South Korea is planning a new city called "New Songdo", 40 miles away from Seoul, which aims to be the largest (and first?) ubiquitous computing urban area. All city services (water, power, telephony, traffic, etc) are planned to be linked to internet.
Since now more than half the world population live in urban areas, it's a good point to start thinking about new notions of being human on a metropolis context. Let's hope it's not just an ostentatious project with fancy propaganda.
Seen at The China Observer.
Fast Company: Cisco's Big Bet on New Songdo.
Promotion Video on youtube: Songdo Vision.
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Philips had developed an amazing wake-up machine that acts directly on one of our self-regulation center of time.
It lights up as the daylight used to do over our face when we lived whithout watches, mobile phones and anoying alarms. Telling our bodies that the time has come, regulating our circadian rhythm as we wake easily and more peacefully. At least that's what they say.
A wonderful example of what can be done in interaction design if you pay close attention to human physiology.
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It's widely accepted that domestic appliances are the kings of everyday misunderstadings. From video recorders to washing machines, they all share a so broad range of diferent controllers that makes semantic hard to reuse.
We all have to learn them one by one, but one it's learnt we are supposed to know how to set the devices. But there is one concern that seems still to be resolved:
How can we remove the gap between selected intensity and time to reach the expected outpout?
Most small and major appliances (specially those related with temperature) run in a nominal power, leaving the control of the result to a matter of duration in time. Some of them express clearly the final state of the expected effect in numeric indicators, such as degrees for a central heating system, and others rely on a continuous scale of simulated power variations like electric cooktops.
Although cuantitative controllers are widely present, why is still so insanely frequent that people keeps misunderstanding these stuff that they use every single day?. Some examples:
Will my air conditioning machine works faster setting a lower temperature?. It won't, because its coefficient of performance is fixed. Will the cooktop heat more at higher values? It will heat water quicker but maximun heating power is limited. In most of them the selected value of intensity means an inverse rate of time pauses between heat activations.
The solution could be to make obvious that they work at a linear rate. A good solution for cooktop could be to avoid relative numeric controllers and to ask always for the desired temperature, showing through process the expected time for reaching the goal. An easy way to accept that intensity means time when power is fixed.
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Technology is full of beautiful unexpected uses. Even the most simple act of use innovation should be take as an inspirational example.
Is it possible to design for unknow needs? Probably not. But you must always keep an eye on what people are doing with your product.
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AGU is a three letters word that stands either for my short-name and for the ARNm triplet that codes Serine, an amino acid presented in all of us.
As you may remember from school, biology is built from tiny parts that just interact between themselves in a mechanical way that leads to bigger, greater and complex things.
The little strands called DNA, replicated almost one hundred trillion times in your body, and which could surround the entire earth (each strand), have written in them each detail of what you see every morning in the mirror.
At some point in the cell's life, those strands start to get transcribed into RNA chains, a middle-man molecule in the process of polypeptides synthesis.
Once a polypeptide strand is completed by hundreds and even thousand amino acids, it starts to fold in unpredictable forms until it shapes the final structure, revealing a protein, the engine of life.
This plethora of magical steps occurs in a deterministic way, several times per minute in every single organism.
Do you recognize this?:
gagtgcttgg gttgtggtga aacattggaa gagagaatgt gaagcagcca ttcttttcct gctccacagg aagccgagct gtctcagaca ctggcatggt gttgggggag ggggttcctt ctctgcaggc ccaggtgacc cagggttgga agtgtctcat gctggatccc cacttttcct cttgcagcag ccagactgcc ...
This is an extract from the DNA which codes the p53 protein, one of the most globally studied molecules involved in cancer development, well known as the star of cancer suppression proteins.
And what about this other piece of code?:
8B542408 83FA0077 06B80000 0000C383 FA027706 B8010000 00C353BB 01000000 B9010000 008D0419 83FA0376 078BD98B C84AEBF1 5BC3
This strange code is all you need to program the fibonacci serial in the low-level machine language. Executable by almost every gadget around you. See what both codes have in common?
