🔬 Managing AI Risks in MLOps: Insights from CEO Alex Combessie
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Ensuring quality in AI models and mitigating risks with Giskard MLOps platform
🇺🇸🇬🇧 English transcript
VT: Vincent Touraine, journalist at BFM Business TV, host of the FocusPME show.
AC: Alex Combessie, co-founder and CEO of Giskard.
VT: Ensuring the quality of Artificial Intelligence models by eliminating biases that can penalize organizations, that’s the mission of Alex Combessie, hello!
VT: You are the CEO and co-founder of Giskard, G-I-S-K-A-R-D
VT: Thank you for being with us at Focus PME. So, we’re going to talk about Giskard, your company, your startup. First, where did the idea come from?
AC: So, the idea of Giskard came firstly from our experience. We’re three co-founders and we’ve been working for 10 years as engineers/data scientists, and we develop systems based on Artificial Intelligence for large enterprises. And we realized around three years ago that there’s a real acceleration in AI, but that there’s a real need for an AI that is responsible and regulated. Because now AI is everywhere, and it can pose real problems and risks for companies.
VT: We’re seeing this right now with ChatGPT, absolutely
VT: It’s just the tip of the iceberg
VT: What does Giskard propose as a solution exactly?
AC: What we have is a software to ensure the quality of algorithms, specifically to measure and mitigate ethical problems of algorithms, trust issues and false information, and to avoid these issues happening to algorithms that are used on the general public
VT: Internally do you call yourselves Giskardians?
AC: We’re Giskardians, exactly
VT: What are the risks of Artificial Intelligence
AC: So, there are multiple risks. First, we’ll talk about risks to society and ethical risks, AI that is used in public services, financial services that can either create or reinforce certain discriminations against certain groups. It can lead to exposing companies to considerable reputational damages. Secondly, the trustworthiness of models. We sometimes talk about the robustness of algorithms, or more simply algorithms that make mistakes. And algorithms that make errors, algorithms that aren’t more perfect than humans, can have big problems when we think of Artificial Intelligence in industrial applications, or the medical industry. There are economic implications that can be considerable
VT: So, what is the result of using Giskard?
AC: We help companies to test their models before going into production. Testing is something we know, it’s normal for all industries, and we help to apply it to Artificial Intelligence. The result for businesses is reducing their risks, because for them there can be real regulatory issues, and that soon in Europe noncompliance will expose companies to fines of 6% of their global revenue.
VT: There’s not much talk about this, but yes 6%
AC: We don’t talk about it enough, but a company that has 10 billion in revenue would have 600 million euros in damages and potential risks, that we help to avoid.
VT: We’ll talk about your development, you’re a young company, a startup created in 2021 based in Paris, with 12 employees. What are you working on right now to prepare for the future?
AC: Our goal is to be able to test all types of Artificial Intelligence, so exactly like you mentioned ChatGPT and other conversational models, how to ensure their trustworthiness and avoid errors and biases is something we’re currently working on.
VT: And we’ll certainly follow Giskard, it’s a name you won't forget. Thank you very much Alex Combessie for being with us at Focus PME, CEO and co-founder of Giskard. Goodbye
AC: Thank you, goodbye