What if machines are more human than we thought?

Can machines become our own creative partners?

Interview to Federico Bomba, Creative Director of Sineglossa, about the impacts generative AI will have on the artistic and cultural domains.

Materahub recently won the national call TOCC Azione 1- Capacity building, funded under the Italian Recovery and Resilience Facility to support the digital transition of Cultural and Creative Industries. The winning project, named “The New Real, A Generative AI Academy” is a lifelong learning class designed for cultural institutions, cultural enterprises, artists, and designers, intending to enhance the competitiveness of the sector by integrating generative AI technology and skills.

To better understand the vision beyond the academy and the philosophical position beyond its design, we interviewed Federico Bomba, Research Fellow of Human-Computer Interaction and Creative Director of Sineglossa, partner of the winning consortium and AI experts.

When did you first approach Artificial Intelligence?

So, I graduated in Philosophy of Language and what I did during my university years was work on epistemologies. At that time, it seemed a field completely abstract and inapplicable to reality. And of course, I was fascinated by the never-to-be-found human consciousness.

So when Artificial Intelligence came about, I thought that the possibility of studying how humans interact and collaborate with machines, through linguistic-based ploys, would have opened a deeper understanding of who we are as human beings, how we approach others and how we do things.

So what is the project and the AI Academy about?

The academy designed by Materahub, Sineglossa and Basilicata Creativa, was conceived not only as a space to disseminate knowledge about this cutting edge technology – there are already plenty of other courses that do that – but rather as a safe space  for the cultural and artistic sector professionals to acquire the tools and, ultimately, to engage with Generative AIs to favour the critical role of arts and culture to transform our lives. This is the spirit of the academy!

The idea is to start with an analytical phase, functional to understand the state of the art by organising two working tables. The first aims to engage for-profit stakeholders in order to understand the needs of companies, what they are working on, and how creatives could be useful within companies using AI generative models.

The second table will be dedicated to the non-profit domain: cultural institutions, cultural enterprises, and artists, aiming to understand their skill gaps for a better use of the AI within their own organisations. For both targets, there will be an initial literacy session, with an overview on the production of texts, images, and videos, choosing from different datasets.

Then there will be MOOC modules in e-learning, with specialized vertical sessions for sub-domains, for example, for those dealing with archives, cultural enterprises, business models, design, etc. In these modules, there will be instructors showing how they have used generative artificial intelligence in their experiences, testing and teaching participants how to incorporate these devices into their activities. In the last phase of the project, we are going to build an ecosystemic approach and bring together tech enterprises, organizations, institutions, and artists in a 1 to 3-day session to prototype new usage for AI tools, but also a path on how to work better together. If on one hand there is a need to learn how to use technological tools, on the other there is an urgency to imagine what and how to communicate to these machines. In the production-consumption model, this is potentially revolutionary and we believe it can produce scalable results.

What is the current understanding of the generative AI tools in the cultural field? And how is AI going to impact cultural production?

My perception is that, despite many professionals working on it, we are far behind both in comparison to other sectors and other countries. Cultural institutions, like museums and libraries, are still reluctant in experimenting new services or products produced by Large Language Models.

I hope the academy can contribute to create prototypes of services or functions that these cultural institutions on one side and enterprises on the other, would want to explore together with content creators.

The significant difference with the past, and with other existing technologies, is that AI speaks our same language. We cannot speak natural language with animals or plants. In other words, for the first time, we find ourselves facing something alien that yet engages in a relationship and information exchange through Natural Language Processing. This is and must become a prerogative, humans do not totally control these tools yet engage with them in the construction of multiple realities. This aspect essentially poses questions about two huge art-related topics belonging to the 20th-century capitalistic approach: that of authorship and that of truth.

Recently, Sineglossa curated the exhibition of Roberto Fassone that, with his work “And We Thought”, challenged what we think is one of the main issues related to technology: the idea that machines facilitate human work. The rhetoric we’ve always carried forward, and partly almost always true, is that we build machines to ease our work.

However, these generative AIs, in the future, will be much more than mere facilitators of human work but true creative companions as they can make choices, in the case of Roberto on how to reinterpret dataset. And this is no different from what happened in the past history of art. We all know that neither Shakespeare nor Michelangelo or Leonardo worked by themselves, they were leading workshops of people creating things, reasoning around artistic processes and technicalities, and spreading collective intelligence. In the same way, AI technologies gather together all the existing intelligences and build different creative worlds, making the technologies creative companions.

Generative AIs are an epistemic technology and not an absolute truth provider. Humans have to learn to interact with these specific machines to define what is their own truth. In this sense, AI enables us to make a bigger conceptual shift acknowledging the fact that what we see and read may not be true just for the fact that we see it and read it. We build our reality as human beings through conventions in an aggregated and social manner. We should not focus on immutable truths, which do not exist anyway, but on the ability to agree on what truth is. Therefore, the development we should pursue is not only in content production but in content evaluation, curation, to choose the right content for creating new meaning.