Scientists and tech people have worked really hard during last decades building levels of abstraction. Look inside and you will find a large amount of conceptual layers from ones and zeros to the graphical user interface, each one simpler than the previous. All drives in the direction that nobody needs to think on hexadecimal to send a plain email.
Have you ever think about a cell as a machine?. They really behave like it whether they are yeast or pluripotent cells in your bone marrow. In fact, as Drew Endy define them, they act as computational systems. They receive inputs, and behave accordingly as outputs. Cells have measurements tools, priorities to satisfy and self awareness of different kinds.
DNA is a reference of functions for a certain being, as software is for an application.
The only difference between software and life source code is the abstraction layers created that enables us to understand, write and debug what we do in a computer. Fortunately, that complex frontier between life in nature and what can be done in a lab by humans is breaking down throughout international cooperation in biology and health research.
Knowledge repositories about enzyme interactions in pathways, expression rules of genes and protein transcriptions are spreading all over the web in different public databases.
Although work with bulk data in these databases is still a hard task, little pieces of proteins interactions are been described and identified as functions in projects like the "Registry of Standard Biology Parts", initiated by previously cited Drew Endy. Basic biological functions are explained in its website as simple parts that get combined making devices and systems. The result is a hierarchical scheme of complex behaviors.
Craig Venter used to say "Electronic industry is based upon 12 fundamental components. Up to now, 20 million genes had been identified."
The faculty for using these genes as pieces of code in engineered organisms have an unprecedented potential in creating new things.
OK, but what does all this have in common with interaction design?. As defined in wikipedia, "Interaction Design is the discipline of defining the behavior of products and systems that a user can interact with."
As you can find in some related lectures, biology must be understood as a technology. A technology for creating complex things with complex implications.
As designers, we are used to deal with problem solving tasks, requirements, and constraints. Biotechnology industry is developing extremely fast, enabling a myriad of applications for new products and services based on biology.
Many authors describe the necessity of compartmentalize competences in biotechnology. Specialization brings better quality in every decision step. From laboratory operators to the function of a biological engineer as a technical architect, someone has to deal with the human side of the final product.
As interaction designers we can apply all the inherited knowledge in our discipline to new horizons like biotech. It's just a new framework with new variables.
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-Jerry, how does this work?
-I refuse to work on the problem.
-What???
-I refuse to work on the problem of figuring out how this work. Because it wasn't designed for, to be easy for me to figured out how it works.
O dicho de otro modo:
Biology itself it's not optimized by nature to be easy to model. Because nature doesn't care about that.
Drew Endy hablando sobre problemas computacionales evolutivos y biología. Una pista sobre el tema de mi charla en la desconferencia de este sábado.
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A properly designed problem is partially solved.
John Dewey.
Esta cita de Dewey me hizo pensar en Planetaki hace un par de días. La encontré leyendo el último libro de Berkun sobre innovación. En una parte del mismo, transmite el beneficio de definir correctamente las necesidades de cualquier proyecto para llevarlo a buen puerto y si es posible, restringir con decisión las posibilidades para encontrar soluciones interesantes.
Javier Cañada mostró desde el principio que tenía muy claro a qué puerto quería llegar. Y llevar la nave hasta allí no era nada fácil, porque crear un lector de feeds para gente que no sabe lo que es un feed es casi como crear una rueda sin eje de giro.
Planetaki combate las dificultades de comunicación del concepto, con una interfaz de obviedad aplastante. Es intuitiva, sencilla y bonita. Un duro ejercicio para eliminar todo lo superfluo o lateral.
Por mi parte hago un uso algo especial del servicio. Si Google Reader es mi mochila, Planetaki es mi bolsillo. Es ahí donde tengo todos los high priority feeds. Fuentes cuya actualización comprobaba antes varias veces al día, abriendo y cerrando carpetas, ahora las reviso de una manera mucho más cómoda.
Larga vida a Planetaki.
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