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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Every step we take in the digital world leaves behind a record of ourbehavior; a digital footprint. Research has suggested that algorithms cantranslate these digital footprints into accurate estimates of psychologicalcharacteristics, including personality traits, mental health or intelligence.The mechanisms by which AI generates these insights, however, often remainopaque. In this paper, we show how Explainable AI (XAI) can help domain expertsand data subjects validate, question, and improve models that classifypsychological traits from digital footprints. We elaborate on two popular XAImethods (rule extraction and counterfactual explanations) in the context of BigFive personality predictions (traits and facets) from financial transactionsdata (N = 6,408). First, we demonstrate how global rule extraction sheds lighton the spending patterns identified by the model as most predictive forpersonality, and discuss how these rules can be used to explain, validate, andimprove the model. Second, we implement local rule extraction to show thatindividuals are assigned to personality classes because of their uniquefinancial behavior, and that there exists a positive link between the model'sprediction confidence and the number of features that contributed to theprediction. Our experiments highlight the importance of both global and localXAI methods. By better understanding how predictive models work in general aswell as how they derive an outcome for a particular person, XAI promotesaccountability in a world in which AI impacts the lives of billions of peoplearound the world.

Explainable AI for Psychological Profiling from Digital Footprints: A Case Study of Big Five Personality Predictions from Spending Data