AI

Artificial intelligence (AI) refers to the development of computer systems that can perform tasks that ordinarily require human intelligence. Core capabilities include perception, reasoning, learning, planning, and problem solving. AI encompasses narrow or weak AI, designed to excel at a specific task, and more speculative general AI, intended to match or surpass human intelligence across a broad range of activities.

Approaches to AI are broadly divided into symbolic and data-driven methods. Early AI emphasized hand-crafted rules and logic, while contemporary AI relies largely on machine learning, especially deep learning, where systems learn from large datasets. Subfields include machine learning, natural language processing, computer vision, robotics, planning, and knowledge representation. Reinforcement learning adds decision-making through trial and error.

AI has become integrated into many domains, including search, speech and image recognition, translation, medical diagnosis, finance, and autonomous vehicles. Its efficacy depends on data quality and problem structure; it can be brittle and opaque, and it may reproduce or amplify biases present in training data. Evaluation often uses task-specific benchmarks and real-world testing.

Ethical and societal considerations focus on safety, accountability, transparency, privacy, job impact, and governance. Researchers pursue methods for explainability, reliability, and alignment with user values. Policymakers and organizations advocate for standards and regulatory frameworks to address risks while enabling beneficial applications.