AI: Pros, Processes, and Pitfalls

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AI processes and drawbacks

Created by

rere ahmed

Egypt

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AI: Pros, Processes, and PitfallsOnline version AI processes and drawbacks by rere ahmed 1 AI systems never need human oversight after deployment. Yes No 2 Overfitting occurs when a model performs well on training data but poorly on new data. Yes No 3 All AI models are completely transparent and explainable by default. Yes No 4 The only cost of AI is computing power; there are no ethical concerns. Yes No 5 AI can automate repetitive tasks, increasing efficiency in many sectors. Yes No 6 A major challenge of AI is bias in training data affecting outcomes. Yes No 7 AI systems require ongoing monitoring to manage drift and maintain performance. Yes No 8 AI decisions are always unbiased if the data comes from a single source. Yes No 9 AI development does not require data; models are trained from scratch with no data. Yes No 10 AI development involves data collection, model training, evaluation, and deployment. Yes No

AI: Pros, Processes, and PitfallsOnline version

AI processes and drawbacks

by rere ahmed

AI systems never need human oversight after deployment.

Yes

Overfitting occurs when a model performs well on training data but poorly on new data.

Yes

All AI models are completely transparent and explainable by default.

Yes

The only cost of AI is computing power; there are no ethical concerns.

Yes

AI can automate repetitive tasks, increasing efficiency in many sectors.

Yes

A major challenge of AI is bias in training data affecting outcomes.

Yes

AI systems require ongoing monitoring to manage drift and maintain performance.

Yes

AI decisions are always unbiased if the data comes from a single source.

Yes

AI development does not require data; models are trained from scratch with no data.

Yes

AI development involves data collection, model training, evaluation, and deployment.

Yes

You can integrate the game into an LMS compatible with LTI 1.1 or LTI 1.3 such as Canvas, Moodle, or Blackboard. This way, the scores will be automatically saved into the platform’s gradebook.

AI: Pros, Processes, and Pitfalls

Yes or No

About this activity

Created by

Download the paper version to play

Top Games

Yes or No

Foot and Ankle Anatomy Quiz

Yes or No

Adjective Checker

Yes or No

Grammys for best song/record

Yes or No

Is it true?

Yes or No

Is it created with Artificial Intelligence? - Complete game

AI: Pros, Processes, and PitfallsOnline version

by rere ahmed

AI systems never need human oversight after deployment.

Overfitting occurs when a model performs well on training data but poorly on new data.

All AI models are completely transparent and explainable by default.

The only cost of AI is computing power; there are no ethical concerns.

AI can automate repetitive tasks, increasing efficiency in many sectors.

A major challenge of AI is bias in training data affecting outcomes.

AI systems require ongoing monitoring to manage drift and maintain performance.

AI decisions are always unbiased if the data comes from a single source.

AI development does not require data; models are trained from scratch with no data.

AI development involves data collection, model training, evaluation, and deployment.

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