Virtual worlds are multi-faceted technologies. Facets of virtual worlds include graphical simulation tools, communication, design and modelling tools, artificial intelligence, network structure, persistent object-oriented infrastructure, economy, governance and user presence and interaction. Recent studies (Merrick et al., 2010) and applications (Rosenman et al., 2006, Maher et al., 2006) have shown that the combination of design, modelling and communication tools, and artificial intelligence in virtual worlds makes them suitable platforms for supporting collaborative design, including human-human collaboration and human-computer co-creativity. Virtual worlds are also coming to be recognised as a platform for collective intelligence (Levy, 1997), a form of group intelligence that emerges from collaboration and competition among large numbers of individuals. Because of the close relationship between design, communication and virtual world technologies, there appears a strong possibility of using virtual worlds to harness collective intelligence for supporting upcoming design challenges on a much larger scale as we become an increasingly global and technological society (Maher et al, 2010), beyond the current support for small-scale collaborative design teams. Collaborative design is relatively well studied and is characterised by small-scale, carefully structured design teams, usually comprising design professionals with a good understanding of the design task at hand. All team members are generally motivated and have the skills required to structure the shared solution space and to complete the design task. In contrast, collective design (Maher et al, 2010) is characterised by a very large number of participants ranging from professional designers to design novices, who may need to be motivated to participate, whose contributions may not be directly utilised for design purposes, and who may need to learn some or all of the skills required to complete the task. Thus the facets of virtual worlds required to support collective design differ from those required to support collaborative design. Specifically, in addition to design, communication and artificial intelligence tools, various interpretive, mapping and educational tools together with appropriate motivational and reward systems may be required to inform, teach and motivate virtual world users to contribute and direct their inputs to desired design purposes. Many of these world facets are well understood by computer game developers, as level systems, quests or plot and achievement/reward systems. This suggests the possibility of drawing on or adapting computer gaming technologies as a basis for harnessing collective intelligence in design. Existing virtual worlds that permit open-ended design  such as Second Life and There are not specifically game worlds as they do not have extensive level, quest and reward systems in the same way as game worlds like World of Warcraft or Ultima Online. As such, while Second Life and There demonstrate emergent design, they do not have the game-specific facets that focus users towards solving specific problems required for harnessing collective intelligence. However, a new massively multiplayer virtual world is soon to be released that combines open-ended design tools with levels, quests and achievement systems. This world is called Lego Universe (www.legouniverse.com). This paper presents technology spaces for the facets of virtual worlds that can contribute to the support of collective intelligence in design, including design and modelling tools, communication tools, artificial intelligence, level system, motivation, governance and other related facets. We discuss how these facets support the design, communication, motivational and educational requirements of collective intelligence applications. The paper concludes with a case study of Lego Universe, with reference to the technology spaces defined above. We evaluate the potential of this or similar tools to move design beyond the individual and small-scale design teams to harness large-scale collective intelligence. We also consider the types of design tasks that might best be addressed in this manner.