Data centers, which run all the AI of today globally consume about 143 million books’ worth of data everyday. Every second, they need water which is enough to provide daily water for about 2 million people. AI is the central reality of our times. It’s a reality centered on massive amounts of human data scraping (often without awareness of humans) and massive amounts of extraction of Earth’s resources. AI machines collect every aspect of our lives in data and are able to manipulate that to influence our lives in all kinds of ways- from potentially naive aspects like what shoes to buy to influencing elections at scale. We are caught within filter bubbles and have no awareness of the ideological walls we are trapped within. We, as human consumers share all this data willingly- almost like offerings, very much like making offerings in ritualistic practices. This data requires processing with huge amounts of compute powered by indiscriminate extraction of resources- with data centers set to account for 21% of the global energy needs within 5 years. The offering we are making, in massive amounts to the robots is that of data and the climate. This work highlights that process, hinting at the evolution of the superior being to AI robots and our evolution of rituals along the same lines.

In this work, the artist uses AI to speculate layered pasts rooted in the socio-political context of the present. The artist works with architectural structures symbolic of the diverse cultural influences of India’s past. Cut out parts of these are juxtaposed with AI imagined erasures of this diverse richness to hint at the present’s tense narratives around these themes. The past is always moulded in the politics of the present. Could technologies of today then, the same ones used for percolating these narratives, be used for perceiving these pasts in alternate ways? Is this an act of encroachment, hybridization, erasure or simply forced speculation?

Through this work, the artist builds on Hieronymus Bosch’s famed work ‘The Garden of Earthly Delights’ to question the idea of delight in today’s times, and the metaphor of garden as a place for relaxation and enjoyment, simultaneously a place for establishing and maintaining a sense of identity. The artist draws this parallel to digital gardens of today- data centers and digital filter bubbles, created with the g(u)ardening tools of AI like drones, surveillance, data, algorithms. The role of the gardener draws parallel to the role of the the human labor in AI. Often wrongly perceived as a self-functioning independent entity, AI builds on the labor of millions of invisible people sitting hours in front of screens tagging data, looking at extremely disturbing content for moderation, all to maintain a sense of digital delight and properness. The digital delight is crafted and curated to keep people in the confines of bubbles, enforcing an identity trapped in this guarded garden.

The artwork is a 3 minute 41 second quadriptych (4 part) video work with custom made audio, artwork made in 2023. The artwork will be displayed in 4 square digital displays or 2 horizontal digital displays, preferably at a right angle wall, with 2 parts of the video playing on each wall. Each part of the video talks about different notions of the digital garden today, with one part speaking about the labor involved in creating and maintaining such a digital garden.

The last 2 years have radically changed how we live and engage with the world. Stuck indoors, people have found new ways to feel a sense of belonging and liveliness. It has accelerated our journey to becoming increasingly digitally native, existing more in bits and bytes than atoms and molecules. In this work, the artist creates an apartment facade, though replacing windows with screens, which act both as a means to communicate our digital identity and engagement with the world, an entry into embracing the metaverse, and to capture each of our own solicitation in the digital for companionship. The screens show performative works generated with AI, where the artist ‘learns’ by downloading via an AI new hobbies like dancing, yoga while being stuck inside digital windows (onto his avatar).

Through this interactive work, my earliest artwork with AI (made in 2015)- i began pondering the question of coming together of human and machine creative expression. Tandem is an interactive drawing tool, with an interface like any simple drawing application, however it’s one with an AI capable of ‘imagination’- which can turn your doodles into something unexpected and invite you to have a visual creative dialogue with itself. The audience begins the interaction by doodling or drawing something. The audience can then select a ‘personality’ type for the AI between options of ‘Happy, Dreamy, Dark, Angry’ and a non-personality option of ‘Pencil’. These give different visual stylistic outputs. The other choice to make is between ‘Abstract’ or ‘Figurative’ outputs- this results in the AI output to vary from abstract pattern outputs to more figurative identifiable elements based on the categories of AI’s training. The system works using the Deepdream AI technique primarily, which relies on AI’s training on the Imagenet dataset comprising ~14 million images in 1000 categories. The distinction between Abstract and Figurative happens by determining the layer the Deepdream algorithm uses to be the final layer in each step of its creation. Abstract patterns are achieved by chosing earlier layers in the Deepdream algorithm and figurative ones achieved by letting the Deepdream algorithm run till the final layers. The ‘personality’ is applied with the Neural Style Transfer Algorithm run on the Deepdream output using pre-curated images for each category of the personality. For the pencil stylistic category- i use a custom written Open CV script to transform the Deepdream output to a pencil sketch style artwork. The Deepdream algorithm comprising of Convolutional Neural Networks was a major breakthrough in deep learning, exhibiting the machine’s capability to ‘imagine’ visual material. Through Tandem, the input for machine imagination is human doodles and Tandem explores this interaction from the capacity of forming a human-machine creativity continuum.

