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Artificial intelligence (AI): 5 trends, hype-tested

If you are considering using artificial intelligence (AI) to mature your foundational IT and data capabilities, how do you separate hype from reality?

Whether you are exploring the promises of AI for your business or still wondering when you will see truly transformative results, here are five industry trends that will help realize AI’s untapped potential.

For most of us, deep learning systems are essentially incomprehensible. Using millions of data points as input and the correlating data as output, their internal logic can generally not be interpreted using plain language.

However, if automated systems are to assist in making critical decisions such as which operations and processes to use and we cannot understand how these decisions are made, how can we identify and address errors? This lack of common sense (a term first defined in the context of AI by John McCarthy in the 50s), has limited the application of AI in the real world to date. We need a clearer, less complicated AI system that better relates to the world and to people.

The original article can be found here.

Regarding to explainable AI and Causality, Professor Judea Pearl is a pioneer for developing a theory of causal and counterfactual inference based on structural models. In 2011, Professor Pearl won the Turing Award, computer science’s highest honor, for “fundamental contributions to artificial intelligence through the development of a calculus of probabilistic and causal reasoning.”  In 2020, Professor Pearl is also awarded as World Leader in AI World Society (AIWS.net) by Michael Dukakis Institute for Leadership and Innovation (MDI) and Boston Global Forum (BGF). At this moment, Professor Judea also contributes to Causal Inference for AI transparency, which is one of important AIWS.net topics on AI Ethics.