Professor Illah Nourbakhsh: AI Ethics & Retail Media Innovation
At Mediar, we are building more than a measurement platform, we are building trust in a new era of retail media. To do that, we are guided by leaders who combine deep technical expertise with a commitment to ethical, responsible innovation. One of those leaders is Illah Nourbakhsh, Professor of Robotics and Computer Science at Carnegie Mellon University.
Professor Illah Nourbakhsh has been part of AI’s story for nearly three decades. With early research at Stanford University and a long career as Professor of Robotics and Computer Science at Carnegie Mellon University, he has seen artificial intelligence grow from early reasoning systems to today’s predictive, data-driven platforms.
The Data Revolution That Changed Everything
Illah’s journey began during a pivotal era. In the 1980s at Stanford, he worked with some of the first AI reasoning systems, driven by an ambitious question: could machines truly “learn” like humans? The vision was compelling, but the reality was humbling. Without sufficient data, even the most elegant algorithms fell short of their promise.
Then the internet changed the game entirely. Those same methodologies suddenly had access to humanity’s digital footprint—images, conversations, text, and behavior patterns at unprecedented scale. Models that once struggled began to flourish. This transformation crystallized a fundamental insight for Illah: AI’s success depends not just on algorithmic sophistication, but on the depth and quality of the data that fuels it.
This principle continues to shape his vision today. The next breakthrough in AI will emerge from capturing new classes of data, particularly how people move, decide, and behave in physical spaces, and transforming these patterns into actionable predictions.
Ethics as a Cornerstone, Not an Afterthought
As AI matured, Illah emerged as one of its most thoughtful voices on ethics. His “Ethics and AI” course at Carnegie Mellon consistently ranks among the most popular on campus, reflecting how central these questions have become to the field’s future.
His approach is pragmatic: without trust, even the most sophisticated data becomes worthless. AI systems that involve human behavior must embed privacy protections from the ground up, not as an afterthought. This isn’t just moral imperative, it’s business necessity. Systems that erode public confidence ultimately undermine their own effectiveness at scale.
The Mediar Connection: Principles in Practice
llah’s path to advising Mediar emerged through his work with Robo Global, where he specialized in identifying companies that demonstrate meaningful AI applications. What distinguished Mediar was its foundation in real shopper behavior data, used to generate genuine predictive insights rather than superficial analytics.
The alignment with his core principles was immediate: robust data as the foundation, combined with an unwavering commitment to responsible implementation.
From Prediction to Action: The Weather Forecast Analogy
Illah frequently draws parallels to weather forecasting when explaining AI’s potential. Meteorologists synthesize historical patterns, real-time sensor data, and predictive models to anticipate tomorrow’s conditions with remarkable accuracy. Similarly, AI systems grounded in authentic behavior patterns can help organizations transcend backward-looking reports and embrace forward-thinking strategy.
This represents the critical bridge he’s passionate about: transforming raw data into practical decisions that drive real-world impact.
Looking Ahead: The Next Frontier
For Illah, AI’s ultimate measure has always been its ability to create tangible, measurable change beyond the laboratory. This perspective shapes his excitement about what’s coming next, particularly in how AI can transform retail and shopper understanding.
His advisory role with Mediar embodies this philosophy: anchoring advanced models in high-quality data, designing with ethical considerations at the forefront, and empowering organizations to make more intelligent, human-centered decisions. This intersection of rigorous research and practical application represents not just his career path, but his vision for AI’s future, sophisticated technology that serves human needs while respecting human values.
