Course Description
These lessons on Privacy, Safety, and Security in Artificial Intelligence will discuss General Data Protection Regulation, consent, data portability, the ability to restrict processing, right to rectification, and right to erasure. You will learn important concepts involving reliability and safety and discover how monitoring can detect potential risks and quickly mitigate harm if the system is not functioning as desired. These lessons will also cover how traceability is important to safety.
In discussing the broad array of concepts surrounding privacy, safety, and security in artificial intelligence, we’ll look at the value and influence of the European Union General Data Protection Regulation (GDPR) that came into effect in 2018. We’ll also review the link between reliability and safety. For a system to be safe, there must be a certain level of reliability in the performance and decisions made by the system. A risk management approach can be used to figure out what testing procedures are relevant to a given domain and determine risks that the system might pose to important considerations like privacy and human rights.
By the end of these lessons, you’ll learn that the security of AI systems is also related to unauthorized use of the data or the AI system. You’ll discover that unauthorized use can cause harm to the creators and the users of the system, which is why many organizations are considering security-by-design in the implementation of any AI system.
What You'll Learn
- Understand the principles governing AI privacy, safety, and security, including the EU General Data Protection Regulation (GDPR) that came into effect in 2018
- Explain how reliability and safety are interlinked in AI systems
- Describe how monitoring can detect potential risks and quickly mitigate harm when a system is not functioning as desired
- Assess the relevant security principles of an AI system, including issues of unauthorized use of data
- Apply concepts of consent, data portability, restricting processing, right to rectification, and right to erasure
- Examine testing procedures and a risk management approach for determining risks an AI system might pose
Key Takeaways
- The EU General Data Protection Regulation (GDPR), which came into effect in 2018, addresses consent, data portability, the ability to restrict processing, the right to rectification, and the right to erasure.
- For an AI system to be safe, there must be a certain level of reliability in the performance and decisions made by the system.
- Monitoring can detect potential risks and quickly mitigate harm if a system is not functioning as desired, and traceability is important to safety.
- A risk management approach can be used to determine relevant testing procedures and identify risks the system might pose to considerations like privacy and human rights.
- Security of AI systems relates to unauthorized use of data or the system, which can harm creators and users, leading many organizations to consider security-by-design.
Frequently Asked Questions
What topics does this course cover?
It covers privacy, safety, and security in artificial intelligence, including the GDPR, consent, data portability, restricting processing, the right to rectification and erasure, reliability and safety, monitoring, traceability, testing procedures, and the security of data and outcomes.
What will I be able to do after completing this course?
You will be able to understand the principles governing AI privacy, safety, and security, explain how reliability and safety are interlinked, describe how monitoring can detect risks and mitigate harm, and assess the relevant security principles of an AI system.
What does the course say about the link between reliability and safety?
The course explains that for a system to be safe, there must be a certain level of reliability in the performance and decisions made by the system.
Why is security important for AI systems according to this course?
The security of AI systems is related to unauthorized use of the data or the AI system, which can cause harm to the creators and users, which is why many organizations consider security-by-design in implementation.
What lessons are included in this course?
The lessons are Consent and Control Over the Use of Data; Ability to Restrict Processing; Right to Rectification and Erasure; Reliability and Resilience of AI systems; Testing Procedures; and Security of Data and Outcomes.
