Balancing Ethics, Regulation, and Strategic Opportunities

Join us for an insightful conversation with one of the industry’s leading voices, Rob Risany, Director of Edge AI Solutions at Intel Corporation. We talk about the importance of collaboration between government and industry to balance innovation and regulation and how disruptive innovation can transform national strategies. Rob emphasizes the ethical considerations of AI, such as data privacy and responsible practices, and the complexities of regulating AI initiatives.

Watch&Listen to the full interview here.

Rob Risany

Director of Edge AI Solutions at Intel

Rob, could you tell us a bit about yourself and your role at Intel for those who may not be familiar with you?

Absolutely. I’ve had a diverse career spanning several years and various fields. I spent ten years at IBM in advanced analytics, working on data science and techniques now broadly classified as AI. I was involved in this field before it became mainstream. Back then, it was mainly statisticians working behind the scenes, but now data science is widely recognized, and there’s no longer a shortage of skilled professionals.

At Intel, my role is to bridge the gap between emerging technologies and specific industry problems. It’s one thing to have theoretical concepts, but the real impact comes when these technologies are applied to practical business issues. The goal is to make these technologies accessible not just to large corporations but also to smaller businesses. I focus on integrating these technologies with the Intel ecosystem to accelerate market readiness. We want to move from theoretical ideas to real-world applications that benefit a broad range of industries, from local grocery stores to mining companies.

As the Director of Edge AI Solutions, you’re at the fascinating intersection of edge computing and artificial intelligence. How do these technologies bring tangible value to businesses?

Sure, I’d be happy to. I often use retail as a starting point because people can easily relate to it. When discussing AI, it’s crucial to translate abstract concepts into understandable examples. Many think of AI as just something like ChatGPT, generating text, but its applications go far beyond that.

In retail, AI can transform the shopping experience. For instance, nobody likes waiting in long lines with just a few items. AI can facilitate smoother self-checkout options, enhancing customer satisfaction. Similarly, if you’re in a hardware store and can’t find that one bolt for your dishwasher, AI can help streamline the process, ensuring better customer service.

The key point about edge computing is that it brings computing power and analytics to the location where the experience happens—at the edge. This isn’t just about having servers on-site; it’s about enhancing the customer experience directly where it occurs. The edge is where real-world interactions take place, whether in a store, on a cruise ship, or in a call center. It’s where value is created and captured.

This approach is not only applicable to retail but extends to various sectors, such as industrial settings, healthcare, manufacturing, the public sector, and more. For example, edge AI can monitor machinery in manufacturing in real time to prevent downtime. In healthcare, it can provide immediate analysis of patient data, leading to quicker diagnoses.
In essence, the combination of AI and edge computing allows us to improve processes right where they happen, making the technology practical and beneficial for a wide range of industries.

How does Intel handle concerns and regulations about the sensitive data being captured?

First, it’s essential to acknowledge that AI can present ethical challenges. Organizations, governments, and agencies must consider issues like data privacy, such as those outlined in the European GDPR. The key is understanding the proper use of data and focusing on its specific applications.

Take machine vision, for example. It’s growing rapidly due to the rich information cameras can provide. Video enhances human connections even across long distances. However, storing and using this data unethically, like misusing facial recognition, is a concern. Organizations need governance structures to ensure ethical practices and avoid unnecessary data storage.

Regarding recent regulations like the EU’s AI Act, which aims to prevent AI from influencing personal autonomy, there’s bound to be a period of adjustment. Initially, regulations might swing from being too lenient to too strict before finding a balance. Definitions like “personal autonomy” can be subjective, making implementation complex.

Intel plays a crucial role in these discussions, working with governments and leading industry coalitions to prioritize ethics in AI. This proactive stance helps shape responsible practices and guidelines. While regulations will vary by country, the goal remains to balance technological advancement with ethical considerations. Overall, handling sensitive data responsibly and navigating regulatory landscapes will be essential as AI and edge computing continue to evolve.

Rob, thank you for joining us and discussing edge computing and AI. We appreciate your experiences and perspectives on practical applications and ethical considerations. Look forward to future conversations!