Today we talk a lot about the “responsible” use of AI, but what does that actually mean?

Generally speaking, being responsible means being aware of the consequences of your actions and ensuring that they do not cause harm or put anyone at risk.

But there's a lot we don't know about AI. For example, it is very difficult to say what the long-term impact will be of developing machines that can think, create, and make decisions for us. It will affect human work and life in ways that no one is yet sure about.

One of the potential dangers is the violation of privacy, which is generally accepted as a fundamental human right. AI systems can now recognize us in the following ways: our face When we are in public places and are routinely used to process sensitive information such as health or financial data.

So what does responsible AI mean when it comes to privacy, and what challenges does it face for businesses and governments? Let's take a look.

Consent and privacy

AI often uses data that many of us consider private, such as our location, finances, and shopping habits, to provide services that simplify our lives. This could be route planning, product recommendations or protection from financial fraud. In theory, all this is possible because of consent. We consent to our information being used. Therefore, its use is not an invasion of privacy.

Respecting and acting on consent is one way companies can ensure they are using AI responsibly. Unfortunately, this doesn't always happen.

For example, the Cambridge Analytica scandal found that personal data from millions of Facebook users was collected without their consent and used for political modeling.

Companies and even law enforcement agencies have faced public backlash for using facial recognition technology without taking the proper steps to obtain consent.

A key question is when consent becomes invalid, as its scope is so wide that it can be interpreted in ways that the consenter never imagined. Or is it a case where the terms and conditions given when seeking consent are very complex and can be frequently misunderstood?

To treat privacy responsibly, systems and processes for obtaining clear informed consent must be built into the core of AI systems, rather than simply added on as an afterthought.

One example is the generative AI tools offered by software company Adobe. These differentiated themselves from competitors (such as OpenAI's ChatGPT) in that they were trained only on data created by their creators. If you have given your explicit consent.

data security

If you have a responsibility to protect your privacy, your data must also be kept secure. You can have all the consent in the world when collecting data, but if you can't protect it, you're letting your customers down when it comes to protecting their privacy. That's pretty irresponsible!

Data theft and breaches are always getting bigger and more damaging. At the end of 2023, approximately 14 million people had confidential medical records stored. compromised Due to an attack on transcription service provider PJ&A.And nearly 9 million people were affected by ransomware attacks Targeting MCNA Dental.

In another incident, a hacker gained access Access feeds from more than 150,000 surveillance cameras collected by Verkada, the software company responsible for training facial recognition technology. The footage showed activities in prisons, hospitals, clinics, and private property.

Being responsible here means ensuring that security measures are up to the task of defending against today's most sophisticated attacks. It also predicts and prevents threats and attack vectors that may emerge tomorrow.

Personalization and privacy

One of the big promises of AI is more personalized products and services. I buy insurance that specifically covers my own needs and risks, rather than aligning myself with a group of people similar to me. Or a car that understands my own driving habits and my likes and dislikes when it comes to in-car entertainment and climate control.

While this sounds great, the customized experience obviously comes at the cost of privacy. This means companies collecting data for this purpose need to have a clear understanding of where to draw the line.

One way to approach this is with on-device (edge ​​computing) systems that process data without leaving it in the possession of the owner. These systems can be difficult to design and build because they must run within the relatively low-power environment of a user's smartphone or device rather than in a high-performance cloud data center. However, this is one way to handle privacy responsibly when providing personalized services.

You should also be careful not to get too personal. Customers can easily become “creepy” if they feel that the AI ​​knows too much about them. The key here is to understand what level of personalization is truly helpful to your users, and what crosses the line into being annoying.

Privacy by Design

Consent, security, and balancing the line between personalization and privacy violations are fundamental to building responsible, privacy-respecting AI. Getting it right requires a nuanced understanding of our customers' rights, feelings, and opinions, as well as our own processes and systems.

Getting it wrong can undermine users' trust in AI-enabled products and services, ultimately hurting their chances of realizing their potential.

I have no doubt that there will be many positives and negatives as companies anticipate and adapt to society's changing standards and expectations. The law has a role to play, and we have taken the following steps toward this end: EU AI law. But in the end, it's up to the people who develop and sell these tools, not just us, the users, to define what it means to be responsible in a fast-paced world of AI. .