, mobile devices, and AI processes. What is it about the possibilities and challenges of emerging media that captures your artistic imagination? 

MTM: As a first-generation digital native, computer technologies – and the evolving range of potentials they offer – have deeply informed my life and art. Computational media not only opens different avenues for artistic expression but provides a novel means to recontextualise traditional artforms and histories of practice; its ephemeral nature is a particular draw. However, this also creates new challenges, especially in areas concerning preservation and access. I sometimes wonder if my art will still exist for future generations to experience in full, or if it will simply fade alongside the technologies that I’ve used in its production. 

JE: To what extent does Un/familiar Terrain{s} build on past exhibitions like Imaginary Landscapes and Imaginary Cities, and to what extent does it break new ground for you? 

MTM: Un/familiar Terrain{s} certainly arises from and expands on the artistic concepts of those past projects. The main difference is that each artwork in Un/familiar Terrain{s} is generated from a small sample of personal data (a scenic moment that I’ve captured intentionally), not digital materials gleaned from large public archives and online collections.      

JE: Do you find that working with images of the natural world (as is the case with this exhibition) as opposed to images of human-made environments (as you did with 'Imaginary Cities') leads to different approaches or inspiration on your part? 

MTM: My projects that explore constructed environments often reference principles of Modernist architecture and design whereas my pieces in Un/familiar Terrain{s} explicitly seek to dialogue with the long history of Western landscape art. The AI systems that I have used in their creation are leading edge but conversely, their conceptual references extend back to long before the onset of what we consider ‘modern’ art.  

JE: I've heard many artists criticise digital art in terms of degrading the principal tools and techniques of artists throughout history and those arguments would be made even more vigorously in relation to AI. In this exhibition you're enabling a conversation about the painterly effects you can create as a digital artist and those that can be achieved through AI, yet without leading us to one side or other of that argument. Is your vision essentially one of wanting to see the possibilities in whatever tools, techniques or technologies we have to hand? 

MTM: Absolutely. For me that’s one of the fundamental purposes of art. AI is unquestionably the most disruptive (and potentially problematic) technology affecting creative communities at present, but it’s just the most recent historical example. I imagine similar criticisms arose during the proliferation of devices like the printing press and the first photographic cameras. Such inventions clearly did not ‘degrade’ art, but they indisputably shifted its trajectory. 

JE: While your work is not expressly religious, you have engaged with theological themes and institutions as with Un/familiar Terrain{s}, which is on show at Wesley Theological Seminary in Washington DC. What do you think it is about your work and the ways you use and explore emerging media that enables such a dialogue to take place?  

MTM: I feel that many of the social and ethical questions raised by the emergence of transformative digital technologies are quite similar (and sometimes identical) to ones that have been traditionally posed by theologians. With that in mind, although the fields are quite different in many ways, at present there are some strange and compelling intersections. 

JE: From your experience, what can theological or religious institutions learn from a more engaged involvement with emerging media, particularly AI? 

MTM: Like artists, perhaps theologians can use emerging (and disruptive) media to not only expand possibilities for their work, but more importantly, to refocus their efforts towards areas that these technologies cannot presently (and will likely never) address. 

JE: Apocalyptic scenarios are often invoked in response to developments such as AI, the refugee crisis, populist political movements or the climate emergency. In De/coding the Apocalypse, you worked with emerging media to explore contemporary creative visions inspired by and based on the Book of Revelation. From that experience, what advice would you give to emerging artists wanting to engage with or invoke apocalyptic imagery? How might emerging artists live in the shadow of apocalypse or what have you noticed about our contemporary fear of modern apocalypses? 

MTM: Throughout history, visions of apocalypse have been consistently rooted in humanity’s prevailing fears. In the Digital Age these sit alongside our growing concerns about technologies that afford increasingly greater potential to create or destroy. Of course, artists should continue to reveal the deeply problematic (and potentially apocalyptic) aspects of new technologies, but they should also highlight their positive aspects to encourage the creation of “a new heaven and a new earth” that can be a better place for all. 

 

Un/familiar Terrain{s}, 30 May – 18 September 2024, The Dadian Gallery, Henry Luce III Center for the Arts & Religion.

Article
AI
Culture
Generosity
Psychology
Virtues
5 min read

AI will never codify the unruly instructions that make us human

The many exceptions to the rules are what make us human.
A desperate man wearing 18th century clothes holds candlesticks
Jean Valjean and the candlesticks, in Les Misérables.

On average, students with surnames beginning in the letters A-E get higher grades than those who come later in the alphabet. Good looking people get more favourable divorce settlements through the courts, and higher payouts for damages. Tall people are more likely to get promoted than their shorter colleagues, and judges give out harsher sentences just before lunch. It is clear that human judgement is problematically biased – sometimes with significant consequences. 

