Abstract: Artificial intelligence (AI) provides many opportunities to improve private and public life. Discovering patterns and structures in large troves of data is a core component of data science, driving applications in areas such as computational biology, law, and finance. However, such a highly positive impact is coupled with significant challenges. For tractable pricing of complex financial products, segregation of dubious activities in telecommunications networks, or determining the sanctioning of potentially dangerous criminal acts, the decisions suggested by these systems should be fully understood so that they can be trusted. The quest for interpretable, accountable, explainable, and responsible AI may thus be viewed as a fundamental scientific problem in the understanding of complex systems. A closely connected question would be how to hold such immense responsibilities accountable. Issues of social acceptance, ethical regulations, liability, and law enforcement concerning the behavior of these systems are being addressed by legislators and policymakers, highlighting a need for academic research in this area as well.

Keywords: Big Data, Actionable Insights, Artificial Intelligence (AI), Data Interpretation, Machine Learning, Data Analytics, Predictive Analytics, Data Processing, Data Visualization, AI Algorithms, Data Science, Business Intelligence, Data Mining, Real-time Analytics, Deep Learning, Statistical Analysis, Data Integration, Data-driven Decision Making, Automated Insights, Cognitive Computing.

| DOI: 10.17148/IARJSET.2024.11831