The Power of Maybes Machines, Uncertainty and Design Futures |
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| Author:
| Marenko, Betti |
| Series edited by:
| Dilnot, Clive
Staszowski, Eduardo
Tassinari, Virginia |
| Series title: | Beyond the Modern Ser. |
| ISBN: | 978-1-350-37727-1 |
| Publication Date: | Jun 2025 |
| Publisher: | Bloomsbury Academic & Professional
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| Book Format: | Hardback |
| List Price: | USD $115.00 |
Book Description:
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In the 21st century, decision-making processes are increasingly being transferred from humans to machines. Algorithms and prediction capture and shape our choices about how we live and interact with others before we can register their mechanisms of reaching outcomes. The time that we would allocate to critical thinking, reflecting and assessing, evaporates. Through an examination of the work that predictive machines do when making decisions and their impact on human capacities, this...
More Description
In the 21st century, decision-making processes are increasingly being transferred from humans to machines. Algorithms and prediction capture and shape our choices about how we live and interact with others before we can register their mechanisms of reaching outcomes. The time that we would allocate to critical thinking, reflecting and assessing, evaporates. Through an examination of the work that predictive machines do when making decisions and their impact on human capacities, this cutting-edge study looks to 'uncertainty' as a central, epistemic tool for reimagining human-machine encounters. It focuses on the space of 'maybes', before prediction, as an area for critical inquiry and cultivation.
Through a transdisciplinary approach that brings together design studies and philosophies of processes and technology, Betti Marenko explores how the area of uncertainty can be mapped, diagrammed and designed. By framing uncertainty as a design material, she demonstrates how it can be mobilized to create new modes of knowledge production.
This book sheds light on how current computational processes can deepen contested classifications, inequalities and hierarchies, and offers alternative anticipatory design methods and stratagems based on uncertainty that can be used to avoid reduction and algorithmic capture. It offers a framework for harnessing the power of 'maybes' through design and contributes to contemporary debates around the growing intelligence and autonomy of machines. It is a timely intervention on how to reinvent critique in the algorithmic age by designing new modes of living attuned not to what is, but to what may be.