Launching an AI product is a complex endeavor, and the role of in-house counsel is critical in navigating this process. It’s comparable to launching a driverless car on the highway and ensuring the brakes are well-checked. The success of AI products isn't just about technical readiness but also about legal and ethical preparedness.

The most successful AI launches share a common thread: in-house counsel equipped with the right questions. These are not merely procedural inquiries but are crucial for shaping the product into something ethical, defensible, and competitive. Here's a closer look at the essential conversations in-house lawyers should have before any AI product goes live.

1. What Exactly Are You? Understanding the AI system in plain language is crucial. Is the AI designed to generate content, make predictions, or influence decisions? Knowing exactly what the AI does and the business need it addresses helps mitigate risks associated with its deployment.

2. Where Did You Learn This? AI systems learn from data, and the source of this data is critical. Whether it's from licensed sources, open datasets, or internal archives, knowing the provenance of data helps avoid intellectual property disputes and compliance issues.

3. Which Rules Apply To You? AI does not operate in a legal vacuum. It’s subject to a myriad of global and sector-specific regulations. Understanding these legal frameworks beforehand can save costly redesigns and compliance headaches later.

4. Can You Prove You’re Fair And Accurate? It’s vital to test how the AI performs across different demographics to prevent biases. These tests should aim to identify problems rather than validate assumptions, thus avoiding potential legal and reputational risks.

5. Can You Explain Yourself? Transparency in AI processes is crucial, especially in sectors like healthcare or finance. In-house counsel must ensure there are plans for how the AI’s decisions can be explained to regulators and users alike, maintaining accountability.

6. Who Owns The Output And The Data Trail? Ownership issues of the AI’s outputs and data should be resolved before launch. Clarifying how data is stored, used, and who has rights over it is essential for compliance and operational transparency.

7. What’s The Plan When Something Goes Wrong? Finally, having a robust plan for when things go wrong is essential. This plan should include escalation protocols, pre-drafted regulatory responses, and clear communication strategies, ensuring readiness for any unforeseen issues.

These seven questions are not just a checklist but a framework for responsible innovation. By addressing these areas, in-house counsel can help ensure that the AI product is not only legally compliant but also poised for success in a competitive marketplace. This approach shifts the focus from merely being able to launch to launching with confidence and integrity.