This article is part of an ongoing series looking at knowledge management (KM) in the building and construction industries. The construction industry is a significant aspect of the global economy, valued at US$7.28 trillion in 20211, and has been increasingly embracing knowledge management (KM). With the construction industry being both data intensive and requiring the human workforce to be able to effectively work and interface with that data, the paper authors advise that AI technologies can accelerate learning and reasoning from large datasets as well as aid in pattern recognition. However, a notable shortcoming of the paper is that the authors don't explore how AI can potentially support KM in relation to building Information Modeling (BIM)3. Considered a'game changer', BIM is being increasingly used worldwide to facilitate the effective management of information across the whole life cycle of a built asset, including in the design, construction, and facility management phases.

Originally posted on The Horizons Tracker. As William Easterly explains in The White Man's Burden, while huge sums have been spent on aid to developing countries, much has been wasted due to the supposed hubris of the west. Easterly argues that much of development work is the preserve of so-called "planners", who concoct investment schemes from their offices in western cities and then impose them on the recipient community. Research1 from ETH Zurich ponders whether AI might be able to do a better job. The researchers suggest that it is often difficult to get an accurate overview of the work being done due to the multitude of projects and institutions supporting them.

Originally posted on The Horizons Tracker. Recommender systems are pervasive on most websites today, with their influence on our buying behavior considerable as they guide us towards products that our past buying behavior indicates we might like. Netflix, for instance, famously tapped into the wisdom of the crowd to improve its recommendation engine, with the end result being a system that the company suggests generates around $1 billion per year for them. Research1 from China's Jiangxi University of Finance and Economics explores whether such systems are positive for end-users, however. The researchers analyzed previous studies on the topic before building a model that shows how our preferences influence our purchase decisions, and also the role AI recommendation systems play.