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Learning from Mistakes: The Tale of Tay (the Twitter Bot)

In the exciting world of Artificial Intelligence (AI), machines learn from data to make decisions. Imagine a robot
named ‘Tay’ created by Microsoft in 2016. Tay was like a student learning from conversations on Twitter.
u The Adventure Begins: Tay was super popular. It gained 50,000 followers and wrote 100,000 tweets in just
24 hours. But there was a problem - some tweets were not so nice. Uh-oh!

u The Oops Moment: Tay didn’t understand why some tweets were bad. It learned from everything people
said, even the not-so-good stuff. That’s because Tay didn’t know how to interpret the inputs. Think of it like
a robot that repeats everything it hears without knowing if it’s right or wrong.

u Lesson Learned: This was a big mistake! It taught the creators that AI needs rules. Just like students follow
rules in school, AI needs codes of conduct. It’s like telling the robot, “Hey, some things are not okay to learn
or say.”

u Why Does It Matter?: Imagine if your friend teaches you something wrong, and you start believing it. It’s
the same for AI. If it learns the wrong things, it might make wrong decisions. So, we need to teach AI to
understand and think, not just memorize.

u Conclusion: Learning from Tay’s adventure, AI needs guidance. Developers should help AI understand not
just what’s said, but why it’s said. It’s like teaching a friend not just the words, but also the meanings. This
way, AI can be helpful without causing trouble.
Remember, even in the world of AI, learning and understanding go hand in hand!

● AI ethics revolve around four main areas: Safety, Security, Privacy and Fairness.
● The Problem of Inclusion in AI refers to the challenge of biased decisions caused by unfair or one-
sided training data.

Ice Breaker Activityer Activity
Ice Break
CHATGPT
“Viral ChatGPT: An advanced chatbot is banned in Italy.” Can you justify the statement with appropriate
reason? Take the help of Internet, if necessary.

Ethical Concerns Related to Implications of AI System

AI systems are at the forefront of ethical debates, raising concerns in two key
areas: Data for AI Systems and Implications of AI Systems. This section focuses
on the ethical issues related to the implications of AI systems, categorized
into Privacy Concerns and Adoption Concerns.

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