When the human starts to doodle something, the AI ‘recognizes’ it as objects it knows and the biases inherent in it. It then imagines on top of the human drawing with each iteration of its creation. The human could choose to continue this cycle of imaginations by editing the machine’s output or re-feeding it its own output. Someone interacting with this work experiences the eerie continuities and discontinuities between the human and machine imagination where our own human visual categories (which the machine has been trained on) are filtered and estranged through the (sometimes alien) associations the machine makes. Mindless doodles often turn into definitive objects which we might not have imagined ourselves, however once we start to see those emerge from the machine’s imagination- we start to associate with those objects in the context of our drawings too. It becomes a playful mechanism to peep into the inner functioning of the AI’s algorithm or ‘imagination’ too. This was a critical part of the thinking behind the work, especially given how new the idea of AI generating completely new visuals was back when Deepdream released- making an interactive system to explore its workings would invite people to form their own insights and relations with the machine rather than being prescribed one. Such active engagement with AI systems is crucial for taking ownership of the narrative and influence of these technologies, in debunking their hype and confusions- instead creating more tangible ways to critique it.

The output raises some pertinent points to ponder. We are left to wonder whose was that final drawing? The human interlocutor’s? The AI’s? Or does it really belong to the deep formal patterns in the human subconscious that the machine learns through looking at the way we form associations between the verbal and the visual?

Tandem has been exhibited internationally on various occasions, including at the early AI Art exhibition (alt-AI at the School for Poetic Computation in 2016, about which you can learn more in this video of interviews https://vimeo.com/189974949). This video piece records the functioning cycles of the system- from human doodle or sketch to selecting parameters of input and the AI made output in steps of emergence.

In this 2 part video artwork, the artist looks at abstraction through the contemporary lens of machine aesthetics. Grounded in his practice of exploring machine intelligence and emergent aesthetics for over a decade now, the artist works with intergenerational and inter-geographical representations of abstraction art. Can we teach machines the aesthetics of abstraction, can we use its capabilities to lead an inquiry into the dialogue and departures between eastern and western approaches and aesthetics of it, between the figurative and surreal comparisons and influences of it. Can we build on the inherent nature of digital repeatability fused into it and evolve it to take contemporary forms of movement and dynamism. Above all, machine intelligence or ‘artificial’ intelligence based art in itself is a craft of abstraction drawing from data (or accessing inputs from machinic memory), combined with codified processes. In this work, the artist attempts to augment the aesthetics of abstractionism and our engagement with it through a machinic lens of enquiry to them.

In this work, a viewer’s facial expressions are transformed into those of a (female) Kathakali performer juxtaposed simultaneously with that of a (male) Theyyam ritual performer.

Kathakali is a performance art deeply informed by upper caste, Sanskrit aesthetics and epic, patronized by royal families and “sattvic” temples (where typically the scheduled castes had no entry); Theyyam, a deity possession ritual, is locally varied and participated in typically by the lower castes in India. Here, i try to create a work, which uses the same technology of facial recognition being used for surveillance and perpetuating bias further, in the context of being used here as a medium for social empathy, to bring light to social justice frameworks, where one sees themselves as both an upper and lower caste performer, a female and male form simultaneously.

There are 2 AI algorithms at play here. The first learns to identify the structure of a face in real-time, and the second learns to generate corresponding performance art faces by transforming the detected face to a face with painting rituals of a Theyyam or a Kathakali performer. The system runs in a real-time interactive manner with a modified surveillance camera and 2 Generative Adversarial Networks (GANs) running simultaneously.

