Short introduction I’m thrilled to sit down with Laurent Giraid, a renowned technologist with deep expertise in Artificial Intelligence, specializing in machine learning, natural language processing, and the ethical dimensions of technology. With cybersecurity becoming a cornerstone of trust in our digital world, Laurent offers a unique perspective on how ethical practices are reshaping the landscape in 2025. In our conversation, we explore the shift from traditional security to a more responsible approach, the role of AI in decision-making, the importance of trust and transparency in tech design, and the global strategies that balance innovation with cultural and regulatory needs.
How do you define ethical cybersecurity, and what sets it apart from the conventional focus on just protecting systems?
Ethical cybersecurity is about more than just building stronger defenses or locking down data. It’s a broader responsibility to safeguard not only organizations but also individuals and society as a whole. While traditional cybersecurity often prioritizes technical barriers—think firewalls or encryption—ethical cybersecurity considers the real-world impact of those measures. For instance, automatically shutting down a hospital system to contain a threat might do more harm than the threat itself. It’s about making decisions that balance security with the consequences for people’s lives, ensuring we’re not just solving a problem but doing so responsibly.
Why is it critical to prioritize the protection of individuals and society alongside organizational security in today’s environment?
In 2025, the stakes are higher than ever. With everything moving to the cloud and data breaches becoming headline news, people are more aware of how security failures affect them personally—whether it’s their privacy being invaded or critical services being disrupted. Focusing only on organizational needs ignores the human element. If a security measure alienates users or erodes trust, it’s ultimately counterproductive. Protecting society means building systems that respect privacy, minimize harm, and foster confidence, which in turn strengthens the organizations relying on those systems.
With security now seen as a baseline expectation rather than a competitive advantage, how can companies differentiate themselves in this space?
Security being a baseline means customers just expect it to work—no one’s impressed by a company simply having a firewall anymore. Differentiation comes from how a company handles data and implements security with integrity. Transparency in practices, ethical data use, and showing a genuine commitment to user well-being can set a company apart. It’s about proving you’re a trusted partner, not just a vendor. Companies that communicate clearly about their values and back it up with action—like refusing to exploit customer data—build loyalty in a way that tech specs alone can’t.
Can you explain what an ‘ethical by design’ approach means and how it shapes the development of technology products?
‘Ethical by design’ is about weaving fairness, transparency, and accountability into the very foundation of a product, right from the idea stage. It’s not an afterthought or a compliance checkbox—it’s a guiding principle. For example, when designing a security tool, we ask: Does this respect user privacy? Is it clear how it works to those using it? Can we stand behind every decision it makes? This mindset ensures that ethics isn’t just a reaction to problems but a proactive part of innovation, creating tools that users can trust inherently.
How does a commitment to not monetizing or monitoring customer data influence trust with your audience?
When you take a firm stand against monetizing or monitoring customer data, you’re sending a clear message: this information belongs to the customer, not us. That’s a powerful trust-builder. In an era where data is often treated as a commodity, users are wary of hidden agendas. By prioritizing their ownership over their data, you show respect for their autonomy. It’s not just a policy; it’s a promise that we’re here to protect, not profit off, their information. Over time, that transparency turns into a bond that’s hard to break.
Can you walk us through the concept of ‘trust by design’ and how it helps balance the push for innovation with managing risks?
‘Trust by design’ means embedding responsibility into every step of development, so innovation doesn’t come at the expense of safety or ethics. It’s about ensuring that new features or technologies are built with compliance and user trust in mind from day one. For instance, before rolling out a new tool, we align it with industry standards and rigorously test it for vulnerabilities. This approach lets us innovate quickly—say, integrating AI into security—while minimizing risks like breaches or ethical missteps. It’s a framework that keeps us accountable while still pushing boundaries.
How has the role of AI in cybersecurity evolved from being a supportive tool to taking on decision-making responsibilities?
AI in cybersecurity started as a helper—think pattern recognition or flagging anomalies for human review. But now, in 2025, it’s increasingly making decisions, like isolating a suspicious device or prioritizing threats in real time. This shift is driven by the sheer volume and speed of threats; humans can’t keep up without automation. However, it’s a double-edged sword. While AI can act faster, it also raises questions about accountability and bias. The evolution is exciting, but it demands strict oversight to ensure those decisions align with ethical standards and don’t cause unintended harm.
What are the most pressing ethical concerns when AI starts making critical security decisions on its own?
The biggest concerns are accountability and transparency. If AI makes a call—like blocking a system—and it’s wrong, who’s responsible? There’s also the risk of bias in the algorithms; if the data it’s trained on isn’t representative, it could unfairly target certain users or miss real threats. Another worry is the ‘black box’ problem—when AI’s reasoning isn’t explainable, users can’t trust or challenge its actions. These issues aren’t just technical; they’re deeply human, affecting trust and fairness in ways that can have serious real-world consequences.
How do global strategies, like adapting to local privacy and regulatory needs, enhance trust with customers across different regions?
Operating globally means recognizing that one size doesn’t fit all. Privacy laws, cultural expectations, and even trust in technology vary widely across regions. By tailoring our approach—say, aligning data centers with local regulations or having regional teams who understand local nuances—we show respect for those differences. This isn’t just about compliance; it’s about building cultural trust. When customers see that we’re invested in their specific context, not just applying a generic solution, they feel valued and understood, which is the bedrock of a lasting relationship.
What is your forecast for the future of ethical considerations in AI-driven cybersecurity over the next decade?
I believe the next decade will see ethical considerations become non-negotiable in AI-driven cybersecurity. As AI takes on more autonomous roles, the demand for transparency and accountability will skyrocket—think explainable algorithms becoming a legal requirement. We’ll also see tougher regulations around data privacy and AI bias, pushing companies to prioritize ethics over pure efficiency. Quantum computing will add another layer, challenging encryption norms and forcing us to rethink secure communication. My forecast is that the industry will move toward a human-centric model, where technology serves people first, and trust isn’t just earned but actively designed into every system.
