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AI and ML - Coggle Diagram
AI and ML
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Cybersecurity Risks
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Data posioning
A risk with the use of AI/ML in cybersecurity is data poisoning. Essentially by using false or intentionally deceptive information and feeding it to an AI you can create a system that responds with incorrect information or results.
You find a data source that is being used to train an AI for your stock firm. you learn that this data was collected accurately but the writers of the data may have been biased, you decided to still throw out the data
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you discover that your coworker john has been submitting unverifiable data into your AI. John says it's not a big deal and he didn't realize. Is John being ethical?
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Ethical Challenges
job replacements
Removing jobs like data anyalsis or Cybersecurity expert and replacing them with AI to save money or to remove emplyees they do not like
Clearly the unethical decision, you are putting multiple employees out of work because you do not like them or feel their jobs may be redundant. These jobs may not actually be redundant or may be ready for AI to replace.
redundant work like filling out forms and getting rid of jobs like taking down notes from phone calls or fixing computers for people.
this is ethical as you are not removing any jobs or replacing them, instead the AI is being used to supplement the work done
Creating AI art
using AI art as a way to inspire your own art and collecting data to be used from consenting creators and artists
This is more ethical as an option as they give the artists credit and is not passing off the work of AI as your own
using AI to create art and pass it off as your own. In addtion using creators art without their consent to fuel AI art algorithims
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