But imagine you were on the receiving end of such treatment, and wanted to appeal your overly harsh sentence, your unfair court settlement or your punitive essay grade: is Artificial Intelligence the answer? Is AI intelligent enough to review the evidence, consider the rules, ignore human vagaries, and issue an impartial, more sophisticated outcome?  

In many cases, the short answer is yes. Conveniently, AI can review 50 CVs, conduct 50 “chatbot” style interviews, and identify which candidates best fit the criteria for promotion. But is the short and convenient answer always what we want? In their recent publication, As If Human: Ethics and Artificial Intelligence, Nigel Shadbolt and Roger Hampson discuss research which shows that, if wrongly condemned to be shot by a military court but given one last appeal, most people would prefer to appeal in person to a human judge than have the facts of their case reviewed by an AI computer. Likewise, terminally ill patients indicate a preference for doctor’s opinions over computer calculations on when to withdraw life sustaining treatment, even though a computer has a higher predictive power to judge when someone’s life might be coming to an end. This preference may seem counterintuitive, but apparently the cold impartiality—and at times, the impenetrability—of machine logic might work for promotions, but fails to satisfy the desire for human dignity when it comes to matters of life and death.  

In addition, Shadbolt and Hampson make the point that AI is actually much less intelligent than many of us tend to think. An AI machine can be instructed to apply certain rules to decision making and can apply those rules even in quite complex situations, but the determination of those rules can only happen in one of two ways: either the rules must be invented or predetermined by whoever programmes the machine, or the rules must be observable to a “Large Language Model” AI when it scrapes the internet to observe common and typical aspects of human behaviour.  

The former option, deciding the rules in advance, is by no means straightforward. Humans abide by a complex web of intersecting ethical codes, often slipping seamlessly between utilitarianism (what achieves the most amount of good for the most amount of people?) virtue ethics (what makes me a good person?) and theological or deontological ideas (what does God or wider society expect me to do?) This complexity, as Shadbolt and Hampson observe, means that: 

“Contemporary intellectual discourse has not even the beginnings of an agreed universal basis for notions of good and evil, or right and wrong.”  

The solution might be option two – to ask AI to do a data scrape of human behaviour and use its superior processing power to determine if there actually is some sort of universal basis to our ethical codes, perhaps one that humanity hasn’t noticed yet. For example, you might instruct a large language model AI to find 1,000,000 instances of a particular pro-social act, such as generous giving, and from that to determine a universal set of rules for what counts as generosity. This is an experiment that has not yet been done, probably because it is unlikely to yield satisfactory results. After all, what is real generosity? Isn’t the truly generous person one who makes a generous gesture even when it is not socially appropriate to do so? The rule of real generosity is that it breaks the rules.  

Generosity is not the only human virtue which defies being codified – mercy falls at exactly the same hurdle. AI can never learn to be merciful, because showing mercy involves breaking a rule without having a different rule or sufficient cause to tell it to do so. Stealing is wrong, this is a rule we almost all learn from childhood. But in the famous opening to Les Misérables, Jean Valjean, a destitute convict, steals some silverware from Bishop Myriel who has provided him with hospitality. Valjean is soon caught by the police and faces a lifetime of imprisonment and forced labour for his crime. Yet the Bishop shows him mercy, falsely informing the police that the silverware was a gift and even adding two further candlesticks to the swag. Stealing is, objectively, still wrong, but the rule is temporarily suspended, or superseded, by the bishop’s wholly unruly act of mercy.   

Teaching his followers one day, Jesus stunned the crowd with a catalogue of unruly instructions. He said, “Give to everyone who asks of you,” and “Love your enemies” and “Do good to those who hate you.” The Gospel writers record that the crowd were amazed, astonished, even panicked! These were rules that challenged many assumptions about the “right” way to live – many of the social and religious “rules” of the day. And Jesus modelled this unruly way of life too – actively healing people on the designated day of rest, dining with social outcasts and having contact with those who had “unclean” illnesses such as leprosy. Overall, the message of Jesus was loud and clear, people matter more than rules.  

AI will never understand this, because to an AI people don’t actually exist, only rules exist. Rules can be programmed in manually or extracted from a data scrape, and one rule can be superseded by another rule, but beyond that a rule can never just be illogically or irrationally broken by a machine. Put more simply, AI can show us in a simplistic way what fairness ought to look like and can protect a judge from being punitive just because they are a bit hungry. There are many positive applications to the use of AI in overcoming humanity’s unconscious and illogical biases. But at the end of the day, only a human can look Jean Valjean in the eye and say, “Here, take these candlesticks too.”   

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