On 8 April 2026 Steward.exe released their first album Humanwear Cuts, free to listen to here and across all streaming platforms. Readers in the UK can see them live as the play their first UK date on 31 May. As regular readers will know, this is a project that I am involved in myself, both as a drummer and percussionist and philosophical investigator.

Together with Luca Severino (and with live performance from Lisa Mos), we have been experimenting on ourselves and with AI, firstly exploring the technicalities of using generative AI to produce sounds and music while in parallel reflecting upon the experience.

AI is used across the board in the music industry today, not only in production and sound creation, but also during the development and execution of promotional materials and strategies. Steward is experimenting with using AI within the creative process. It is not AI generated music as we might imagine it though, but some of the source materials are AI products.

Once the sounds have been generated, they are treated in the same way that any other source might be treated. Sampled, manipulated, chopped and changed. They offer inspiration, rather than being an end product. Steward.exe uses its production skills to create from sources that may or not have been ‘artificially’ generated. Generated thanks to knowledge and technique that Steward possess.

The Steward.exe project aims to be a synthesis of sound research and ethical reflection in the age of artificial intelligence. What does it mean to use AI as part of the artistic production, rather than as a technical assistant? Can we speak of a sort of co-production? If a piece of music develops from a line that was created by AI, is it AI produced? Once the idea has been created by AI can it be forgotten? Or is the end result, regardless of the process, the ‘child’ of that first AI input?

The AI revolution is linguistic. Suno gives the possibility to anyone who wants to create their own music. They have to describe what they want, and the machinery generates music based upon the description. A movement from needing to learn how to play an instrument, to hold a note, to imagine a structure – to being able to describe what we want, to a machine that will then approximate what we are asking for. What about skill? Can we find it in the description? In the prompts? Or is that merely knowledge (or is that also not necessary)?

But reflection brings many questions. Could we see this as the democratization of music production? Who has the right to use its creation, to sell it, to gain from it? Whereas once musicians had the power to create, using their own experience and skills, anyone can now create a song. If anyone can create their own music (and market it and benefit from it) we must be witnessing change in the distribution of power, but is this a democratization or centralization? And is it detrimental to musicians? Or creativity?

And could AI agents do all of this for itself? Create its own music and its own power?

What role does professionality hold? Suno will produce a song from a few search terms, but can a user express professional knowledge and experience in those terms, and can we hear that in the resulting music? We are feeding knowledge into a machine, professional knowledge built from decades of experience. And the machine gains from our experience, it comes to embody our experience. How does this sit within ideas of professionality? And responsibility?

Can we ask similar questions of video production? I am sure we can. See this video for the Steward.exe single Blockroots Tar, AI production, complete with prompts.

Alongside raising these and many other questions, the music raises aims to show how established and experienced musicians can develop ideas that have been generated by AI. The finished product is not the product of AI, it is crafted by Luca Severino, you can hear his style in the music, it is not generic, a mash-up of previously digitized sounds, it is Luca’s sound. The rhythm reflects my style of playing, although I didn’t play it myself (with the odd exception) I can feel myself in the music. Check out the latest video here.

It’s a very personal interrogation. These AI systems have been trained on music whose intellectual property and copyright has not been respected. The black box is closed around even knowing how they have been trained, on which (whose) materials. Possibly including materials that myself and Luca have previously released. All without traceability, payment, or citation.

When we set knowledge down in book form, we acknowledge our sources. We extend previously made arguments, we do not take them as our own.

Best wishes for the new year to all of our readers from all of us here at Technology Bloggers and the Bassetti Foundation.

2025 was a busy year for us all, and I thought I would highlight a development that might be of interest to our tech-thirsty readership.

Poiesis Intensive Innovation with the Metaverse

2025 saw the development of the Bassetti Foundation’s gallery on Spatial. The gallery hosts what we call our ‘Cover Story’, and we open the new year with a focus on poiesis intensive innovation, a form of innovation that does not come from scientific methodology or protocol, but from knowing how to do things. We could think about tinkering with machinery so that it can be adapted to perform new tasks, using materials in unusual ways, the human and non-technological side of innovation.

This is a field that I have been active in for many years, it was the focus for one of my (free to download) books, and the exhibition hosts several pieces of my work within a series of videos about projects we have been developing through the Foundation.

As the Cover Stories change, so does the gallery. You will find images that weave a common thread throughout the history of our activities, connecting STEAM (Science, Technology, Engineering, Art, and Mathematics) disciplines as well as the gender issues that permeate these fields, so crucial to the growth of our society. This provides an overview of the complexity of operating responsibly in research and innovation in a rapidly changing world like ours.

Come and check it out.

