Luke Sturgeon

  1. Upcoming workshop at the Science Museum

    Workshops

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    I am very pleased to announce that myself and Shamik Ray will be leading a photographic workshop at the Science Museum, London in a couple of weeks time. The workshop will build on our existing project and is the first time the Android and iOS beta apps will be used by members of the public. The hands-on workshop will allow participants to explore and create photographic data-visualisations using light-painting to discover Electromagnetic Fields around everyday objects.

    The workshop is in close collaboration with the Science Museum and sit’s beautifully alongside their Secret Life of the Home permanent exhibition, and is also part of a series of events created for the amazing Stranger Than Fiction exhibition from Joan Fontcuberta.

    Limited paces are still available at the moment for what should be a really fun day of experimentation and learning.


  2. Making Visible: Mediating the material of emerging technology

    Reading list

    Our best machines are made of sunshine, they are all light and clean because they are nothing but signals, electromagnetic waves, a section of a spectrum, and these machines are eminently portable, mobile. […] The ubiquity an invisibility of cyborgs is precisely why these sunshine-belt machines are so deadly. They are as hard to see politically as materially (Haraway 1991)

    This is the PhD thesis of friend and lecturer Timo Arnall. His primary motivation for this body of work comes from his own personal experience and “the focus on seamlessness has meant that there is little design practise or research that looks into making interface technologies apparent, or into revealing and explaining how they work” (Arnall 2014).

    Immaterials-Wifi-21 RFID-Nearness RFID-Touch-Project

    I enjoyed the text greatly as we seem to share similar concerns and opinions about the speed that a new piece of technology moves from concept, to proof-of-concept to market-ready, with little or no consideration of the social, political and economical consequences. Something that Jacques Ellul describes beautifully in his 1954 book The Technological Society. Although Arnall’s focus is upon the attitudes of designers who conceive and communicate these new technologies.

    (more…)



  3. A tool to optimise our memory of past experiences

    Thoughts

    Abstract

    This paper outlines an approach to the study of self-perception and self-reflection in performance, through a research tool that arose from a collaborative project between the author and a dance artist. Original ideas and questions were used to interrogate our own process and methods during the project, that suggested new tools for design research and approaches to self-reflection. This paper starts by introducing the unique qualities of intimate-performance as a research context and addressing relevant research themes and their relationship to this context. Next it discusses the creative process that was undertaken and how practise-based iterative investigation shaped the project. Finally, it focuses on the toolkit that manifested itself as a way to initiate and capture self-reflection.

    We began to realise that if we wanted to change the situation we first had to change ourselves. And to change ourselves effectively we first had to change our perceptions (Stephen R. Covey, The 7 Habits of Highly Effective People)

    (more…)


  4. Four Futures of Hawaii 2050

    Reading list

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    Originally published in August, 2006 this series of four hypothetical future scenarios for the islands of Hawaii provide a way to discuss the probable futures. By projecting current economic, social, political and technological ideas forward by 44 years (from date of publishing).

    Further reading

    • Julian Simon, The Ultimate Resource 2. Princeton University Press, 1998
    • Jared Diamond, Collapse: How societies choose to fail or succeed. New York: Penguin Books, 2005
    • Dennis Meadows, Jorgen Randers, and Donella Meadows, Limits to growth: The 30 year update. Chelsea Green Publishing, 2004
    • Ray Kurzweil,The singularity is near: When humans transcend biology. New York: Viking, 2005

  5. Reading list

    Reading list

    This is something I’ve been developing for a while now. Time to try and put it all in a single place. Not exactly sure what order it should be in yesterday but this post combines recommendations, references in other texts and relevant across a range of topics that I’m interested and curious about.

    • Julian Simon, The Ultimate Resource 2. Princeton University Press, 1998
    • Jared Diamond, Collapse: How societies choose to fail or succeed. New York: Penguin Books, 2005
    • Dennis Meadows, Jorgen Randers, and Donella Meadows, Limits to growth: The 30 year update. Chelsea Green Publishing, 2004
    • Ray Kurzweil,The singularity is near: When humans transcend biology. New York: Viking, 2005

    Philosophy


  6. How we see machines, seeing the world

    Thoughts

    I was inspired to write this post by a recent article on the BBC Future titled “The odd way robots see the world“. As a way to document and organise my own thoughts. The article describes the difficulties in teaching a machine to really “see” and “understand” the world it exists within.

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    It feels important for us to remember that machines don’t “see” the world in any way that would make sense to a human and vice version. Sure we can use a camera to scan and process our living-room, even map content on to objects and detect different types of objects, to create a more immersive and interactive experience. But they have no cultural, social or individual understanding of the objects and their significance.

    How do they know the difference between the photographs of me, the photograph of a long-lost relative, the limited-edition film poster and the cheap magazine spread stuck on the wall. I imagine that a software engineer is working on such an algorithm right now, if it does not exist already. In theory we could identify the images and use the internet to find possible matches. That could give the machine an indication of the actual content, but how does it know the cheap magazine-spread is actually my favourite and holds sentimental value to me above all other objects? What level of detail and data would the algorithm need to computer such a thing? Would it look at my behaviour and actions over time in regards to all objects in the room? Would it require me input key relationship or rate certain things. The BBC article uses another great example to highlight the complexity of situational awareness that humans are constantly processing.

    Most human drivers would expect that a child might follow it, and slow down accordingly. A robot can too, but distinguishing between a ball and a plastic bag is difficult, even with all of their sensors and algorithms. And that’s before we start thinking about people who might set out to intentionally distract or confuse a robot, tricking it into driving onto the pavement or falling down a staircase. Could a robot recognise a fake road diversion that might be a prelude to a theft or a hijacking? (Swain 2014)

    We forget that a machine doesn’t “see” the world. A machine is a collection of digital input devices that pass data in to an algorithm for processing. The algorithm doesn’t even “see”. It just compares the incoming data to the conditions that have been programmed and takes appropriate action.

