Don’t Take A Risk With Your Digital Privacy In Today’s AI Operated World!


The US has become safer with AI thanks to President Biden’s Executive Order, which tells government departments to focus on safe AI development. At the same time, the EU is almost done passing the AI Act. This will make it harder to use AI technologies in Europe without following more rules. These new changes are part of a bigger trend around the world to make AI rules stricter.

Our goal is to find a middle ground between progress in technology and worries about privacy and morals. Let’s talk about how to make sure your business follows the rules and uses AI properly.

AI Privacy Concerns

1. Data Misuse and Lack of Consent

In 2023, the Pew Research Centre did a study and found that 72% of Americans are worried about how companies collect and use them. An important part of AI privacy issues is that people often abuse data. AI needs a lot of information to learn and get better. But it’s not always clear how this information is received. Most of the time, users’ personal information is gathered without their clear permission or understanding.

Someone would be taking down things about your life in secret, like where you shop, what you like, and what you look for online, to make a profile about you. This is not only a breach of privacy, but also a breach of trust. People should be able to see what information is being collected about them and choose not to have it taken.

2. Enhanced Surveillance Capabilities

Face recognition is going to be a $9.8 billion business by 2025. Things like face recognition and walking analysis make it possible to always keep an eye on people. This is true everywhere, not just in high-security areas. It’s also true on the street and in shopping stores. Someone looks at, thinks about, and writes down everything you do all the time. This level of spying could be used by governments or businesses to keep an eye on and control people, which is a very big problem for privacy and freedom.

In Today’s AI Race, Don’t Gamble with Your Digital Privacy

3. Profiling and Discrimination

AI can be biased, which is a sad fact. If data shows how biased the system is given to AI systems, they might strengthen bias without meaning to. This might look like AI that hires people of a certain race or gender more often or credit score algorithms that are unfairly harsh on people from certain social groups. A lot of the time, people don’t know that their information is being used to judge them unfairly, which can harm them in real life.

4. Opacity and Lack of Control

AI systems can be hard to understand at times, like black boxes. A big privacy worry is that these systems don’t make it clear what they do or how they work. People don’t always know how or why their information is being used. People who don’t know about or control personal info are scary. Because of how an AI system works behind the scenes, you might not know why you were turned down for a loan or stopped at the airport.

Strategies to Mitigate Privacy Risks Associated With AI

We know that privacy laws like the CCPA in California and GDPR in Europe are very important. In the world of AI, we can do more to keep personal data safe, though. These are some good ways to do it.

1. Develop A Comprehensive AI Use Policy

The first step is to make clear rules about how AI can be used in the company. It should be easy to understand what is and isn’t allowed in this policy, with a focus on privacy, data protection, and smart use. It will help everyone know what they need to do and what they can’t do when they work with AI. This rule should cover:

  • AI data is collected, saved, viewed, and kept safe. Data governance is the process of data governance.
  • Model explainability means making sure that it is easy to see and understand how AI models decide what to do.
  • AI systems need to get informed and useful permission from users before they can collect and use their data.
  • To handle risk, you have to look for and lower the privacy risks that different AI projects might pose.

In Today’s AI Race, Don’t Gamble with Your Digital Privacy

2. Conduct Privacy Impact Assessments (PIAs)

PIAs are your best friend in this case, and you need them to find private problems that might arise with AI projects. Every so often, doing PIAs can help you find privacy issues before they become real ones. When you plan a project that will involve personal data, do these checks. Then, keep going back to them as the project changes.

There are privacy risks at every step of the way information is collected, handled, stored, and thrown away. This is what a PIA does. Also, it’s important to think about why and how you should handle data and make sure that you only use the bare minimum of data to reach the project’s goals.

3. Ensure Transparency and Consent

It’s important to be open. People who use AI systems should be told clearly and honestly what kind of data is being collected and how it will be used. Don’t use scientific terms when putting this information together; make it simple for everyone to understand. Notifying the person about the risks is also very important. When it comes to their data, your customers should be able to make an informed choice, such as whether to opt in or opt out of data collection methods.

  • Put your money into AI that can be explained (XAI): To figure out how AI models decide what to do, use XAI methods. We will be able to see choices better and hold AI models more responsible for any bias that might be built into their algorithms.
  • Tell the truth when you talk: Be honest about how AI systems are used, what effects they might have, and what their limits are. Just be careful not to hurt real business interests.

4. Implement Robust Data Security Measures

The info that AI systems use needs to be kept safe. A lot of work needs to go into making sure that personal data is kept safe from people who shouldn’t be able to see it, share it, change it, or delete it. This means encrypting data, setting up strong access controls, and making sure that security measures are always up to date so they can handle new threats.

  • To do regular security checks, you should hire outside security experts to do vulnerability studies and penetration tests. This will help you find any weak spots in your barriers and fix them.
  • Stay alert: always keep an eye out for new online threats and holes. Sign up for security tips and updates to stay up to date and make the changes you need to make to your security.
  • You must follow the rules: Laws like GDPR and CCPA say that you must follow certain steps to keep data safe. Compliance not only keeps you out of trouble with the law, but it also shows that you care about handling data properly.

Data Sharing with Third-parties

The fact that Google shares information with outside groups doesn’t make it clear if the people who read chats are Google workers or hired from outside the company. People in this field often hire outside firms to do this kind of work.

In Today’s AI Race, Don’t Gamble with Your Digital Privacy

On the other hand, OpenAI says, “We share content with a small group of trusted service providers who help us run our business.” We only share the information we need to reach our goal, and our service providers are required by law to protect this information and keep it secret.

There is no way to find out who looked at or processed the data at OpenAI. It is made clear that both its own reviewers and trusted third-party service providers do this. The company doesn’t share information with outsiders either, and talks aren’t used to sell anything. Google also says that this isn’t how ads are shown in talks. Google will let people know if this changes in the future, though.

Risks of Personal Data in Training Dataset

There are many risks when personal data is included in the training collection. First, it breaks people’s privacy because their personal information shouldn’t have been used to train models without their clear permission. This can be very annoying if the service provider doesn’t make it clear what their privacy rules are.

Also, the most common risk is that private information will be lost or stolen. The company told its employees they couldn’t use ChatGPT last year because it leaked private business data. The information is kept private, but there are still ways to get the AI model to give up private information.

Finally, data poisoning is a real danger. Attackers could change the model’s results by adding bad data to conversations, according to researchers. It can also add harmful biases that could make AI models less safe. One of the people who helped start OpenAI, Andrej Karpathy, has written a very detailed description of data poisoning here.


Instead, you can turn off chat logs as a first step towards leaving less of a digital trail. There is a private portal page for ChatGPT where you can see your chat history and choose not to be trained as a model. Also, if you really value your privacy, you can run LLMs (large language models) on your own computer.

Many open-source models can run on Windows, macOS, and Linux, even on computers that aren’t too expensive. On our site, you can find a full guide on how to run an LLM on your own computer. You can also use your own computer to run Google’s Little Gemma project. If you want to add your own private files, you can also check out PrivateGPT, which is software that you can run on your computer.

Companies are trying to get data from all over the internet and even make their own data in the race to be the first to use AI. We are responsible for keeping our private data safe. People should not give personal information to AI services if they want to keep their privacy safe. AI firms should not give up useful features just to keep users private. They can live together.

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Moreover, you can also check out our detailed guide on Virbo vs Synthesia. Which AI Avatar Tool Should You Choose? or Snapchat My AI Update: Now Your Favorite Chatbot Can Set Reminders and Countdowns!

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