On 28 October, Steward.exe released blockroots.tar, the first of a series of tracks and albums from a project that was born from the meeting between Italian composer Luca Severino and myself, Jonny Hankins. As regular readers will know, Steward.exe aims to be a synthesis of sound research and ethical reflection in the age of artificial intelligence. The project emerged in 2025 as a natural evolution of our multidisciplinary collaboration through the Giannino Bassetti Foundation, partner of this blog.

Listen to the track on your platform of choice here.

Steward.exe debuted at the N.I.N.A. Festival in Milan in 2025 with a performance integrating AI-generated compositions, live acoustic elements, and featuring performance artist Lisa Mos as a robot that is learning (through AI) to appreciate music and dance. Further shows followed, in addition to live DJ sets in club settings. The project goes beyond simple technological experimentation to become an artistic manifesto on the creative and ethical dilemmas of the digital age. Through the fusion of generative algorithms and human sensitivity, Steward.exe questions the future of art and redefines the boundaries between creator and creation, positioning itself as a pioneer of a new form of poiesis-intensive, philosophically informed electronic music. We continue to develop the concept through songs, articles, performances, and dialogues, establishing Steward.exe as a benchmark for responsible innovation in the contemporary electronic music scene.

About Luca

Luca Severino brings over a decade of experience in the international club scene to the project, with releases since 2009 on prestigious labels such as Defected and Snatch!. His transition to media composition in 2015 have seen him contribute to Netflix productions such as “Emily in Paris” and RAI productions, his most recent soundtracks including “De Occulta Imagine” by Stefano P. Testa and “René Va Alla Guerra,” the latter of which won an award at the 81st Venice Biennale. With numerous albums of music for images for international publishers, Severino has established himself as a sound architect capable of blending strong melodic elements, electronics, and innovative sound design.

And you know me.

Following on from my last post about Error 0xHUMAN: System Overdrive, I wanted to introduce another music project that plays on the intersection between AI and musicianship. A new work by composer Zeno van den Broek premiered at the Gaudeamus Festival in Utrecht on 10 October with AI powered drum robots developed specifically for the show.

The robots are responsive, learning from the music as it is played by humans. They can develop their own ideas as well as respond to the music that they are emersed in.

This is a step away from playing with a pre-programmed machine, at which point the musicians are slaves to the rigidity of technology, as the technology can influence the sound produced itself.

Another aspect that I find interesting is that the musician has developed a way of communicating with the robots using gestures, very much as we ‘live’ musicians do between each other. And the robots have a light system that they themselves can use to communicate with those surrounding them. They might want to make a change in the structure or sound for example.

The robots can ask for the materials that they play to be changed (maybe from wood to metal), and they can make these requests whenever they ‘want’. The timing of requests changes too, with changes requested more or less frequently at different points by different players.

There are a lot of similarities here with the Error0X:Human project. The line between AI and machine production and human production is blurred. AI is an artistic tool that might also be seen as having its own agency. Both projects raise lots of questions about art, authorship and creativity.

There is an article in the Dutch newspaper Trouw available in which the band members (the human ones) talk about their experience. One of the aspects is that the robots have names and really aren’t spoken about as if they were machines, but as band members. They have gone beyong machinery and into something that has agency. It’s a lovely article to read.

And if you can get to Bucharest on 20th September my colleague Luca Severino is bringing the Error0X:HUMAN project to a new public in a new format…. See below, on full screen.

On 10 May 2025 I visited and participated in the NINA festival (Not Intelligent, Not Artificial). The festival was dedicated to thinking about the various uses of AI within the arts.

The talks were fascinating, as were the installations, and I was fortunate enough to perform myself as part of Error 0xHUMAN: System Overdrive.

This music project involves using AI to create music which is performed with a live drummer and human robot. The show aims to raise questions about the human/machine relationship. Where does the machine begin and the human end? Where does art begin and end?

AI is used regularly in music production, but its use to create music that is then performed and released (and used to generate income) brings a host of questions, including about the right to royalties and copyright. Not to mention musicianship, the rights and wrongs of third party creativity, possible job losses within the industry, increased efficiency leading to lower payment for musicians working commercially, the list is long.

And how does it feel to be a musician who performs through AI? And most importantly, what does it sound like?

You can find out by watching the video, and please comment.

I have just read a short article called Neuralink’s brain-computer interfaces: medical innovations and ethical challenges, authored by Andrea Lavazza, Michela Balconi, Marcello Ienca, Francesca Minerva, Federico Gustavo Pizzetti, Massimo Reichlin, Francesco Samorè, Vittorio A. Sironi, Marta Sosa Navarro and Sarah Songhorian.

You can find it in the open access publication Frontiers in Human Dynamics, and it is part of a series of 10 articles that appear in a collection titled Socio-Legal, Ethical, Technical and Medical Considerations on Neuroprivacy and Brain-Machine Interaction Technologies in the era of A.I.

