Why is it important to understand the relationship between #AI and #GDPR? #iaandgdpr post series
Contrary to traditional #personaldata processing, AI features challenge GDPR provisions
Distinctive aspects of big data analytics
1) use of algorithms. The analysis of a dataset involves a ‘discovery phase’: running algorithms against the data to find correlations. Once they are identified, a new algorithm can be created and applied to particular cases in the ‘application phase’.
2) opacity of the processing: the processing involves feeding vast quantities of data in non-linear neural networks that classify the data based on the outputs from each successive layer
3) tendency to collect ‘all the data’. BD analytics leverage from collecting and using all the available data
4) repurposing of data: using data for a purpose different from that for which it was originally collected
5) use of new types of data:
– provided: data consciously given by DS (filling a form)
– observed: data recorded automatically (online cookies)
– derived: data produced from other data in a relatively simple way (customer profitability from purchases)
– inferred: data produced by using more complex analytics to find correlations bt datasets to profile DS (calculating credit scores)
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