Here, i teach an AI what the human insides look like by showing it several videos of surgical operations and dissections. The algorithm is then allowed to produce its own images of imagined dissections, which are
animated to mimic the flow within. By experimenting with the amount of training the algorithm gets, i try to generate vivid abstract painterly images which recall Shiraga and sometimes de Kooning. There is an ironic reference to Rembrandt’s early masterpiece in the title- that painting (The Anatomy Lesson of Dr. Nicolaes Tulp) was produced by Rembrandt in an era of troubled fascination with medical technology- this one is produced by AI, in an era of troubled excitement about its rise.

This work was part of the iconic ‘Gradient Descent’ AI Art show in 2018 at Nature Morte Gallery in Delhi, India. It is touted as the first AI Art show in a contemporary gallery globally. i was the only Indian artist among 7 global AI Art pioneers. The other artists were- Mario Klingemann, Anna Riddler, Tom White, Memo Akten, Jake Elwes and Nao Takui.

One of my early works made with GANs. i’ve often stated- generative AI models should feel more like pencils and not stencils and GANs feel like that.

Do Universals Exist? Both western and Indian philosophies have been very concerned with how we intuitively form universal concepts (like blackness or even numbers for instance) when all we have access to are objects that are similar or dissimilar in several ways. Plato, for instance, famously concluded the only reason we think something is beautiful is because ‘Beauty’ actually exists in the world of ideal forms! But this is a debate that is still ongoing. A question i try to pose with this artwork is- how would a machine understand a universal quality, given all it sees are examples. The images it produces tell us something about our own selves, refracted through the alien eye of the machine looking at the way we attach words to the world!

Here, i use Attn GAN to create the work, an AI model that uses a massive database of images with captions (like “facade of an old shop”) to learn verbal-visual connections. It is then trained to produce images for sentences it has never seen before. In particular, it is asked to produce images that correspond to sentences like “This is white” or “This is black” which elicit from it its visual representation of universal qualities like ‘old’, ‘young’, ‘black’, ‘white’ etc. Each column pair represents one such universal notion and and its opposite. The overall collection of images is reminiscent of
Beeple’s famous ‘Everydays: the first 5000 Days,’ bringing to the fore the aesthetic of multiplicity (often inherent to digital art, especially AI and generative art) here created through human-machine partnership.

This work was inspired by conversations with 64/1 (Karthik Kalyanaraman & Raghava KK).

Part human, part human-machine (hand)writing.

We are increasingly offloading a lot of our mental and subjective tasks to machines. In every such interaction, we effectively authorise the machine to momentarily substitute for our mind with its own intelligence, taking decisions and executing (its) plans on our behalf. We achieve an output and feel ownership of it, without explicitly knowing how we achieved it. We have become so accustomed to internalizing this substituted mind, that we do not even acknowledge its authorship in our tasks, let alone reflect on its influence in our everyday thoughts and actions. In this scope, we investigate how this relationship evolves, when the substitution leaks out of just the cognitive domain, and finds its way onto our physical body. For this, we create a handwriting system, where a machine moves our hand on a paper surface to write out its thoughts. How do we feel when our hand ‘mindlessly’ moves on the paper, but eventually writes something meaningful. What happens to our relationship with this other author of our everyday lives as it rises out from behind the surface onto the tips of our hand. How does our sense of ownership of the handwritten outcome vary, if at all? What’s the effect if our own thoughts and actions write all the content, half of it, quarter, none? Offloading how much control to the machine is enough? Also, a lot of entities and their intelligences are involved in writing this piece of paper- the user, the machine, the creator of the program, the various people whose text and thoughts for the part of the dataset- all that eventually makes your hand write something. This already happens in our everyday lives to some extent, often without us explicitly realising. However, once carried through a physical medium, does it make us more aware of the multitude of intelligences we inherit in our everyday, simple tasks?

How do we ultimately extend this experience to rethinking the balance of authorship and authorisation in our lives, especially as machines continue to grow in their intelligence?

Made in 2017 during a residency at X-Lab in Japan with Prof. Yasuaki Kakehi and Junichi Yamaoka.