TY - GEN
T1 - Explainable AI (XAI)
T2 - 10th IEEE Open Conference of Electrical, Electronic and Information Sciences, eStream 2023
AU - Reddy, G. Pradeep
AU - Kumar, Y. V.Pavan
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Artificial intelligence (AI) has become an integral part of our lives; from the recommendations we receive on social media to the diagnoses made by medical professionals. However, as AI continues to grow more complex, the 'black box' nature of many AI models has become a cause for concern. The main objective of Explainable AI (XAI) research is to produce AI models that are easily interpretable and understandable by humans. In this view, this paper presents an overview of XAI and its techniques for creating interpretable models, specifically focusing on Local Interpretable Model-Agnostic Explanations (LIME) and SHapley Additive exPlanations (SHAP). Furthermore, this paper delves into the various applications of XAI in different domains, including healthcare, finance, and law. Additionally, the ethical and legal implications of using XAI are mentioned. Finally, the paper discusses various challenges and future research directions of XAI.
AB - Artificial intelligence (AI) has become an integral part of our lives; from the recommendations we receive on social media to the diagnoses made by medical professionals. However, as AI continues to grow more complex, the 'black box' nature of many AI models has become a cause for concern. The main objective of Explainable AI (XAI) research is to produce AI models that are easily interpretable and understandable by humans. In this view, this paper presents an overview of XAI and its techniques for creating interpretable models, specifically focusing on Local Interpretable Model-Agnostic Explanations (LIME) and SHapley Additive exPlanations (SHAP). Furthermore, this paper delves into the various applications of XAI in different domains, including healthcare, finance, and law. Additionally, the ethical and legal implications of using XAI are mentioned. Finally, the paper discusses various challenges and future research directions of XAI.
UR - https://www.scopus.com/pages/publications/85162028046
UR - https://www.scopus.com/pages/publications/85162028046#tab=citedBy
U2 - 10.1109/eStream59056.2023.10134984
DO - 10.1109/eStream59056.2023.10134984
M3 - Conference contribution
AN - SCOPUS:85162028046
T3 - 2023 IEEE Open Conference of Electrical, Electronic and Information Sciences, eStream 2023 - Proceedings
BT - 2023 IEEE Open Conference of Electrical, Electronic and Information Sciences, eStream 2023 - Proceedings
A2 - Navakauskas, Dalius
A2 - Paulikas, Sarunas
A2 - Sledevic, Tomyslav
A2 - Udris, Dainius
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 27 April 2023
ER -