The National Gallery in London is currently exhibiting a selection of Caravaggio’s paintings. The exhibition includes also those that imitated Caravaggio’s style. As I was given the space to compare Caravaggio’s work to his followers I understood which is the factor that glues me in front of any Caravaggio’s work: “the space in between”. When I stop in front of any of his work I have the feeling that the painting is meant to fill the space between myself and the canvas. The scene looks as a suspended action, not a frame, but something that is meant to continue . A looping tableau vivant that never gets completed and it is open to a plethora of interpretations. The way light, colours, characters are composed together makes the scene extend beyond the space of the canvas; time and the subject become relative. The space in between doesn’t have any shape; it is an intimate place that each viewer can design through observation. The space transcends any subject, wether religious or mythological. The subject is the pretest of a superficial interpretation; once indeed the subject disappears, the tension of the space in between bounds the viewer to the painting. The tension is made of different factors: light, position of the character, emergence of part of the scene that hides others, etc. The effect of the painting reaches my senses without any specific reason. The ability of the painter consists indeed in the creation of a suspended place that leaves any viewer the freedom of interpretation. Caravaggio must have been a good observer of street dwellers. His characters’ eyes, facial expressions and body’s posture are his language through which he designs theatrical scenes of chiaroscuros. I suppose that the universality that Caravaggio’s paintings give to any society is given by the freedom each of us has to imagine what we see in it, without any guideline. When visiting the exhibition try to have a go without audio guides!
In our daily life we interact with different “humans” – colleagues, friends, partner(s), family, etc. Our interaction is not at all linear. We get excited (😊), angry (😡 ), annoyed (😒 ). We, humans, react to human to human interactions with emotions, which is a kind of language that expresses our thinking beyond, and within, our social and cultural background. Human emotions can be unpredictable; they constitute the glitch of human interaction, and require some planning and exercise to understand, and possible, predict human reactions.
In our social interaction everyday we are quite often catalogued by data. Our behaviour becomes a cluster of information, which informs patterns that put us in a box. Such system is increasingly becoming the way to get a job, a relationship, a morgage. According to data we are patterns of behaviour that encode the possibility of an event. In her book “Weapons of Math Destruction” Cathy O’Neil describes the frustration of such a system applied to humans. She indeed describes how the pattern based social hierarchy discriminates more than a human based judgment. Such a system, indeed, doesn’t take into account the unpredictable factor of human reactions, the human glitch that makes us diverse, unique and odd, which is the beauty of being human.
Here I am not suggesting any better system, which is capable of encoding the human glitch. Human beings are special animals, which life is made of productive and less productive moments. In this blog I quite often come back to the Roman concept of otium and negotium: enjoy your laziness as much your productive time; otium and negotium are complementary aspects of our being that make us a better humans in society. IN this specific case otium is the glitch. Data are a great system to cluster information that reveals patterns that tell us a different truth. Such truth is not the absolute system of reference, but one of the many that any of us should look at to evaluate decisions, whether it is the case to get pissed off, or the journey we like to take or employing a candidate.
In this article from the Harvard Business Review it is recommended to not swear at any form of AI; as they are learning from us it may cost our career. In other words we should start treating AI with respect. Please do not use inappropriate language and think them as kitties.
With Tay Microsoft had quite an experience in learning what happens if you leave your AI follow Internet trends. Humans, we know, are not always nice. In particular the Internet gives us many examples of how human interaction is not always for the good of knowledge.
I would like to reflect on another point though, which calls AI speech improvements. One of the best features Google Pixel offers is Google Assistant. Assistant learns from you and your interaction with the phone, hence the world around you. By learning your behaviour Assistant can anticipate your actions, can join your conversations and interface with third parties like Uber. Google AI relies on an improved “understanding” of human-like thinking and language. As its human resolution gets better you might end up establish an empathic relationship with your AI and treat it as human.
Nonetheless do we need to create different kinds of humans? What can they offer to us, more than mimicry our actions to the point of believing them alive entities? Chatbots are currently used to replicated our beloveds when they pass away, by learning “language styles”. What is the ontological social role, and value, of AI? Do we want them to give us immortality? Do we want them to replicate us? Do they need then to develop human empathy? For which reason? I suppose one way to analyse the context is language. Language, indeed, is the first human vehicle, whether written or spoken, that helps with establish relationships. We do need a form of language to establish any form of connection with the other party. As AI navigate the blurred threshold of quasi-human, as we do, we can acknowledge their “being”, hence their social presence, by giving them a language. Such action blurs the human-AI threshold and makes us, human, look like machines. Is this what we want?
