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Exploring value change

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This article aims to explore the use of cross-impact balances (CIB) to identify scenarios of value change. The possibility of value change has received little attention in the literature on value-sensitive design (VSD). Examples of value change include the emergence of new values and changes in the relative importance of values. Value change could lead to a mismatch between values embedded in technology and the way they are currently considered in society. Such a mismatch could result in a lack of acceptability of technologies, increasing social tensions and injustices. However, methods to study value change in the VSD literature are rare. CIB is a scenario tool that can study systems characterized by feedback loops that are hard to describe mathematically. This is often the case when aiming to define values and their relationships. We demonstrate the use of CIB to identify scenarios of value change using two cases: digital voice assistants and gene drive organisms. Our findings show that CIB is helpful in building scenarios of value change, even in instances where the operationalization of values is complex. CIB also helps us to understand the mechanisms of value change and evaluate when such mechanisms occur. Finally, we find that CIB is particularly useful for social learning and explanatory modelling. CIB can therefore contribute to the design of value-sensitive technologies.
Title: Exploring value change
Description:
This article aims to explore the use of cross-impact balances (CIB) to identify scenarios of value change.
The possibility of value change has received little attention in the literature on value-sensitive design (VSD).
Examples of value change include the emergence of new values and changes in the relative importance of values.
Value change could lead to a mismatch between values embedded in technology and the way they are currently considered in society.
Such a mismatch could result in a lack of acceptability of technologies, increasing social tensions and injustices.
However, methods to study value change in the VSD literature are rare.
CIB is a scenario tool that can study systems characterized by feedback loops that are hard to describe mathematically.
This is often the case when aiming to define values and their relationships.
We demonstrate the use of CIB to identify scenarios of value change using two cases: digital voice assistants and gene drive organisms.
Our findings show that CIB is helpful in building scenarios of value change, even in instances where the operationalization of values is complex.
CIB also helps us to understand the mechanisms of value change and evaluate when such mechanisms occur.
Finally, we find that CIB is particularly useful for social learning and explanatory modelling.
CIB can therefore contribute to the design of value-sensitive technologies.

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