Google releases AI Explorers to further lower the threshold for machine learning participation

In recent years, the use of artificial intelligence (AI) and machine learning (ML) has become quite popular, with AlphaGo, for example, becoming a fierce rival to human chess players. In addition, scientists use it to explore dark matter, marketers to develop the best advertising strategy, and many researchers hope it will be able to overcome epidemics like COVID-19. The good news is that to further lower the barriers to access and participation in machine learning, search giant Google has launched a new project called AI Explorers.

Google releases AI Explorers to further lower the threshold for machine learning participation

Hidden Bias (from: Google)

For most people, a lot of literature about machine learning may be too esoteric. With this in mind, Google hopes to help people better understand the core concepts of machine learning through the AI Explorers project and a series of interactive parsing.

Google has now released explanations of two basic concepts, “hidden bias” and “fairness measure”.

Google releases AI Explorers to further lower the threshold for machine learning participation

Measuring Fairness

Over the next few months, the tech giant will explain more concepts, such as the impact of the feedback loop on system bias, the logical steps the system takes to achieve specific goals, the handling of privacy issues, and what it means in the AI system.

In summary, AI research can be easier to access and inclusive with AI Explorers. Interested friends can move to google FAIR home page to learn more.