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Algorithms are becoming more widely used in business, and businesses arebecoming increasingly concerned that their algorithms will cause significantreputational or financial damage. We should emphasize that any of these damagesstem from situations in which the United States lacks strict legislativeprohibitions or specified protocols for measuring damages. As a result,governments are enacting legislation and enforcing prohibitions, regulators arefining businesses, and the judiciary is debating whether or not to makeartificially intelligent computer models as the decision-makers in the eyes ofthe law. From autonomous vehicles and banking to medical care, housing, andlegal decisions, there will soon be enormous amounts of algorithms that makedecisions with limited human interference. Governments, businesses, and societywould have an algorithm audit, which would have systematic verification thatalgorithms are lawful, ethical, and secure, similar to financial audits. Amodern market, auditing, and assurance of algorithms developed toprofessionalize and industrialize AI, machine learning, and related algorithms.Stakeholders of this emerging field include policymakers and regulators, alongwith industry experts and entrepreneurs. In addition, we foresee auditthresholds and frameworks providing valuable information to all who areconcerned with governance and standardization. This paper aims to review thecritical areas required for auditing and assurance and spark discussion in thisnovel field of study and practice.

Audit and Assurance of AI Algorithms: A framework to ensure ethical algorithmic practices in Artificial Intelligence