Ethics in AI: Don’t Let DANN Turn Evil!
Actua's AI Series - Activity 8
In this activity, participants will learn about morals and ethics, how they apply to the world, and how they apply to artificial intelligence. They will explore data bias, and learn how it can affect AI programs in significant ways. Participants will then use this knowledge to develop their own code of ethics for an artificial intelligence program.
If you’re accessing this activity directly, did you know there are eight other activities in this series up on our website? These activities also follow a space exploration narrative when done in order. It is recommended to complete the activities in order but they can also be done on their own.
If you find yourself unfamiliar with any of the AI concepts and terminology introduced in these activities, please refer to our AI Glossary. For more information about Artificial Intelligence and how to incorporate it into your classroom, we suggest exploring our AI Handbook.
Here we go:
You and your group-mates are astronauts and scientists aboard the Actua Orbital Station. Unfortunately, your station just got bombarded by magnetic rays and your electronics have begun to shut down! The only one who can save you is the orbital station’s AI, DANN. DANN stands for Dedicated Actua Neural Network, and it’s gone a little loopy. Brush up on your technical skills, learn about AI, and save yourself and your crewmates! So far, we have read through DANN’s manual, rebooted its audio and visual cores, and gotten all of DANN’s core functions fixed.
Most of DANN’s physical sensors and other functions are back online, like the audio core we fixed in “Voice Activated AI: Training Audio Recognition Models”. But DANN’s ethics system has been completely wiped! We have to make sure DANN understands the difference between right and wrong, and doesn’t use your data in evil ways. Could you imagine an evil AI? That would be a disaster! Once we can be confident DANN won’t turn evil, we can look at fixing its ability to understand us in “Sentiment Analysis: Understanding the Emotion Behind Text”.