AI Security & Governance Courses

Artificial intelligence (AI) is becoming a driving force in today’s technology landscape. Its application has spanned across numerous sectors. Its rapid expansion brings unique challenges and considerations that demand specific expertise to ensure its effective, safe, and secure implementation and ongoing responsible management.

With the uptick in the adoption of AI, specific AI security risks are escalating, necessitating the need for advanced security measures. Notwithstanding the technical flaws in training an AI, it can make errors and present incorrect statements as facts, which is a flaw referred to as 'AI hallucination'.

Examples of AI Security risks include prompt injection attacks, which are a major weakness in language model systems. It happens when attackers make the model behave unexpectedly by giving it certain inputs. This could lead to generating offensive content, revealing confidential information, or causing unintended issues in systems that don't check inputs properly.

Data poisoning attacks occur when attackers alter the data used to train an AI model, resulting in undesirable outcomes such as security risks and biases. As language models are increasingly employed to transfer data to third-party applications and services, these types of attacks will continue to grow.

AI ethics is a subset of applied ethics and technology that focuses on the ethical issues raised by the design, development, implementation, and use of AI.

Business professionals now face growing demands to identify and mitigate ethical risks to navigating ethical trade-offs, such as privacy and accuracy, fairness and utility, and safety, security, and accountability.

AI can influence society and individuals in various ways, both positively and negatively. As AI technology advances rapidly, it's crucial to incorporate ethical considerations into the design process from the outset.