English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

There has been much discussion of the right to explanation in the EU GeneralData Protection Regulation, and its existence, merits, and disadvantages.Implementing a right to explanation that opens the black box of algorithmicdecision-making faces major legal and technical barriers. Explaining thefunctionality of complex algorithmic decision-making systems and theirrationale in specific cases is a technically challenging problem. Someexplanations may offer little meaningful information to data subjects, raisingquestions around their value. Explanations of automated decisions need nothinge on the general public understanding how algorithmic systems function.Even though such interpretability is of great importance and should be pursued,explanations can, in principle, be offered without opening the black box.Looking at explanations as a means to help a data subject act rather thanmerely understand, one could gauge the scope and content of explanationsaccording to the specific goal or action they are intended to support. From theperspective of individuals affected by automated decision-making, we proposethree aims for explanations: (1) to inform and help the individual understandwhy a particular decision was reached, (2) to provide grounds to contest thedecision if the outcome is undesired, and (3) to understand what would need tochange in order to receive a desired result in the future, based on the currentdecision-making model. We assess how each of these goals finds support in theGDPR. We suggest data controllers should offer a particular type ofexplanation, unconditional counterfactual explanations, to support these threeaims. These counterfactual explanations describe the smallest change to theworld that can be made to obtain a desirable outcome, or to arrive at theclosest possible world, without needing to explain the internal logic of thesystem.

Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR