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HSS8121: 3 – Making in Public: Practices in Creative Research and Maker Culture


In this session we will:

  • Examine the meaning of maker culture or maker movement
  • Look at some of the practices regarding making in the public influenced by research
  • Discuss our perspective on public making as creative makers


Link from previous sessions


What have you seen up until now in this module?

  • Theoretical approaches to the public – foundation
  • From art in the public realm to the civic agency in hybrid spaces

Lessons learnt up to now? How do you apply them in your practice and behaviour?

This is what today’s lecture is going to focus on. Focusing on the makers’ culture and creative research practices and behaviour.

Creative Research Practices

Helen Kara (2015) classifies creative research methods into four key areas:

1. Arts-based research

  • Draw on forms of creative writing and/or the visual arts (drawing, painting, collage, photography etc) or infused with more artistic angle they incorporate music, drama, textile arts (i.e. sculptures).
  • However, the product/artwork is not necessarily experienced in the same way by everyone, leading to multiple perspectives for an item. This comes in contrast with traditional research views where an object can have a single meaning.

2. Research using technology

  • Examples include research through social media, through the use of mobile devices, apps.
  • ‘Technology itself has an influence on people’s creativity, yet the role of technology in the creative process has not yet been fully understood or theorised’. This may neglect what some disciplines say about how new technologies relate to innovative socio-cultural practices with direct implications for research methods.
  • Some fear that technology will change their research practice, and it will, though this seems not a cause for fear, but for care and thought on how to direct the change.

3. Mixed-methods research

  • Mixed methods are perhaps the most well-established approach.
  • But the potential – and the risks – of mixing methods are still not understood by most researchers. People often think in terms of gathering data using both quantitative and qualitative methods, but there is so much more scope for mixing, from using different theoretical perspectives to inform the same piece of research to multi-media presentation and dissemination.

4. Transformative research frameworks (such as participatory, decolonising, or community-based methods)

  • These are frameworks designed to reduce power imbalances within the research process and, ideally, to affect structural inequalities more widely.
  • They are challenging to implement, requiring more time and other resources than more traditional frameworks for research, but when used well they can indeed transform aspects of our society for the better.


  • H. Kara, Creative Research Methods in the Social Sciences: A Practical Guide, 2015]

“Creative is not directly synonymous with ‘innovative'”.

Maker Culture or Movement

So what do we define as maker culture? What is new?

Maker culture focuses on using and learning practical skills and then applying them creatively to different situations. Maker culture draws upon a more participatory approach than traditional learning, encouraging learners to collaboratively engage with others as they learn through the creation of new items (Sharples et al., 2013). Maker culture draws upon a social constructivist perspective which emphasises the social, cultural, and historical factors of experiences (Vygotsky, 1979) as well as a constructionist view on learning (Papert, 1993), which examines the tangible items that are created through learners working within their environments.

People of the maker era are a diverse group including those using 3D printers to create toys, instruments, and weapons; those who experiment with the modification of household items such as retrofitting these items with sensors and Internet connectivity; and those who craft one-of-a-kind designs, such as clothing or furniture, for production on demand (Morozov, 2014)

Maker Culture

The maker culture is a contemporary culture or subculture representing a technology-based extension of DIY culture that intersects with hacker culture(which is less concerned with physical objects as it focuses on software) and revels in the creation of new devices as well as tinkering with existing ones.

Maker Movement

The maker movement is a trend in which individuals or groups of individuals create and market products that are recreated and assembled using unused, discarded or broken electronic, plastic, silicon or virtually any raw material and/or product from a computer-related device.

Even President Obama alluded to the Maker Movement in a speech at the National Sciences Academy’s Annual meeting in 2009 when he remarked:

I want us all to think about new and creative ways to engage young people in science and engineering, whether it’s science festivals, robotics competitions, fairs that encourage young people to create and build and invent – to be makers of things, not just consumers of things.


Maker Education

“Maker education is a new education model which integrates information technologies, adheres to the education ideas of open innovation and exploration experience, uses creation-based learning as the main learning style, and finally focuses on cultivating more innovative talents.” (Xianmin & Jihong, 2015)

Two of the core concepts underlying maker education are learning by doing and constructionism.