On another hand can machine have their own language, based on the skills and opportunities they cab open for us to live a better world? By changing the way they speak I suppose human perception and understanding of AI might take another route and open different kinds of opportunities for human-machine collaboration.
Semantic search seeks to improve search accuracy by understanding the searcher’s intent and the contextual meaning of terms as they appear in the searchable dataspace, whether on the Web or within a closed system, to generate more relevant results. Semantic search systems consider various points including context of search, location, intent, variation of words, synonyms, generalized and specialized queries, concept matching and natural language queries to provide relevant search results. Major web search engines like Google and Bing incorporate some elements of semantic search. (from Wikipedia)
For the common good we should get familiar with semantic search, as it will soon change the way we acquire knowledge and learn. In this article in Forbes it is illustrated a a very interesting perspective on how our interaction with recent AI based technology is shifting our methodology of learning. The metaphor which I think works the best, as explained in the article, is to consider current search engines as funnels. We search for something and get a narrowed list of answers. The more the search engines knows about us, the better the answer is accurate. However human brain is great on pattern recognition; we are capable of linking different elements together – which includes our own background, our expectation, our bias – that affect what we are looking for. In the book Diffusion of Innovation Everett M. Rogers defines information as a process through which we reduce uncertainties when in an unfamiliar context. In other words we search to get a better picture of the context; we are not naturally looking for a specific answer, but an answer located in a context that makes sense for us.
Hence Google knowledge graph-based search. It is a search process, introduced in 2012, which looks at the context, at the user, at the location, the language, i.e. the context the search happens.
However when we speak to Siri, Google Now, Cortana, Alexa, etc we don’t get anymore a series of links, but a single answer. We are no longer allowed to select what we want to read, either the source. According to the Forbes article this system will reshuffle the information business.
Nonetheless in this post I would like to focus more on education and research. Looking for different kinds sources, connecting/disconnecting them, prooving the “truth” are actions at the core of research and knowledge. If we have a single platform that provides answers, will we be still entitled to understand where information comes from? My provocation to this is the following: context and mapping.
My guess on how human being will still find ways to be curious, investigative, to challenge assumption and axioms (for Google we would be probably still living in a flat earth, if the answer was provided by algorithms that assemble information) will be the skills on understanding and compare different contexts and map answers in a bigger picture. Basically flipping the way Google intends to map its search engine and use it for exactly the opposite. We may be able to funnel research the other way around.
One of the projects exhibited at the Oslo Architecture Biennale – which is described in The Guardian – tells the story of Mark and the experience he provides through Airbnb. Mark’s homes stage family everyday living. You will find family’s pictures and anything that will satisfy your imaginary of renting a family home. Well, it’s all fake. Mark’s business hacked the Airbnb’s keystone value: dwelling the everyday of anybody’s home with all the memories, artefacts and memorabilia that each of us collect along our life.
Airbnb’s strategy, indeed, uses the human’s perceived meaning of intimacy into a business value (which Mark flipped into the core of his business). The more the host makes you feel home, the more the accommodation will provide the experience – and good rating- you are expecting to live visiting the place, whether you ever been there or not. Intimacy is no longer a private sphere of our being, which takes shape through a series of objects we relate to. Intimacy is something you can sell. Your life goes on market (and rated), as much your image does with selfies.
Airbnb is not the only company “looking after” people’s interiors – with the collection of objects and memories; Amazon and Google are also on the same page. Amazon Alexa is indeed an artificial intelligence capable of sensing the environment. Alexa learns from you, about your taste, what you read, the music you listen, the place you visit, the friends you see,.., the list is quite long; Alexa absorbs your life, so that it can “suggest” Amazon what to suggest to you. Whether in Airbnb your intimacy mimics the social masks you need to wear to perform the character your house is placed in (romantic, modern, family, etc), Alexa moulds the character (you indeed).
Similarly Google is shifting its business approach by changing what made them very successful: search engine. According to this article in the MIT Technology Review Google is ready to introduce Assistant to the public. Assistant is a “third person” that reads you and the environment you are in (physical and digital) to make suggestions. The ambition is to turn Google search from a general page you can type in to a custom, interactive character that suggests information, whether asked or not. Assistant can enter a conversation you are having with friends and make suggestions on the topics of discussion.
