The Key to Trusting AI: Security and Privacy

Security and Privacy — Principle of AI

When we talk about artificial intelligence (AI), one of the most important things to remember is that it must be secure and private—like driving a car.

You want the car to function properly, keep you safe, and always be in your control.

AI is no different.

These systems must perform as intended and resist tampering, especially by unauthorized parties.

In my experience working with IoT and smart cities, I have seen the risks and benefits of AI, and developers need to ensure that safety and security are built into every system from the beginning.

Let me explain with some simple examples.

Example 1: Self-driving Cars

One of the most exciting advancements in AI is the development of self-driving cars. Imagine a vehicle designed to drive itself from point A to point B.

The promise of these cars is enticing: fewer accidents, no need for human intervention, and efficient traffic management.

But what happens if the AI controlling the car is hacked? What if an unauthorized party can take control and steer the vehicle into danger?

This is where safety and reliability come into play.

The AI system must be designed to resist such interference. Developers must ensure that only authorized individuals can interact with the AI’s decision-making process.

If someone tries to hack into the system, the AI must be able to detect and prevent the intrusion. Without this security, the risk of accidents increases dramatically, and people may lose trust in AI technology.

In my experience with IoT and smart city solutions, we must design systems with these safeguards from the ground up.

AI systems should be tested rigorously under various scenarios to ensure they perform as intended, even in unexpected conditions.

For instance, just as we ensure an IoT device in a smart city responds safely during a power outage, a self-driving car should still behave responsibly if something goes wrong.

Example 2: AI-powered Healthcare Diagnostics

Another powerful application of AI is in healthcare.

AI systems are now being used to assist doctors in diagnosing diseases based on medical images or patient data. Consider how an AI system can analyze thousands of medical scans in seconds to identify potential problems like tumors or heart conditions.

But what if the AI system gives a wrong diagnosis? Or what if someone manipulates the data to favor certain patients while discriminating against others?

Here’s where privacy and data protection become crucial.

Developers must obtain consent before using someone’s personal health data to develop or run an AI system. Patients must know how their data is being used and should have the right to control it.

Data collected for these purposes should never be used to discriminate against patients based on race, gender, or other factors.

Incorporating security-by-design and privacy-by-design principles ensures that data is protected from misuse throughout the AI system’s entire lifecycle.

Developers should also adhere to international data protection standards so patients can trust that their health data is safe and won’t be used unlawfully. As someone who has worked with data from IoT systems, I know how easily personal data can be misused if not handled carefully.

Example 3: AI in Smart Home Devices

Now, let’s look at something more straightforward: smart home devices. Many people use AI-powered gadgets in their homes, like smart thermostats, voice-activated assistants, or security cameras.

These devices collect a lot of personal data.

Imagine if someone could access your security camera without your permission or your voice assistant recorded your conversations and shared them with companies you don’t know about.

Developers of these AI systems must obtain user consent before collecting and using this data. And once the data is collected, it must be protected.

The system should guarantee privacy, meaning the information stays confidential and cannot be accessed by unauthorized parties.

Moreover, the system must be transparent about how the data is used so that users can make informed decisions.

I often tell people that IoT and AI systems are like locks on a door. You wouldn’t leave your front door unlocked for anyone to walk in, right?

In the same way, AI systems must lock down data and make sure only the right people have access.

A secure and privacy-conscious design helps build trust with users, which is essential for the widespread adoption of AI technologies.

Final Thoughts

For AI to truly succeed and be embraced by the masses, it must be trustworthy.

We can’t ignore the risks associated with it, but we can mitigate those risks by focusing on safety, security, and privacy. AI systems must be reliable, and developers should always aim to meet the highest standards for protecting users’ data.

When AI is safe, secure, and controllable, we all stand to benefit from its incredible potential.

In every project I’ve been involved in, from IoT solutions to smart cities, this principle has been at the forefront: build systems that people can trust.

We can only realize AI's full potential in transforming industries, healthcare, and our daily lives.