“However, maker could be a deformed technology culture for excessive emphasis on the value of products and ignoring the existence value of non-makers.” (Xianmin & Jihong, 2015)

Empowerment, Participation and Democracy

Making has transformed from a fringe and hobbyist practice into a professionalizing field and an emerging industry. Enthusiasts laud its potential to democratize technology, improve the workforce, empower consumers, encourage citizen science, and contribute to the global economy. DIY making is often described as open to anyone, a practice that broadens participation by empowering everyone: makers and users, rich and poor, men and women, young and old. Advocates of DIY promise to turn passive consumers into active participants in state affairs and the market economy as well as revamp a broken educational system through hands-on learning. [Ames et al., 2014]

Currently “empowerment” is the term favoured to convey the idea of people becoming the agents of their own development. Normatively, saying that people have been “empowered” means that they have become better able to shape their own lives, which is a goal that everyone has reason to value. From a more empirical perspective, “empowerment” means gaining a number of factors that make this goal achievable. [Drydyk, 2010]

Another virtue of participation is that it can make a development process more democratic. More precisely, some participatory practices make development decision-making function more democratically. [Drydyk, 2010]

“The quality of participation, depends on its initial entry point” (Goulet 1995, 95).

Communities of Practices, Communities of Interest, Participatory Design, Capacity Development etc.: First stage of these approaches is a needs assessment, identifying stakeholder – not only those whose needs or practices are at the centre of the design, but also potential external stakeholders who could be affected by the aims of the project. So in this manner, you create a consultative forum, where all stakeholders are represented, to contribute to verifying the needs of the project and setting objectives.

The case of Young Company (@ Northern Stage).


Student-Led Seminar (17/04/2018)

Suggested Reading Material:

15 min presentations:

  • Pete – How are maker projects and makers legitimated? Who gets to make these decisions?
  • Nick (Ning An) – In which ways does DIY making extend existing systems of power and divisions of labor?
  • Katharine – What are the possible synergies between critical making, critical technical practice and commercial explorations in making cultures?
  • Benazir – Who is drawn into the making movement, who is excluded or stays away, and why?

DMS8013: Algorithms & Gererativity


  • To learn about the history of algorithms and generative computer code
  • To think about the ways that computers ‘model life’ or otherwise connect to the physical world
  • To experience creating generative systems

Algorithm: “a description of the method by which a task is to be accomplished,”

How do you perceive the meaning of an algorithm?

History in Computer Science (and previously in mathematics)

From writing about recipes in cooking and rituals to the Turing Machine (1936) to Dijkstra’s algorithm.

In art/music/education Shintaro Miyazaki & Michael Chinen, Algorithmic Sorting

Formalism vs Action

The algorithm “is the unifying concept for all the activities which computer scientists engage in.” Provisionally a “de- scription of the method by which a task is to be accomplished,” the algorithm is thus the fundamental entity with which computer scientists operate.[…] But the algorithm is not simply the theoretical entity studied by computer scientists. Algorithms have a real existence embodied in the class libraries of programming languages, in the software used to render web pages in a browser (indeed, in the code used to render a browser itself on a screen), in the sorting of entries in a spreadsheet and so on.

Fuller, M. (2008). Software Studies: A Lexicon. Leonardo Books, MIT Press. p17

So (what I’ll call) the mode of material expression is vital, powerful etc.

A conception of the algorithm as a statement as Michel Foucault used the term might allow us to understand this approach a little better. For Foucault, the statement is not analytically reducible to the syntactic or semantic features of a language; it refers instead to its historical existence and the way that this historical existence accomplishes particular actions. […] As Foucault puts it in The Archaeology of Knowledge, “to speak is to do some- thing—something other than to express what one thinks, to translate what one knows, and something other than to play with the structure of language.

Fuller, M. (2008). Software Studies: A Lexicon. Leonardo Books, MIT Press. p17

Generativity: Modelling life?

In a sense, we can think of the field of cybernetics as an orientation.

Cybernetics: “Our bodies are hardware, our behavior software”

‘In a sense, the original purpose of Cybernetics was to produce a unified theory of the control levels and types of messages used by men and machines and processes in normal operation. Thus the history of computer technology may be interpreted as progress in making communication between men and machines more natural and complete. This remains an ideal definition, however, because quite often in industry human beings have been adapted to inhuman machine schedules, rather than the other way around. What is less realized is that most businesses of any size have had to adapt themselves, more or less traumatically, to radically different patterns of administration and organization as the result of information structures made possible by computer systems. So in part Software addresses itself to the personal and social sensibilities altered by this revolution.’

