Artificial intelligence (AI) is becoming increasingly more popular and can be found in workplaces and homes around the world . Regulation changes such as the GDPR mean that users have aright to understand how their data has been processed and saved . TrustyAI is a new initiative which looks into explainable artificial intelligence (XAI) solutions to addresstrustworthiness in ML as well as decision services landscapes . We investigate techniques such as LIME, SHAPand counterfactuals, benchmarking both LIME and Counterfactual techniques against existing implementations . We also look into an extended version of SHAP, which supports background data selection to be evaluated based on data and allows for error bounds. We also examine an extension ofSHAP, a version of the SHAP which supports Background Data Selection to be

Author(s) : Rob Geada, Tommaso Teofili, Rui Vieira, Rebecca Whitworth, Daniele Zonca

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Keywords : data - lime - selection - artificial - trustyai -

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