    “Acquiring, processing, analyzing, and understanding images and, in general, high-dimensional data from the real world in order to produce numerical or symbolic information, e.g., in the forms of decisions” (Wikipedia 2014).

    Fundamentally every human and machine decision is a giant “if statement” but one could argue that humans are able to prioritise and understand the variables that make up almost all the conditions and outcomes for a decision. The final decision is based on all their previous knowledge up until that point, and their decision as to whether or not the effect of their decision is satisfactory.

    Perhaps that leads to an interesting difference. That machine decision making is based on the processing of current conditions and human decision making is based on the affect of their decision, or at least the effect is factored in as well as current conditions. Now this is in no way conclusive and is written as my personal thoughts, I’m confident there is additional research in to this and entire projects aimed at improving machine decision making in this way.

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    My point perhaps, is that even the programmer responsible for the decision making algorithm doesn’t “know” how the machine see’s the world. They must assume, and build extremely accurate and complex data visualisations to process the data. That visualisation is an interpretation of the raw data which must then be interpreted again by the programmer to assess whether or not all criteria is being met and the algorithm has enough data to accurately make its decision.

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    Screenshot of custom software to visualise the computer-vision data for a public installation.

    I have great personal interest in the tools we build to see our world through the eyes of a machine. Or more accurately the tools we build to visualise the the way in which we think the machine “should” be seeing the world. These are tools that we’ve designed to help communicate to ourselves and others how an algorithm is processing real-world data.

    Will we ever get a machine to change it’s behaviour based on human emotions? Do we need to change our behaviour to suit machine requirements? You could argue that we are already do the latter. A tweet is 140 characters, there are many other ways to communicate with people, but millions of people have adapted to producing a series of short messages that neatly sum up their current thought or opinion.



  7. UX keywords and processes

    Thoughts

    A good friend of mine and extremely talented designer asked me many times “why do you think that if you follow the same process, you will always end up with the best solution? This is Design, not Science! It takes intuition and decision making along the way!”

    I spent a long time assuming if I followed the correct path I will always end up at a design solution. But somewhere along that path is interpretation, intuition and creativity. I still need to ‘design’ the thing. Sometimes the answer is staring you in the face and you think “really, I can’t be the only one that see’s this”, whilst other times you could spend many frustrating days waiting for the elements to align themselves and for you to suddenly reach creative enlightenment. “You’re a designer, so you still need to ‘design’ something” my friend would remind me occasionally!

    Since then I’ve taken on many more projects and pushed myself to explore several approaches to work; artistically-experimental, research-driven, practical, and more traditional design processes. User-experience (UX) is a design discipline that’s proud to have a set of keywords, processes and guiding principles. I’ve tried to document them below in the order in which they would usually be tackled.

    User research

    You cannot design anything until you know who you’re designing for. Although this isn’t a UX or IxD principal – I was taught this in my introduction to graphic design – this is just how you design something. Every piece of design communicates something, you need to deliver the message in the most effective way for the group of people you are focused on, as well as being mindful of miscommunication and misinterpretation from the focus group and other groups.

    Personas

    A fictional person who is created to represent the needs, goals, objectives and motivations for a similar section of users. When certain types of users have clearly different or competing needs additional personas are created to capture the different user types.

    Scenarios

    Short stories that describe with a high-level of detail how a user will interact with the product you’re designing. They describe the goals and objectives of the user in a more personal and human way including context.

    User Journeys

    Step-by-step flow of common journeys to understand different steps the user needs to complete before reaching their goal. These can be thought of as a simplification of scenarios, removing some context and focus on the expectations the user has from the product.

    User flows

    High-level diagrams that show all potential scenarios for an entire end-to-end journey. The flow makes it easier to identify all the various pages and loopbacks within a digital product.

    Red routes

    User to identify the crucial journeys that a user will undertake to complete common tasks. Helps increase focus on common scenarios to ensure we’re always creating the best possible experience.

    User stories

    Help to elaborate on red routes, by providing the context for specific user behaviours using a traditional template: “As a <role>, I want <goal/desire> so that <benefit>”. For example, “As a non-administrative user, I want to modify my own schedules but not the schedules of other users.

    Wireframes

    In the case of a digital product these are neatly organised boxes that represent content, features and navigation for a particular view. Each wireframe would represent a required view that can be understood from the user flows.

    Prototypes

    Now take something that’s static and allow someone to click through it. HTML websites have been doing this for a while-now, so that can be a fairly good starting point! More and more shiny tools are becoming available, mostly doing the same thing in a different way. The idea is to simulate the final experience of the product, click a button and go to the next step in that flow.


  8. Difficult Forms: Critical Practices of Design and Research

    Reading list

    This research paper was written by Ramia Mazé and Johan Redström at the Interactive Institute. They introduce the text as a way to “discuss conceptual and critical design, suggesting that they constitute a kind of critical practice in design. Tracing a historical background and contemporary tendencies, we consider implications for design research”.

    If there is no extension beyond commentary or critique, conceptual and critical design might tend toward the self-reflexive and genetic autonomy – design for designers.

    Discussion around a “critical practise” not just academic or conceptual but a design research practise that functions.

    Engagement with the conceptual realm of design and thereby, potentially also contributing to the development – through critique and counterproposals – of theoretical frameworks proper to design.

    When someone reflects-in-action, he becomes a researcher in the practice context
    — Donald schön, 1983


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