Alexa, Assistant and Airbnb make design the Shell (under Venturi, Scott Brown, Izenour’s perspective) of technology, at different scale of course. What does design propose more than decorating technology’s performances (both aesthetically and technically)? Is there any value that design adds, besides embodying sensors that can connect you to the Internet? Interiors and products are interfaces at different scales that provide information. We interact with spaces and objects through algorithms that “learn” our behavior to loop information back to the private company, then us. What we achieve is a chewed digested information. If interiors will be probably designed to satisfy the best AI scanning (as currently shopping mall are designed to give shops the most of visibility) and objects to keep us “busy”, what can design do? Probably I need to define what I mean with design. The human passion for making and working with materials, thinking about mechanism, sorting problems, satisfying needs. Does design still performe a service to society?
Last year I went to the National Gallery in London to see Francisco Goya’s exhibition. I did enjoy the painter’s mastery on giving human character to his portraits by balancing the relationship between the background, often solid colour, and the subject. Goya doesn’t draw a border between the two; he blurs the boundary so that the subject emerges from the background. Such simple operation gives a sense of the character’s personality; the balance of colours – and chiaroscuro – that gradually progress from the background to the the face and the body returns to me (the interpreter) the experience of the subjects’s personality.
Current research on AI is moving towards giving machines a sense of space, by teaching them what is space (as we do). Through Deep Learning machines are growing the sense of reality. They are developing a form of knowledge that is capable of understanding objects in real space, by means of image pixelation. In this article from MIT Technology Review it is described how machines are capable to detect physical objects via digital images; pixelation is the language they employ. The differential between the background and the given object is indeed in the focus of attention. On the opposite of the poetic skill Goya used to give a sense of the subject’s personality, the understanding of “border” is the key element used to teach machines space. The intention is to teach machines to “see”, and I suppose think, like us. Digital image pixelation is the vehicle that machines use to understand the real as we do.
What is the real?
Quoting Slavoj Žižek’s: “Every field of “reality” is always-ready enframed, seen through an invisible frame. The parallax is not symmetrical, composed of two incompatible perspectives of the same X: there is an irreducible asymmetry between the two perspectives, a minimal reflexive twist. We do have two perspectives, we have a perspecive and what eludes it, and the other perspectives fills in this void of what we could not see from the first perspective“.
In other words we, human, don’t see things as our eyes do. There is a gap in between that constructs our sense of the real. As quoted from Žižek, there is a void in between that we fill with our imagination. Imagination is a form of expectation of the real, which is linked to our past experience that, in our mind, has been stored in the form of memory.
How can such a random and complex fluctuation be translated to a machine? What we call “real” is nonetheless a specific frame of our perception, which doesn’t make any distinction between digital and physical, as everything gets stored in our mind in the form of experience. It kinds of makes me think back to the Ridley Scott’s Blade Runner, which machines desperately need pictures to be acknowledged as humans.
Žižek, Slavoj (2006), The Parallax View, Cambridge MA: MIT Press
Scale is a concept I’ve got familiar with since my first year in Architecture. I am been taught that drawings have to be in scale in relation to the context. What are you trying to communicate? Scale is quite crucial because it defines the resolution of the drawing.
In design practice scale is indeed a very important tool, as it renders intentions in function to context. The understanding of scale change is a skill designers need to master, as it is an intangible infrastructure that crosses and overlaps networks, which context might not be related. Scale makes analogies among diverse territories; of course it is important to understand which analogy enables connections.
The complexity of our society claims for feasible and transferable analysis that modifies over time. Social changes fluctuates at a too high speed for a stiff infrastructure.
I am on my way back from a two days debate over urban globalisation. The LSE/LSECities/Alfred Herrhausen Gesellschaft organised an incredible conference, Shaping the City, on global urbanism. Under the roof of the Venice Biennale Foundation and the support of UN Habitat the conference clustered around proposals that will be taken to the Habitat 3.
The word conflict looked to me the continuous thread that linked the many contributions. Conflict is an interruption, which can trigger positive reactions if channelled towards directions where the contrasting factors negotiate a common territory. Like scale, conflict is as universal as local. Nonetheless when conflict meets scale noise is remouved and attention is kept at core factors. It then follows that scale makes conflict a chameleon entity, as it can be interpreted and tackled via different methodologies, in relation to the specific key factors that draw any analysis.
Scale gives conflict resolution and, by connecting different territories, it helps to see beyond peculiarity to find similarities in other related territories that help find solutions.
I believe scale is a key factor in the contemporary process of design. To understand solutions, that challenge and innovate the existent, is a dynamic fluid process of scaling up and down. One problem doesn’t match one solution but an array of proposals rendered at different scales and resolutions.
Society is far too complex to be looked by stiff systems. As design is the closest infrastructure to people’s everyday, there is an exciting medium to be employed to draw innovations through people’s everyday.