AI Safety Auditing: Pioneering Entrepreneur Gemma Galdon Clavell on AI Ethics, Biases, and the Pace and Limitations of AI Innovation

AI Safety Auditing: Pioneering Entrepreneur Gemma Galdon Clavell on AI Ethics, Biases, and the Pace and Limitations of AI Innovation

Dr. Gemma Galdon-Clavell is a pioneer and global force in AI safety and auditing, on a mission to ensure that AI large language models and unsupervised machine learning tools truly serve society. She is the founder and CEO of Eticas.ai, a venture-backed organization that identifies, measures and corrects algorithmic vulnerabilities, bias and inefficiencies in predictive and LLM tools. Eticas' software, the ITACA platform, is the first solution to automate impact analysis and monitoring, ensuring that AI systems are high performing and safe, explainable, fair and trustworthy. Gemma was acknowledged by the BBC as one of the "people changing the world" and this year honored by Forbes Women as one of the "35 Leading Spanish Women in Technology" and praised as "a pioneer in algorithmic auditing software". She also advises international and regional institutions such as the United Nations (UN), the Organization for Economic Cooperation and Development (OECD), European Institute of Innovation and Technology (EIT) and the European Commission, among others.

🔑Key Takeaways🔑

🚀What's Sci Fi and What's Real: Learn the limitations of AI innovation, as well as opportunities.

🔍 AI and Humans Must Work Hand-in-Hand: While AI excels in identifying patterns in medical imaging and policing dynamics, it's crucial to remember that human expertise and decision-making are irreplaceable. AI should complement rather than replace human judgment.

💡 Bias and Innovation in Venture Capital: AI has the potential to both perpetuate and mitigate biases in venture capital funding. Learn the importance of creating a venture fund that prioritizes social impact and leverages diverse perspectives.

🛠️ The Importance of Tailored AI Models: One size doesn't fit all when it comes to AI. Small, tailored models can be more effective for specific applications, ensuring better performance and minimizing biases and hallucinations.

🎙️Subscribe to Wings and get the full Show Notes at: https://bit.ly/Wings893

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