Ethical Considerations and Implications of Distributed Intelligence

Abstract

Given the importance of distributed intelligence systems in modern computers, their ethical implications must be examined. The innovative Ethical-Aware Distributed Intelligence Framework (EADI) tackles ethical issues in decentralized decision-making. EADI's robust algorithms protect privacy, advance accountability, and decrease prejudices. Distributed intelligence becomes more accountable and fairer. The revolutionary Privacy-keeping Distributed Learning Algorithm (PPDLA) from EADI protects data inputs and privacy during collaborative training using noise. This method improves privacy over linear regression and support vector machines. The transparent and distributed ledger created by the Decentralized accountability Record Algorithm (DALA) simplifies monitoring and enforcing accountability. EADI beats decision trees and k-nearest neighbors, even with different feedback metrics. The Fairness-Aware Decentralized Decision Algorithm (FADDA) designed by EADI mitigates decision-making shortcomings to provide fair results. EADI surpasses existing techniques in various sectors to create and execute ethical distributed intelligence. This makes intelligent decision-making clearer and more reliable.