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#Communication
Balloon Debate
Say: “We are going to debate about the boon and bane of various AI applications in the different
industries you researched. This will be a 4 v 4 debate. As you know, each theme has been given to two
different teams. Now one team out of these two will be in favour of AI applications of that theme, while
the other one will be against AI applications in the same theme. The debate will go theme by theme
wherein each member of the team will get a minute to speak. The first speaker of the affirmative team
will start the debate after which the first speaker of the rebuttal team will put their points. In this manner,
each speaker will get a minute to speak and finally one team will be chosen to be eliminated from the
balloon debate depending upon how convincing their points were. The speaker who speaks for more
than a minute will get his team disqualified. You will get 15 minutes to prepare your points. And your
time starts now!”
Imagine there are two families of four people out for a ride in a hot air balloon. Suddenly, the balloon
starts to move towards the earth instead of staying airborne. To stabilise it, one family needs to take the
parachute and go out of the balloon or else it will come crashing down.
Who should be thrown out of the hot air balloon?
The AI project cycle is the process of converting the real-life problem into an AI-based model. The project cycle
framework is designed to help project managers guide their projects successfully from start to end. The purpose
of the project life cycle is to create an easy-to-follow framework to guide projects. The AI project cycle provides us
with an appropriate framework which can lead us towards our goal.
Stages in an AI Project Cycle
The AI project cycle involves several key stages, each building upon the previous one to develop, deploy, and
maintain an AI system effectively. These stages are as follows:
• Problem Scoping: The first stage of an AI project cycle is problem scoping to identify the problem and have
a vision to solve it. Problem scoping refers to understanding a problem and various factors which affect the
problem, and finding a solution for it using AI technology. The 4W’s of problem scoping are Who, What, Where,
and Why. These Ws help in identifying and understanding the problem in a better and efficient manner.
• Data Acquisition: The next stage of the AI project cycle is data acquisition. The term data acquisition means
collecting raw data for the purpose of reference or analysis for the project. The data can be in the form of
text, numbers, images, videos, or audio and it can be collected from various sources like Internet, journals,
newspapers, and so on. The data acquisition system allows us to obtain valuable information about reality to
improve the performance of the project.
• Data Exploration: Data exploration refers to the techniques and tools used to visualise data collected in data
acquisition through complex statistical methods. It is the process of analysing a large dataset.
• Modelling: It is the design phase of the AI project cycle. In this, we select the best way to reach the solution.
It requires the process of selecting the right algorithm to develop a working model for the project. In this
step, different models based on the visualised data can be created and even checked for the advantages and
disadvantages of the model.
114 Artificial Intelligence Play (Ver 1.0)-IX

