Advances in digital technologies and ever growing amounts of data outpace organizations' ability to attend to and make sense of such vast data in knowledge work. Consequently, many organizations face uncertainty in decision-making and problem-solving, which places special demands on ICT design. To cope with such knowledge problems, more and more organizations turn to intelligent technologies, which promise a major breakthrough in how organizations collect, analyze, and act on data and information. Reportedly, 78 percent of managers will trust algorithmic advice in making decisions. Yet old problems loom large. Evidence of fatal failures and repeat problems of control in adaptation of artificial intelligence (AI)-based technologies abound in press and research alike. Since no set of permanent solutions exist, such phenomena call for more research into the sociotechnical arrangements of algorithms, humans, and organizational practices. This project takes an insider view from behind the scenes at a multinational firm in international maritime trade and its dealings with the design and adaptation of data-driven intelligent technologies. We take an interpretive, pragmatist perspective and draw on practice-based approaches to uncover the sociotechnical practices and processes which AI spring from. In particular, we are interested to develop a detailed understanding of emergent configurations of human-machine collaboration and feedback mechanisms as a source for data-driven strategic advantage. Despite much scholarly interest in both AI and the role of uncertainty, surprisingly little attention has been paid to the role of emerging data-driven and algorithmic technologies in shaping firms' knowledge practices and strategies under conditions of uncertainty.
Project leader: Eirik Grønsund
Institution: ISERV COMPUTING AS