Human-Computer Interaction for Knowledge Discovery for Management

Abstract

The rising volume of data in our networked world is a huge problem that necessitates practical and user-friendly solutions. Computational approaches may be useful, but we must recognize that problem-solving knowledge is stored in the human mind, not in robots. A strategic goal for finding answers to data-intensive problems might be to combine two domains that provide optimal preconditions: human-computer interaction (HCI) and knowledge discovery (KDD). HCI is concerned with human vision, cognition, intelligence, decision-making, and interactive visualization approaches; hence, it focuses mostly on supervised methods. KDD is primarily concerned with intelligent machines and data mining, namely the creation of scalable algorithms for discovering previously undiscovered associations in data, and hence focuses on automatic computational approaches. A proverb illustrates this perfectly: “Computers are incredibly fast, accurate, but stupid. Humans are incredibly slow, inaccurate, but brilliant.”