Autonomous Tools in System Design: Reflective Practice in Ubisofts Ghost Recon Wildlands Project

Seidel, Stefan; Berente, Nicholas; Martinez, Benoît; Lindberg, Aron; Lyytinen, Kalle; Nickerson, Jeffrey V.

doi:10.1109/mc.2018.3971341

Cited by 11 publications

(10 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As computing machines moved in the 1960s and 1970s beyond performing simple arithmetic, sorting, and matching carried out by earlier punch-card systems to increasingly complex real time transaction recording where machine exhibit more autonomous and complex agency the shift called also for better learning among system users. In consequence, sociotechnical thinking had to change again (Alvesson and Sandberg, 2011;Ekbia and Nardi, 2014;Kallinikos, 2011;Seidel et al, 2018Seidel et al, , 2019Sutherland, 2008). Several extensions to understand the relationships between machines and people were put forward.…”

Section: The Evolution Of Technology and Organizing Toward Socio-technical Thinking And Metahuman Systemsmentioning

confidence: 99%

Metahuman systems = humans + machines that learn

Lyytinen

Nickerson

King

2020

Journal of Information Technology

Self Cite

View full text Add to dashboard Cite

Metahuman systems are new, emergent, sociotechnical systems where machines that learn join human learning and create original systemic capabilities. Metahuman systems will change many facets of the way we think about organizations and work. They will push information systems research in new directions that may involve a revision of the field’s research goals, methods and theorizing. Information systems researchers can look beyond the capabilities and constraints of human learning toward hybrid human/machine learning systems that exhibit major differences in scale, scope and speed. We review how these changes influence organization design and goals. We identify four organizational level generic functions critical to organize metahuman systems properly: delegating, monitoring, cultivating, and reflecting. We show how each function raises new research questions for the field. We conclude by noting that improved understanding of metahuman systems will primarily come from learning-by-doing as information systems scholars try out new forms of hybrid learning in multiple settings to generate novel, generalizable, impactful designs. Such trials will result in improved understanding of metahuman systems. This need for large-scale experimentation will push many scholars out from their comfort zone, because it calls for the revitalization of action research programs that informed the first wave of socio-technical research at the dawn of automating work systems.

show abstract

Section: The Evolution Of Technology and Organizing Toward Socio-technical Thinking And Metahuman Systemsmentioning

confidence: 99%

Metahuman systems = humans + machines that learn

Lyytinen

Nickerson

King

2020

Journal of Information Technology

Self Cite

View full text Add to dashboard Cite

show abstract

“…Sensors involve the designer's or design team's perception of the output of the autonomous tool. Of note is that while current applications typically involve human designers who work together with tools to create content (Seidel et al, 2018;Smelik et al, 2010a;Summerville et al, 2018) we can also think of nonhuman control systems and even autonomous design tools as control systems. However, as indicated earlier, addressing the frame problem will eventually require a human agent who is able to change the model to react to changes in the problem space.…”

Section: Figure 3 Control System (Partially) Autonomous Design Toolmentioning

confidence: 99%

“…The environment provides sensory inputs to the autonomous design tool. A search-based algorithm might receive a three-dimensional landscape as input and then generate alterations of this landscape until the process terminates with a satisfactory solution (Seidel et al, 2018). Similarly, a machine-learned model might be fed with a partial design and then complete that design (Summerville et al, 2018).…”

Section: Figure 3 Control System (Partially) Autonomous Design Toolmentioning

confidence: 99%

“…Empirical evidence suggests that autonomous design tools are fundamentally changing the organizing of innovative design work and the way that designers 1 will generate artifacts in the future (Seidel et al, 2018;Zhang et al, forthcoming). Instead of creating artifacts by directly manipulating multifaceted design representations, designers will increasingly focus on selecting system goals, features, and constraints, deciding on related design parameters, setting values for these parameters, and evaluating and learning from the analysis of the tool outcomes (Seidel, Berente, Lindberg, et al, 2019;Seidel et al, 2018;Summerville et al, 2018). Design work in such environments requires designers to be mindful of the logic, capabilities, and limitations of the deployed algorithms and to find ways to make sense of and deal with complex and unanticipated outputs.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Artificial Intelligence and Video Game Creation

Seidel¹,

Berente

Lindberg³

et al. 2020

jdsr

Self Cite

View full text Add to dashboard Cite

Autonomous, intelligent tools are reshaping all sorts of work practices, including innovative design work. These tools generate outcomes with little or no user intervention and produce designs of unprecedented complexity and originality, ushering profound changes to how organizations will design and innovate in future. In this paper, we formulate conceptual foundations to analyze the impact of autonomous design tools on design work. We proceed in two steps. First, we conceptualize autonomous design tools as ‘rational’ agents which will participate in the design process. We show that such agency can be realized through two separate approaches of information processing: symbolic and connectionist. Second, we adopt control theory to unpack the relationships between the autonomous design tools, human actors involved in the design, and the environment in which the tools operate. The proposed conceptual framework lays a foundation for studying the new kind of material agency of autonomous design tools in organizational contexts. We illustrate the analytical value of the proposed framework by drawing on two examples from the development of Ubisoft’s Ghost Recon Wildlands video game, which relied on such tools. We conclude this essay by constructing a tentative research agenda for the research into autonomous design tools and design work.

show abstract

“…Software tools using artificial intelligence (AI) methods are now being used within a variety of organizational routines and practices, creating new types of human-machine configurations and playing an increasingly important role in the context of contemporary organizing [4,5]. Examples can be found across areas such as management decision making, manufacturing, and even design and creative applications [e.g., 1, 2].…”

mentioning

confidence: 99%