The abstract summarizes the authors’ positioning:

Neuralink’s advancements in brain-computer interface (BCI) technology have positioned the company as a leader in this emerging field. The first human implant in 2024, followed by subsequent developments such as the Blindsight implant for vision restoration, marks a significant milestone in neurotechnology. Neuralink’s innovations, including miniaturized devices and robotic implantation techniques, promise transformative applications for individuals with neurological conditions. However, these advancements raise critical clinical, ethical, and regulatory questions. From a clinical perspective, BCIs show potential in addressing severe disabilities, but the long-term effects, safety, and usability of these devices remain uncertain. Ethical concerns focus on informed consent, patient autonomy, and the implications of integrating BCIs into human identity. The bidirectional nature of Neuralink’s devices introduces privacy risks, highlighting the need for stringent oversight to safeguard sensitive neural data. Furthermore, the company’s initial lack of transparency, such as delayed trial registration, has drawn criticism from the scientific community for deviating from established norms of research ethics. Regulatory challenges also emerge as BCIs intersect with frameworks governing data privacy, medical devices, and artificial intelligence. The lack of a cohesive legal framework for neurotechnology underscores the importance of developing comprehensive standards to balance innovation with the protection of fundamental rights. Finally, philosophical questions about human identity and agency arise as BCIs blur the boundaries between mind, body, and technology. As BCI technology advances, it is imperative for the scientific community, policymakers, and society to collaborate in addressing the opportunities and risks posed by this transformative innovation.

Beginning with a brief history, the article describes clinical, bioethical, neuroethical, legal, psychological, philosophical, and enhancement aspects of neurotechnological development, with questions of responsibility in innovation running throughout. The authors guide the reader through discussions around risk, cost and benefit, privacy, transparency, the protection and advancement of human rights, regulation, the influence of AI on neurotechnological developments, the primacy of thought over action, posthumanism (the creation of human-machine hybrids), human enhancement, and access for all of such technologies.

This well rounded and easy to read document is an ideal starting point for anyone interested in these fast-moving developments, and is free to read and download here.

If artificial intelligence “works” today, it is not only for technical reasons, but because there is a sort of general belief in its usefulness in different contexts. There is a future, and this future works better, is more efficient, progresses, thanks to AI. In my work this is known as a sociotechnical imaginary (a term developed by Harvard University’s Sheila Jasanoff).

Jasanoff raises questions about the relationship between society and technological development. It’s a kind of co-production, society and technology co-produce the future. Values that are reflected in society are reflected in the technology it co-produces. A vision of the future that includes AI will probably include AI. If we think about the 20^th century, we can find an easy example. In the 1880’s the 4 stroke petrol (diesel) engine took off, and by 1886 the first motor coach was built. The start of the petrol engine world that we know so well today.

But 50 years earlier, Jacobi had already built an electric vehicle. But the vision of the 20^th century included petrol, and visions lead to practices. Research and funding goes toward the vision, and it develops, at the expense of other less successful visions.

Today some in governance are arguing about how much money to invest in AI, which type of AI they want to develop, rules or no-rule approaches, different visions we might say, but they share something. The belief in the importance of AI.

This leads me to a few questions:

What is the role of societal values in AI?

Who has intellectual copyright of the process, the data used and the results?

Is AI becoming a game for the ‘big boys?’

Opting in, or opting out?

Do you have the right to have your data excluded from calculations?

Privacy (not only data, but AI used to identify individuals from the way they walk etc).

Do institutions of governance inform the population about their use of AI? Do they have the technicians necessary (and ethicists) to implement it correctly? How efficiently does the City of Amsterdam Algorithm Directory inform its residents? Or the Dutch National governmental register? Could I understand anything within their databases?

Can AI lead to the amplification of criteria of prejudice?

Are we not entitled to an explanation of the decision-making process? The AI act (process began in 2017) calls for a human-centred approach and explainable AI (XAI). According to the GDPR (EU Privacy regulation), residents have the right to an explanation of how the model made its decision, and the AI service provider the obligation “to make the logic behind a recommendation transparent and humanly understandable” (not only for yes and no decisions but also for example travel organization.

How environmentally and economically sustainable is AI?

OpenAI requires ~3,617 HGX A100 servers (28,936 Graphics Processing Units) to serve Chat GPT so the cost per query is about $0.36 cents. Running ChatGPT also implies an environmental cost, as it uses 500 ml of water for every 5 to 50 prompts it answers. This water is used to cool down the supercomputers that generate heat after using its computational power (Taken from this blog).

Deskilling and reskilling. Effects on the world of work? Diversity and inclusion if AI is used in pre-selection of candidates (will it favour the typical model)?

And how should we think about human-technological-AI interfaces: AI enabled medical devices and software. AI diagnosis? It might be quicker, but will it make all the same mistakes, miss all the same people?

Can we open the black box?