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/

Global: Zendy Plus annual

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

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Moral AI has been studied in the fields of philosophy and artificialintelligence. Although most existing studies are only theoretical, recentdevelopments in AI have made it increasingly necessary to implement AI withmorality. On the other hand, humans are under the moral uncertainty of notknowing what is morally right. In this paper, we implement the MaximizingExpected Choiceworthiness (MEC) algorithm, which aggregates outputs of modelsbased on three normative theories of normative ethics to generate the mostappropriate output. MEC is a method for making appropriate moral judgmentsunder moral uncertainty. Our experimental results suggest that the output ofMEC correlates to some extent with commonsense morality and that MEC canproduce equally or more appropriate output than existing methods.

Towards Theory-based Moral AI: Moral AI with Aggregating Models Based on Normative Ethical Theory