Research Counsel, Data

As the Research Counsel, Data at Anthropic, you will be a vital legal advisor for data acquisition and risk mitigation pertaining to AI research. Your responsibilities will include advising research teams on data usage policies, collaborating on data sourcing strategies, and evolving guidelines to comply with legal risks and regulatory requirements. You will also play a key role in monitoring regulatory developments and engaging with external stakeholders to establish best practices for data governance in AI development.

To qualify for the Research Counsel, Data position at Anthropic, candidates should ideally hold a JD and be a member of a U.S. state bar, with California preferred. Having 5-10 years of experience in legal matters related to copyright, privacy, and data for technology or AI/ML products is essential. Familiarity with the machine learning development lifecycle and the ability to communicate complex legal concepts to cross-functional teams will also greatly enhance your application.

At Anthropic, the working atmosphere is dynamic and fast-paced, designed to support your adaptability and efficiency. As a Research Counsel, you will work within cross-functional teams where prioritization may shift quickly. The collaborative environment encourages open communication and allows team members to wear multiple hats, contributing to innovation while maintaining regulatory compliance, which keeps our mission aligned with real-world applications.

The Research Counsel, Data position at Anthropic offers significant opportunities for professional growth by allowing you to engage in high-stakes legal and technical discussions. You will be part of a cohesive team working on monumental research efforts in AI, enabling you to deepen your understanding of emerging technologies while shaping the legal landscape governing them. You can also develop your leadership abilities as you draft policies, advise your peers, and collaborate with external stakeholders to promote best practices in AI data governance.

The expected salary range for the Research Counsel, Data position at Anthropic is between $300,000 and $375,000 USD annually. This range reflects not just the expertise required for the role but is also complemented by competitive benefits, equity donation matching, and a hybrid work policy, providing you with a comprehensive compensation package for your contributions.

When advising a research team on data usage, I would first familiarize myself with the specific requirements and intentions behind their data sourcing. Then, I would analyze applicable copyright and privacy laws, ensuring compliance while aligning with our innovation goals. Clear communication is essential, so I would facilitate workshops or discussions to help teams understand data policies and legal implications, ensuring a smooth collaboration and fostering a culture of responsible data usage.

I have substantial experience identifying legal issues surrounding data usage, particularly in AI. This includes staying abreast of regulatory changes and collaborating with multiple stakeholders to formulate strategies tailored to address risks, such as adhering to the EU AI Act. My proactive approach has allowed me to draft comprehensive policies that mitigate risks while supporting innovation and project timelines.

To stay up-to-date with legal changes regarding data and AI, I regularly read industry publications, attend relevant seminars, and participate in forums with legal professionals and academia. Engaging with peers in my network who specialize in data governance and AI development also helps me gain fresh perspectives on evolving legal landscapes.

In my previous roles, I've had extensive experience drafting clear and concise policies tailored to data governance. This includes creating guidelines that intricately detail the lawful acquisition and usage of data for machine learning. I put a strong emphasis on clarity and accessibility, understanding that effective policies not only reduce legal risks but also empower cross-functional teams to adhere to best practices.

Key legal concerns when working with AI training data include copyright infringement, data privacy issues, compliance with regulatory frameworks, and the risk of biases in datasets. Each of these aspects requires careful scrutiny and a nuanced approach. I ensure that all data sourced respects intellectual property laws while also addressing ethical considerations, particularly when data significantly impacts diverse populations.

In my past roles, I've actively fostered cross-functional collaboration by facilitating workshops and regular meetings to align legal teams with technical teams’ objectives. By creating a platform for open dialogue, I helped bridge gaps in understanding between legal requirements and technical constraints, leading to a more cohesive strategy that supports both the business's mission and innovative goals.

Balancing regulatory compliance with innovation requires an astute understanding of both realms. My approach involves closely monitoring regulatory developments and then educating technical teams about implications while encouraging creative solutions. Implementing flexible data usage guidelines that allow for agile innovation processes, while making legal safeguards a priority, is critical to achieving this balance.

I manage multiple priorities by employing several strategies: establishing clear objectives and timelines for projects, using prioritization frameworks like the Eisenhower Matrix to differentiate between urgent and important tasks, and maintaining an organized calendar to balance my workload. Regular check-ins with project stakeholders allow me to recalibrate efforts and maintain alignment as priorities shift.

Ethics is fundamental in AI development, as it can dictate how technology is perceived and used in society. My stance is that ethical considerations must be woven into every stage of AI model development, from data collection to deployment. By advocating for responsible AI practices and transparency with stakeholders, I work to ensure our innovations are beneficial, just, and supportive of a diverse set of perspectives.

Handling ambiguity in AI legal issues involves a mix of thorough research and consulting with experts in respective fields. I adopt a pragmatic mindset and focus on risk assessment while remaining adaptable. I prioritize clear communication about potential legal implications when new challenges arise and encourage a culture of shared learning among teams to address uncertainties collaboratively.