Professor Judea Pearl, World Leader in AI World Society (AIWS) Award 2020, Board Member of the History of AI, conceived Deep Understanding and Data Interpretation. Michael Dukakis Institute supports this concept and model, as it will create more transparency, smarter, and easier to monitor in AI. It also will help reduce data and resources, thus saving energy and environment. Governments and business should invest more for education, research, and development of the Judea Pearl model and to create decision-making systems for governments and society.
Professor Judea Pearl wrote:
“The bulk of machine learning in AI (as well as DATA Science in general) is operating in ‘data fitting’ mode, as opposed to ‘data interpretation’ mode, which characterizes scientific thinking. ‘The data-fitting school is driven by the faith that the secret to rational decisions lies in the data themselves, if only we are sufficiently clever at data mining. In contrast, the data-interpreting school views data, not as a sole object of inquiry but as an auxiliary means for interpreting reality, and ‘reality’ stands for the processes that generate the data.’
Mathematical analysis reveals inherent limitations of the data-centric paradigm, and its inability to read Deep Understanding of the domain of discourse. This limitation entails inherent limitation in achieving human level intelligence, specifically in meeting requirements of adaptation, explainability, robustness, and ethics.”