Computational Schema as a Facilitator for Crowdsourcing in a “Social-Motive” Model of Design - Principia Designae: Pre-Design, Design, and Post-Design - page 211

According to L ´ vy, one of the foundational figures in this field, Collective
Intelligence is a “universally distributed intelligence” and as such promotes the
“universality of intelligence” (L ´ vy 1997 ). According to L ´ vy, collective intelli-
gence can be characterized by three concepts:
1. Universal distribution of intelligence
2. Constant enhancement
3. Coordination in real-time and the mobilization of skill.
The phenomenon of the “wisdom of the crowd” (Surowiecki 2004 ), is supported
by web-based technologies and interactive communications media. In parallel to
the development of web communication, the model of the crowd represents an
efficient model for use in decentralized models and decentralized participation.
Crowdsourcing (Surowiecki 2004 ) is an emerging concept demonstrating the
breaking of traditional centralized models of collaboration. The difference between
crowdsourcing and the traditional outsourcing is that issues that need to be solved
can be open and distributed to a body of unknown potential contributors rather than
specific recognized collaborators.
Crowdsourcing is now becoming an accepted model for “online, distributed
problem-solving and production” (Brabham 2008 ) . The model has potential for
solving issues in different fields exploiting a massive crowd of online users in fields
like art, music and photography and has been recently presented and discussed in
the context of design (Oxman and Gu 2012 ; Oxman and Oxman 2014 ).
14.2.2 From Collaborative Design to Crowdsourcing Design
Collaborative design is relatively well understood and has been theoretically
formulated in design research. Collaborative design implies well-organized team-
work and negotiation. Design collaboration depends on designers within the disci-
pline as well as design experts across the discipline. Teamwork and negotiation
processes are based on shared domain knowledge and disciplinary expertise.
However beyond the traditional conditions of collaboration, the emerging com-
plexity of global projects; the need for new models of global practices; and the
influence of a global economy have created demands to find solutions for extended
needs, changing scales, and new modes of design (Lahti et al. 2004 ).
While decision-making and collaborative problem solving process in
crowdsourcing can be guided by statistical results, design as a cognitive activity
is characterized by the uniqueness of its thinking processes (Cross 2011 ). Further-
more, in contradiction to the statistical or optimal outcome that can be associated
with the non-hierarchical collective social intelligence of crowds, design is a task
domain that focuses on unique and specific representational codes and operative
skills. As such, collective intelligence in design must address specific knowledge
and skill-media that are based on accepted representational codes, methods and
processes as well as upon unique bodies of disciplinary knowledge.