The Principles of Nuovo Abitare

  1. Enormous quantities and qualities of data are necessary for our survival. Our globalized and hyperconnected world exposes us to complex phenomena. To be able to understand them and to deal with them, we need enormous quantities and qualities of data. Without them we are not able to understand and experience the world we live in. All of us, simple citizens and global corporations alike. Our dignified survival and the possibility of enjoying our rights and freedoms are at stake. The pandemic that began in 2020 is clear proof of this. And soon climate change, migration, energy, poverty etc. will come. Data and computation are necessary for our survival and for our ability to make sense of the world: they must get out of technology and enter culture.
  2. The data is no longer what it used to be. The age of industry was linear, and data was important because it could be counted. Now is the era of networks, and nothing is linear anymore: everything is interconnection. Even the data. In the enormity of globality and in the condition of hyperconnection, data is no longer important because it can be counted, but because forms and recurring patterns can be found therewithin. Which is what the AIs do: they find shapes in data, like we would find them when looking at clouds. This shift from counting to form and aesthetics marks an epoch. This opens up new questions, because “finding recurring patterns” means “interpreting”. When computation “interprets”, ethical problems arise and the possibility of attributing responsibility. These are relational issues, of sociology and psychology of algorithms which, given their complexity, are only partially controllable by their creators. New social roles are needed for computation, new relationships, new alliances. Computing cannot remain closed in data centers: it must be with us, in society, in communities, in the environment, in public space, and it must be possible to negotiate, make friends, argue, denounce a computational agent, just like with any other actor of our societies.
  3. New alliances with computational agents. It is therefore necessary to devise new alliances with computational agents, because we have no sensitivity to these enormities of data. Without these new alliances we cannot survive in the world. Computation can transform and translate the data we need to inhabit the world into new sensitivities, visualizations, lights, sounds and new tactilities.
  4. Data as common ground, computation as translation and for establishing new relationships. Everyone produces and can produce data: people, animals, plants, forests, buildings, cities, communities, companies, territories, viruses. Data, therefore, can constitute a common ground for all these actors of our ecosystem, on which to meet and establish new relationships and new sensitivities.
  5. From extractive models to generative models. Data and computation are currently interpreted according to extractive models, just like oil. This is highly problematic, and underlies almost all of the issues that are manifesting globally regarding data management and the violation of people’s rights and freedoms. Currently, data is extracted (from the environment, from people’s behavior, crops, markets, services…), and separated from the context, to then reappear in the form of products, services and decisions. It is data-colonialism. On the other hand, data could and should become “zero kilometer data”, “community data”, “locally sourced and managed data”. Which does not exclude industry. What it does mean is that that this industry must be sustainable for the environment, for society, for people’s rights, freedoms and psychology. Having zero kilometer data, close to the person or agent who generates it, allows addressing all the problems of the data supply chain in novel ways, from those of privacy, to portability, to verifiability, up, up, up to the enormous environmental unsustainability of large data centers, which melt the glaciers, where, instead, to keep the data of my farm I would just need a solar panel for a few euros. From the extractive models it is necessary to move on to generative models, in which it is the actor who generates and maintains the data, and makes them available in an ecosystemic way, individually and according to its roles in communities and in society: data becomes autobiography, expression, self-representation.
  6. New conception of digital identity: from digital identification to digital identities. Data is closely linked to the issue of digital identity. The digital identity model that is taken for granted is very far from digital identity as it manifests itself in reality. In fact, identity, in digital systems, is a concept that has many more variations than the concept of identifiability that is used in its place. Digital identity can be individual, anonymous, collective, temporary, transitive, and remix of all these modalities (for example a collective and temporary identity to represent all the participants in an event without necessarily having to identify them). The major problems encountered with respect to data processing (for example privacy, interoperability, etc.) have precisely to do with this discrepancy between identity and identifiability, between what is in the world and what exists in bureaucracies, administrations, in services. For example, we, as a research center, use a protocol called Ubiquitous Commons that provides this very natively digital identity system, in which, just like in digital life, I, subject X, can have multiple identities: individual , anonymous, part of the collective identity of my condominium or my company, the transitive identity of when a loved one dies and transfers to me assets (and data) as an inheritance, and so on. I produce different data with different identities: when I configure my smart boiler I put my individual id to pay the bill, the condominium id to calculate energy efficiency and a transitive id for when I will have to do the transfer. It is cultural models that need evolution, and the bureaucratic and administrative models: the technologies are already there.
  7. End of Human Centered Design, beginning of Ecosystemic Design. Human beings are not at the center of anything, and when they think they are, it has always brought trouble. Human beings are just a part of a relational ecosystem with other human beings, the biosphere, the environment, organizations, institutions and so on. We need to start planning for this network of relationships or interconnections, not according to some bizarre Renaissance conception that sees the human being at the center of the perspective.
  8. The role of art: senseability. We have no sensitivity to all these different quantities and qualities of data. Furthermore, all the expressions of the many players in the ecosystem, which can be experienced through data, correspond to completely different senses and sensitivities. To experience these very different expressions, therefore, we must prepare ourselves to come into contact with different, alien, queer sensitivities, which must be translated into each other, beyond usefulness. This is the role of art: to make these expressions and representations senseable, that is, exposed to the senses and, therefore, generating sensation and meaning.
  9. Data and computation are the greatest cultural heritage produced by humanity. This enormous continuous process of translating data into cultural artifacts through computation is unparalleled in the entire history of human beings, for its richness, diversity, variety and ability to express cultures, languages, places, times, traditions, methods, processes and every other element of our ecosystem and our civilizations.

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