Learn about the core dimensions of responsible AI and discover which one to consider when using personal identifiable data. Explore options like explainability, privacy and security, fairness, and robustness.
Table of Contents
Question
A company is using artificial intelligence (AI) with data that includes personal identifiers. They want to implement best practices of responsible AI with this data.
Which core dimension of responsible AI should they consider?
A. Explainability
B. Privacy and security
C. Fairness
D. Robustness
Answer
B. Privacy and security
Explanation
Incorporating privacy and security safeguards helps companies develop AI that respects user rights, protects vulnerable data populations, robustly withstands attacks, follows regulations, and builds critical user trust through responsible data handling. AI that directly handles personal data requires responsible privacy and security practices. Ignoring these can lead to dangerous failures.
When dealing with personal identifiable data, it is crucial to prioritize the protection of individuals’ privacy and ensure the security of their information. This involves implementing measures to safeguard the confidentiality and integrity of the data throughout its lifecycle.
Responsible AI practices related to privacy and security include:
- Data anonymization: The company should anonymize or pseudonymize personal identifiers to minimize the risk of re-identification. By removing or encrypting directly identifiable information, such as names or social security numbers, the company can reduce the chances of unauthorized access or misuse.
- Data encryption: Employing encryption techniques, both during data storage and transmission, adds an extra layer of protection. Encryption helps prevent unauthorized access to personal data, ensuring that even if the data is intercepted, it remains unreadable without the appropriate decryption keys.
- Access controls and permissions: Implementing strict access controls and permissions helps limit data access to authorized individuals or systems. The company should establish policies and procedures to define who can access the data, what level of access they have, and under what circumstances.
- Data lifecycle management: Responsible AI practices involve managing personal data throughout its lifecycle. This includes defining retention periods, securely deleting or anonymizing data when it is no longer needed, and ensuring compliance with relevant data protection regulations.
- Transparency and consent: The company should be transparent about the collection and use of personal data, providing clear explanations to individuals about how their data will be processed. Obtaining informed consent from individuals before using their data is essential to respect their privacy rights.
By considering privacy and security as a core dimension of responsible AI, the company can demonstrate a commitment to protecting individuals’ personal information, fostering trust, and complying with applicable data protection laws and regulations.
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