AI Ethics and Responsible AI for Data Scientists

As data scientists and business leaders, we need to think about the ethical and privacy considerations of machine learning and artificial intelligence.

Featuring

Scott Zoldi

Chief Analytics Officer

FICO

Michael Krigsman

Publisher

CXOTalk

Overview

As data scientists and business leaders, we need to think about the ethical and privacy considerations of machine learning and artificial intelligence. FICO's Scott Zoldi shares recommendations around responsible AI, ethics, and privacy during this important conversation.

The Conversation Covers These Topics:

Scott Zoldi is chief analytics officer at FICO responsible for the analytic development of FICO's product and technology solutions. While at FICO, Scott has been responsible for authoring more than 100 analytic patents, with 65 granted and 53 pending. Scott serves on two boards of directors, Software San Diego and Cyber Center of Excellence. Scott received his Ph.D. in theoretical and computational physics from Duke University.

Main Discussion

Scott Zoldi: "We persist our model development governance process and we define it around the blockchain technology, so it's immutable."

Michael Krigsman: "Scott Zoldi is the chief analytics officer of FICO."

Scott Zoldi: "We're a company that focuses on predictive models and machine learning models that help enable intelligent decisioning, decisions such as fraud detection, decisioning such as risk. At the heart of our company are analytic models that are driving these decisioning systems. My role as a chief analytics officer is to drive the decisions we make with respect to machine learning and analytic technologies that enable these decisioning software. That includes a lot of research in areas such as machine learning as we address the increasing digital needs out there with respect to decisioning systems and software."

What is responsible AI?

Michael Krigsman: "When we talk about responsible AI or ethical AI, what do we actually mean?"

Scott Zoldi: "Responsible AI is this concept of ensuring that we have a level of accountability with respect to the development of these models. I like to talk about it in four different pieces."

  1. Robust AI: Ensuring that we take the time to build models properly, understanding the data, ensuring that it's well balanced and not overtly biased, and choosing the right algorithms.
  2. Explainability: What is driving that decision in the model? Interpretability of models is crucial.
  3. Ethical AI: Ensuring that the model does not have a different impact for different groups of people.
  4. Auditable AI: Being able to audit how the model was developed and ensuring it operates as intended when making decisions.

Michael Krigsman: "How central is responsible AI to your work at FICO?"

Scott Zoldi: "It's really central to my work. I have authored now 20 patents in this area, so it's a huge focus for myself and for the entire firm."

AI Governance and Ethical Principles

Scott Zoldi: "We need to constrain the data scientists to use prescribed technologies that we find responsible, as there are different methodologies that they might apply."

Michael Krigsman: "What is the organizational standard associated with responsible AI?"

Scott Zoldi: "Today, organizations are often characterized by diverse analytic teams defining their own methodologies. It's essential to have a corporate standard that ensures consistency and accountability."

Michael Krigsman: "What are the main blockers to implementing responsible AI practices?"

Scott Zoldi: "Lack of executive visibility at the board level about the importance of responsible AI is a significant obstacle."

Responsible AI and Corporate Culture

Michael Krigsman: "What if the responsible AI framework conflicts with corporate goals?"

Scott Zoldi: "We need a C-level executive sponsor for the responsible AI framework who can bridge the gap between corporate goals and responsible practices."

Scott Zoldi: "Ethical AI is a corporate governance standard; when organizations prioritize responsible AI, it enables them to meet their business objectives without harming individuals."

Conclusion

Michael Krigsman: "Scott, what advice do you have for data scientists and business leaders?"

Scott Zoldi: "Data scientists should advocate for corporate governance around AI practices, while business leaders must ensure that ethical standards are part of the organization's discourse. It’s vital that both perspectives converge to create a robust AI governance framework."