‘It is now empirically clear that Darwinian evolutionary theory contained a very great error in its identification of the unit of survival under natural selection. The unit which was believed to be crucial and around which the theory was set up was either the breeding individual or the family line or the subspecies or some similar homogeneous set of conspecifics. Now I suggest that the last 100 years have demonstrated empirically that if an organism or aggregate of organisms sets to work with a focus on its own survival and thinks that that is the way to select its adaptive moves, its “progress” ends up with a destroyed environment. […] The flexible environment must also be included along with the flexible organism because, as I have already said, the organism which destroys its environment destroys itself. The unit of survival is a flexible organism-in-its-environment.’ Bateson, Gregory. “Form, substance, and difference.” Essential Readings in Biosemiotics (1970): 501. p508

Swarm Intelligence: Moving as a Hive

Simulating birds and bees in groups, forming them into intelligent systems. The groups are smarter when thinking together. Researchers have explored the collective behaviour of fish, bees, and ants and constructed algorithms to simulate them, constructing smart systems that could provide solutions to problems, forming swarm intelligence. Swarm intelligence is the collective behaviour of decentralized, self-organized systems, natural or artificial. The concept is employed in work on artificial intelligence.


These AI systems have even predicted Oscar nominations!

Generative Code

Meanwhile in computer science bleeding to art practice people became interested in algorithmic modelling, generative processes on both ontological and processual levels.

Such as Conway and the game of life.

‘These artistic systems are not wholly deterministic, running an image through pre-set parameters until it reaches perfection. Indeed, Latham realized early on that the most interesting outcomes of his program were quite unforeseen by him: his evolutionary program could arrive at unexpected conclusions. Even if an artist programs the computer from the start, there will always be an important element of mystery in the working of the software. Such quirks render the computer less mechanistic (and predictable) and more “artistic,” because the outcome of certain operations cannot always be foreseen. is unpredictability can be harnessed in the same way as the chemical reactions of pigments, or the densities of stone. In other words, an artist develops a feel for its working and gradually incorporates its idiosyncrasies into their work, which itself changes subtly or overtly to accommodate these properties.’ Lambert, Nicholas, William Latham, and Frederic Fol Leymarie. “The emergence and growth of evolutionary art: 1980–1993.” ACM SIGGRAPH 2013 Art Gallery. ACM, 2013.
‘For Lev Manovich, contemporary generative art is distinctively concerned with complexity, unlike the paradigm of reduction that characterised abstraction in the visual arts in the first half of the twentieth century.’

‘Software art systems are concrete collections of objects, relations, actions and processes. In part they are formal but constructed ontologies, describing entities and their interrelations. These ontologies are partly metaphorical or figurative—constructing for example «agents» in an «environment.» They are also partly technical / textual, in the sense that the implementation of these figures occurs within the structures of a formal language with particular representational and computational limits. How do we read such systems, critically? They are literally texts, in their source code, but also in a critical sense, in that they involve specific figurations, relations, decisions, values and ideologies.’ Whitelaw, Mitchell. “System stories and model worlds: A critical approach to generative art.” Readme 100 (2005): 135-154.

One example is Generative Composition Engine. The Generative Composition Engine is the culmination of a year-long project in an algorithmic artwork. The application generates unique compositions and plots supplied assets. The settings are derived by the user, compositional rules and a level of chaos to instantaneously create infinite artwork. Every composition has a focal point which affects the scaling of all items on the canvas and several ways of plotting coordinates.



Particle Systems:

Now to design a swarm we need first to create the smallest unit which is a single particle.
What are its characteristics? How do we want it to move?
We will, therefore, create a class that will hold all the information for this particle.
Create the class together…step by step.

Then we want this particle to act in some way. What do we want the particle to do? We add methods for its behaviour within the class.

Sketches here.

Look inside the particles class and decide how you’re going trigger or affect the sound. This should probably be some method (function) of the distance between nearby particles.


Create Langton’s Ant


Or a Turing Machine:

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