Reflective Remediation as Critical Design Strategy: Lessons from László Moholy-Nagy and Olafur Eliasson

Reflective Remediation as Critical Design Strategy: Lessons from László Moholy-Nagy and Olafur Eliasson

Reflective remediation is an important component of contemporary media theory, which emphasises the creative efforts of avant-garde artists and designers to shape the evolution of media in a critical way. However, the critical capacity of reflective remediations may be compromised by commercial dynamics or conventions, such as the celebration of ‘reflec-tivity for reflectivity’s sake’ that aims to construct an auratic experience for viewers. Because reflectivity is a critical media practice, it is vital to investigate reflective remediations in tandem with the critical intensions and creative visions of artists and designers. We investigate the critical media practices of the Bauhaus master, László Moholy-Nagy (1895-1946) who explored the concept of ‘productive creativity’, according to which creative experimentation should lead to design knowledge, redefining the relationship between what is known and unknown. We then scrutinise the artistic practice of the Icelandic-Danish contemporary artist Olafur Eliasson (b.1967), who contextualises reflectivity as an embodied experience , in terms of what he calls ‘frictional encounters’. When applied together, the two concepts enhance our understanding of reflective remediation as a critical design strategy.

https://www.researchgate.net/publication/334122137_Reflective_Remediation_as_Critical_Design_Strategy_Lessons_from_Laszlo_Moholy-Nagy_and_Olafur_Eliasson

Good Design-Driven Innovation

Good Design-Driven Innovation

Radical innovations are designs that alter the meaning of our life experiences. In order to realize such innovation, a designer needs a vision, a strong personal view on the world. The identity and values of designers however, are often denied in modern design processes. Consequently, (junior) designers have difficulties in connecting with their values and standing for their ideals, especially when designing within a corporate setting. We report a case study that demonstrates how nurturing a designer’s personal understanding of ‘good design’ and integration of this understanding in his work, influences a design-driven innovation project and outcome. Our findings suggest that a designer’s principles for good design, enable him to design more in tune with his identity and related ideals. Personal principles for good design empowered the designer’s creativity, decision making, process planning, and drive to design
and promote the acceptance of a radical idea within a corporate setting. We hope to inspire designers to use personal values and identity for design-driven innovation, and would like to start a discussion with design research and education communities to ponder on how designers can be supported in this journey.

http://pure.tudelft.nl/ws/portalfiles/portal/47894840/Baha_et_al_2018_Good_Design_Driven_Innovation.pdf

Windows and Mirrors: Interaction Design, Digital Art, and the Myth of Transparency

Windows and Mirrors: Interaction Design, Digital Art, and the Myth of Transparency (Leonardo): AmazonSmile: Bolter, Jay David, Gromala, Diane, Malina, Roger F., Cubitt, Sean: 9780262524490: Books

https://smile.amazon.co.uk/Windows-Mirrors-Interaction-Transparency-Leonardo/dp/026252449X/ref=sr_1_1?dchild=1&keywords=Windows+and+Mirrors%3A+Interaction+Design%2C+Digital+Art%2C+and+the+Myth+of+Transparency&qid=1609336427&sr=8-1

Linear design processes

Design sprint: map, sketch, decide, prototype, test.

Design thinking: empathise, define, ideate, prototype, test.

Double Diamond: discover, define, develop, deliver.

What’s the difference? Is one better for certain things than another?

I see two problems with these & all models; they are linear, and dumb (fixed, unable to respond to change, & isolated, not connected to other models). We need smart (sensing and responding to change, connected and able to communicate, continuously improving) networked models.

So, there’s a journey from not using any models, using dumb models badly, using dumb models well, and then moving on to using smart models which form an evolving ecosystem of models that better reflects our understanding of reality.

A design process is not an innovation process

Direct – Choose the problem space

Discover – Understand the problem space

Define – Select the problem to solve

Design – Figure out the solution

Develop – Build the solution

Deliver – Get the solution working

Do – Keep using the solution

Design ecosystems for wicked problems