Software powers nearly everything around us. From pacemakers to electric vehicles, from insulin pumps to smart doorbells, code has quietly moved from convenience to critical infrastructure.
But as software takes on more responsibility, the stakes grow higher. What happens when the algorithm driving a life-saving device or a self-driving car doesn’t behave as expected?
We tend to think of bugs as an inconvenience, an app freezing, a website glitching. But in high-stakes environments, even a minor bug can become a safety hazard.
So, what can we learn from industries that already treat software as a risk factor worth regulating?
The Expanding Reach of Software in Critical Systems
It used to be that safety concerns were tied to hardware. A cracked seatbelt, a faulty circuit, or a broken valve, these were physical failures we could inspect and test.
Now, more failures are digital.
An automatic braking system that misreads road signs. A heart monitor that drops a Bluetooth connection mid-operation. A home security app that lags in sending alerts. These failures may not leave a mark, but their consequences can be just as serious.
And the trend isn’t slowing. Software is becoming the interface between users and the physical world. That gives it tremendous power, and responsibility.
Which raises a simple question: are we designing software with the same care we apply to physical components?
Why Software Can Fail: Complexity, Updates, and Edge Cases
Unlike physical parts, software evolves. It gets patched, updated, integrated with third-party tools, recompiled for new devices. Each change introduces new complexity, and potential new failure points.
Here’s the catch: most software doesn’t fail because of poor intention. It fails because of assumptions.
An electric vehicle software may assume clean GPS input. A home alarm may assume a stable Wi-Fi connection. A medical device may assume user compliance. But what happens when those assumptions break?
Consider a pacemaker software that relies on internal clock sync. A slight timing mismatch could delay shock delivery by milliseconds, which, in a cardiac emergency, is unacceptable.
These aren’t just technical quirks. They’re safety risks. And the more environments a piece of software operates in, the more edge cases it encounters.
This is why traditional QA methods aren’t enough. We need design philosophies and regulatory frameworks built specifically for software.
Medical Devices and SaMD: Where Software Meets Human Health
Nowhere is this more evident than in Software as a Medical Device (SaMD). This is software that diagnoses, prevents, monitors, or treats diseases, without being part of a physical device.
Think of AI tools that analyze X-rays, mobile apps that monitor blood glucose, or cloud platforms that adjust medication based on real-time data.
Unlike traditional software, SaMD is held to medical-grade safety standards. Developers must follow rigorous quality systems, post-market surveillance plans, and often justify every line of code from a clinical safety perspective.
For a deeper dive into how these systems work, and what developers need to know, check this illustrated guide to SaMD.
Why does this matter beyond medicine?
Because SaMD offers a model for other industries where software affects safety, especially as smart technologies spread into daily life.
What Cars, Phones, and Smart Homes Teach Us About Software Safety
You don’t need a medical device to experience the consequences of a software failure.
Modern vehicles are rolling data centers. Software governs everything from steering to lane assist. A miscalibration can be deadly. Tesla’s autopilot incidents aren’t just PR issues, they’re safety case studies.
Home security? Also software-dependent. Cloud-connected cameras and alarms are great, until an app fails to notify you of a break-in. For people living alone or in remote areas, that’s not just annoying. It’s dangerous.
Curious how these systems work behind the scenes? Here’s the basic guide on how alarm systems work, a good reminder that even simple software tools carry assumptions that don’t always hold.
Even your smartphone isn’t exempt. When biometric authentication fails, it’s not just a password reset issue. In some regions, phone-based health monitoring and payment systems are vital. Software hiccups have real-world consequences.
The line between “consumer tech” and “critical tech” is vanishing. And that means safety can’t be limited to regulated industries anymore.
Global Safety Standards: ISO 62304, IEC 61508, and Beyond
So how do we make software safer?
One answer is standardization. Frameworks like ISO 62304 (for medical device software) or IEC 61508 (for electrical/electronic safety systems) define structured approaches to software development in safety-critical environments.
They require more than just testing. They focus on lifecycle risk management, documentation, traceability, and change control. If something fails in the field, these frameworks make it possible to trace why, and prevent it next time.
Adopting these standards isn’t about compliance checklists. It’s about building software with accountability in mind.
Other emerging standards are beginning to cover areas like autonomous vehicles, AI bias, and cybersecurity in embedded systems. The goal isn’t to make software perfect. It’s to make it reliable, explainable, and safe under real-world conditions.
Designing for Safety: From Risk Class to Real-World Use
Ultimately, the way we classify risk should inform the way we design software.
Medical device software is classified into different levels depending on the potential harm a failure could cause. This determines the scrutiny applied at each stage of development.
The same logic should apply elsewhere.
A game app doesn’t need the same safeguards as a smart lock. A food delivery service doesn’t need the same oversight as a digital blood pressure monitor. But the moment software affects security, health, or mobility, the development process needs to change.
Safety protocols should scale with impact, not popularity.
And that starts with recognizing that software isn’t neutral. It reflects the assumptions, values, and blind spots of those who built it.
Final Thoughts: Software Isn’t Harmless – And That’s Okay
We tend to talk about software as if it’s invisible. It’s just “there,” making things work. But when software touches safety, it stops being invisible. It becomes part of the system we rely on to live, move, and stay healthy.
Acknowledging the risk doesn’t mean fearing software. It means designing it like we design bridges, airplanes, and hospital beds, with layers of protection, transparency, and responsibility.
Whether it’s a heart monitor, a braking system, or a home alarm, the same principle holds: if software can fail, someone can get hurt.
And that’s reason enough to build it better.
