Week 1- AI

Tasks that AI can solve

What can artificial intelligence do? A lot. The main thing is to formulate the task correctly and provide the algorithm with the necessary data. AI learns well and can understand speech, recognize questions, and decipher information from images and photographs. With the right approach, AI can guide a client from making an inquiry to solving a problem. If, for some reason, the request proves to be too complex for AI, it is transferred to a specialist.

One of the achievements that can be attained through AI is adaptive learning. The essence is that the digital platform on which a person learns analyzes their successes and mistakes and selects precisely those tasks that will be beneficial to them. This makes learning personalized.

A whole family of such digital AI-based solutions is already helping schoolchildren with mathematics. For example, a mobile application can suggest a child first take a small test and based on the results, create an individualized micro-learning lesson plan. The application can be used by preschoolers who are just learning to count, as well as ninth graders who need help mastering inequalities and trigonometric functions.

The AI tutor explains new topics, provides solution examples, checks exercises completed by the child, and gives feedback. One can even scan a mathematical problem from a textbook or write it on the screen—and get the solution and similar examples. Games are also available for children where they need to perform arithmetic operations.

Additionally, the application will offer courses for a broader audience (from elementary school students to university students) and besides mathematics, it also teaches chemistry, physics, statistics, and even the basics of accounting.

In theory, this could mean saving on tutoring sessions by replacing some of them with platform-based learning.


References:

Chesani F., Mello P., Milano M. Solving mathematical puzzles: a challenging competition for AI //AI Magazine. – 2017. – Т. 38. – №. 3. – С. 83-96.

Howe A. E., Von Mayrhauser A., Mraz R. T. Test case generation as an AI planning problem //Knowledge-Based Software Engineering. – 1997. – С. 77-106.

Chui M. et al. Notes from the AI frontier: Insights from hundreds of use cases //McKinsey Global Institute. – 2018. – Т. 2. – С. 267.

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