Artificial Intelligence (AI) is a transformative technology that brings forth a diapason of advantages and challenges. On the positive side, AI offers unknown effectiveness, allowing tasks to be performed briskly and more directly than mortal capabilities. robotization, a crucial point of AI, reduces the burden of repetitious and mundane tasks, enabling mortal coffers to concentrate on further creative and strategic trials. AI excels at data analysis, recycling vast datasets to prize precious perceptivity, serving fields from healthcare to finance. also, AI operates lifelessly,24/7, without succumbing to fatigue.   Again, AI has its downsides. robotization’s effectiveness can lead to job relegation, particularly in diligence where mortal labor is substituted by machines. Bias and fairness enterprises arise as AI systems learn from poisoned literal data, potentially immortalizing societal inequalities. sequestration becomes a concern with the eventuality for invasive surveillance and data abuse. Ethical dilemmas crop when AI is assigned with making life- or- death opinions in independent vehicles and healthcare. Security pitfalls are current, as AI can be exploited for cyberattacks and the creation of satisfying deepfake.


The past 20 years have seen a dramatic shift in educational policy toward a concentration on socio-emotional competencies and other 21st century abilities. Technological progress, machine learning, and AI ethics provide the background for this article's discussion of 21st-century soft skills, which include social and emotional intelligence. The paper defines these skills as non-epistemic competence components. However, there are significant societal issues that may arise from using data-driven AI technologies to model and quantify them. These challenges will have enormous ramifications for educational policies and practices. We recommend waiting to incorporate data on these skill components into machine learning systems until we have a clearer grasp of the societal impact.