Transparency and AI

Transparency is one of the big five issues in TIPPER framework for managing legal risk of AI

The promise of AI: Businesses using powerful AI tools like ChatGPT are making an implicit promise to customers: we will give you vastly better service,

1. faster response times,
2. everything customized just for you,
3. smarter decisions, and
4. exponentially better value for your money.

And in exchange, customers, you trust us, you trust us to use these “black box” algorithms, that even we don’t understand, and, in exchange, you trust us with your personal data, with information about almost everything about you.

Businesses have to hold up their end. That means, in a word, “transparency” Businesses using AI tools must be transparent about

1. how AI is used and its limitations,
2. the risks associated with AI integration,
3. the type of data collected and how it is analyzed, and
4. the overall usage and handling of customer data, in order to maintain trust and avoid potential legal issues.

The Steps to Transparency: To uphold transparency and disclosure, businesses must

1. provide clear, honest explanations about their AI use and intentions and
2. keep their promises.

This involves

1. offering straightforward information about AI applications and data collection,
2. establishing and communicating data privacy policies,
3. enabling customers to access, modify, or delete their personal data, and
4. continually monitoring and updating AI systems and policies to stay current with evolving technologies and regulations.

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Here are some questions to keep in mind:

1. Be Clear about what AI is doing: Make sure that any communication generated by LLMs is clearly identified as coming from an AI system. This will help prevent confusion and potential legal issues that may arise if users believe they are interacting with a human when they are not.
2. User consent and privacy: Before implementing LLMs, make sure to establish a robust process for obtaining user consent to interact with AI systems and ensure that users understand how their data is being collected, processed, and used by the AI tool. This includes being transparent about data storage, retention policies, and sharing practices.
3. Compliance with emerging AI regulations: As AI continues to evolve, new regulations and guidelines are likely to be introduced. Every company should stay informed about any relevant AI-specific laws or industry best practices and ensure her business complies with them.
4. Transparency in AI decision-making process: While it might not be feasible to fully disclose the inner workings of the AI, it's important for each company to provide users with a general understanding of how the LLMs make decisions or generate content. This helps users trust the AI system and make informed decisions about whether to rely on the AI-generated content.
5. Disclosure of AI limitations and potential inaccuracies: To maintain transparency, every company should clearly communicate to users the potential limitations and inaccuracies of AI-generated content. This may include providing information on the AI's training data, the scope of the AI's capabilities, and any known issues that may affect the accuracy or reliability of the content.
6. Be transparent about what data you are collecting. What are you using the data for? Who can see the data?