Lehrveranstaltung Digitalisierung der Arbeitswelt (Seminar)

Blockveranstaltung:

Data is among the most important resources for enterprises in the contemporary economy. But to use data for economic purposes, for instance in highly-automated artificial intelligence systems, a substantial amount of human work is needed. In this seminar, we track the varied work activities along the so-called data value chain – from to the acquisition of data to analysis, curation, storage and usage. At each step, we will ask about the characteristics and location of workplaces and how these are linked to the global data economy. The understanding about the immaterial backbone of value creation, provides tools for the analysis hierarchies, power relations and inequality in contemporary societies.

Key literature

Cobbe, J., Veale, M., & Singh, J. (2023). Understanding accountability in algorithmic supply chains. 2023 ACM Conference on Fairness, Accountability, and Transparency, 1186–1197. https://doi.org/10.1145/3593013.3594073

Curry, E. (2015). The Big Data Value Chain: Definitions, Concepts, and Theoretical Approaches. In J. M. Cavanillas, W. Wahlster, & E. Curry (Hrsg.), New Horizons for a Data-Driven Economy. A Roadmap for Usage and Exploitation of Big Data in Europe (S. 30–36). Springer.

Posada, J., Newlands, G. & Miceli, M. (2023) Labor, Automation, and Human–Machine Communication. The SAGE Handbook of Human–Machine Communication, Guzman, A.L., McEwen, R. & Jones, S., 384–391. London: SAGE.

Blockveranstaltung:

Data is among the most important resources for enterprises in the contemporary economy. But to use data for economic purposes, for instance in highly-automated artificial intelligence systems, a substantial amount of human work is needed. In this seminar, we track the varied work activities along the so-called data value chain – from to the acquisition of data to analysis, curation, storage and usage. At each step, we will ask about the characteristics and location of workplaces and how these are linked to the global data economy. The understanding about the immaterial backbone of value creation, provides tools for the analysis hierarchies, power relations and inequality in contemporary societies.

Key literature

Cobbe, J., Veale, M., & Singh, J. (2023). Understanding accountability in algorithmic supply chains. 2023 ACM Conference on Fairness, Accountability, and Transparency, 1186–1197. https://doi.org/10.1145/3593013.3594073

Curry, E. (2015). The Big Data Value Chain: Definitions, Concepts, and Theoretical Approaches. In J. M. Cavanillas, W. Wahlster, & E. Curry (Hrsg.), New Horizons for a Data-Driven Economy. A Roadmap for Usage and Exploitation of Big Data in Europe (S. 30–36). Springer.

Posada, J., Newlands, G. & Miceli, M. (2023) Labor, Automation, and Human–Machine Communication. The SAGE Handbook of Human–Machine Communication, Guzman, A.L., McEwen, R. & Jones, S., 384–391. London: SAGE.

Blockveranstaltung:

Data is among the most important resources for enterprises in the contemporary economy. But to use data for economic purposes, for instance in highly-automated artificial intelligence systems, a substantial amount of human work is needed. In this seminar, we track the varied work activities along the so-called data value chain – from to the acquisition of data to analysis, curation, storage and usage. At each step, we will ask about the characteristics and location of workplaces and how these are linked to the global data economy. The understanding about the immaterial backbone of value creation, provides tools for the analysis hierarchies, power relations and inequality in contemporary societies.

Key literature

Cobbe, J., Veale, M., & Singh, J. (2023). Understanding accountability in algorithmic supply chains. 2023 ACM Conference on Fairness, Accountability, and Transparency, 1186–1197. https://doi.org/10.1145/3593013.3594073

Curry, E. (2015). The Big Data Value Chain: Definitions, Concepts, and Theoretical Approaches. In J. M. Cavanillas, W. Wahlster, & E. Curry (Hrsg.), New Horizons for a Data-Driven Economy. A Roadmap for Usage and Exploitation of Big Data in Europe (S. 30–36). Springer.

Posada, J., Newlands, G. & Miceli, M. (2023) Labor, Automation, and Human–Machine Communication. The SAGE Handbook of Human–Machine Communication, Guzman, A.L., McEwen, R. & Jones, S., 384–391. London: SAGE.