Listen "S5 Ep38: Director’s Cut: How to make Industry 4.0 work for Europe"
Episode Synopsis
Bruegel director Guntram Wolff talks to Padmashree Gehl Sampath, a Berkman Klein fellow at Harvard University, on the consequences of ‘new manufacturing’ for European industrial policymaking.
In this Director’s Cut of ‘The Sound of Economics’, Bruegel’s Guntram Wolff discusses Industry 4.0 with Harvard University Berkman Klein fellow Padmashree Gehl Sampath.
Europe is yet to truly explore what interventions can and should be made with regard to the digitisation of industrial policy. But the ongoing development of technologies obliges the EU to examine how best to create a level playing-field for companies, and how to ensure that newly compiled sets of data can contribute positively to the welfare of its citizens.
The deployment of Europe’s General Data Protection Regulation brought into focus the potential negative consequences of people’s data being amassed. Yet, as the discussants consider here, there are many potential works to which these data can be put that would serve a greater public good. But this will only follow once policymakers formulate fresh approaches tailored to the challenge, and propose how they will follow through on their aforementioned obligations.
If you would like to on this topic, we recommend our blog post by Silvia Merler on machine learning and economics.
In this Director’s Cut of ‘The Sound of Economics’, Bruegel’s Guntram Wolff discusses Industry 4.0 with Harvard University Berkman Klein fellow Padmashree Gehl Sampath.
Europe is yet to truly explore what interventions can and should be made with regard to the digitisation of industrial policy. But the ongoing development of technologies obliges the EU to examine how best to create a level playing-field for companies, and how to ensure that newly compiled sets of data can contribute positively to the welfare of its citizens.
The deployment of Europe’s General Data Protection Regulation brought into focus the potential negative consequences of people’s data being amassed. Yet, as the discussants consider here, there are many potential works to which these data can be put that would serve a greater public good. But this will only follow once policymakers formulate fresh approaches tailored to the challenge, and propose how they will follow through on their aforementioned obligations.
If you would like to on this topic, we recommend our blog post by Silvia Merler on machine learning and economics.
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