The ability to control the information one reveals about oneself over the internet and who can access that information has become a growing concern. These concerns include whether email can be stored or read by third parties without consent or whether third parties can continue to track the websites that someone visited. Another concern is whether websites one visits can collect, store, and possibly share personally identifiable information about users.

The advent of various search engines and the use of data mining created a capability for data about individuals to be collected and combined from a wide variety of sources very easily. AI facilitated creating inferential information about individuals and groups based on such enormous amounts of collected data, transforming the information economy.

The FTC has provided a set of guidelines that represent widely accepted concepts concerning fair information practices in an electronic marketplace, called the Fair Information Practice Principles. But these have been critiqued for their insufficiency in the context of AI-enabled inferential information. On the internet many users give away a lot of information about themselves:

Unencrypted emails can be read by the administrators of an e-mail server if the connection is not encrypted (no TLS), and also the internet service provider and other parties sniffing the network traffic of that connection are able to know the contents. The same applies to any kind of traffic generated on the Internet, including web browsing, instant messaging, and others.

In order not to give away too much personal information, emails can be encrypted and browsing of webpages as well as other online activities can be done anonymously via anonymizers, or by open source distributed anonymizers, so-called mix networks. Nym and I2P are examples of well-known mix nets.

With social media and e-commerce sites being used more frequently, there are more potential openings for stealing consumer’s data. Companies can see which types of products consumers like to purchase and can use targeted ads to try to make people purchase more items thinking that this is what they will want to purchase. However, sometimes this type of data is used without explicit consent.

Users are unaware of all of the personal information that is collected about them. Cookies track browsing data and location settings show where a person is based out of, and can show shops or products that are physically located near someone. These combined that be a big safety and privacy issue for users if their data is not being stored safely.

With laws like the California Consumer Privacy Act (CCPA), people’s data can be protected and they asked for explicit consent before using said data.^[20] Globally, many nations are trying to implement similar clauses to protect consumers. Email is not the only internet content with privacy concerns. In an age where increasing amounts of information are online, social networking sites pose additional privacy challenges.

People may be tagged in photos or have valuable information exposed about themselves either by choice or unexpectedly by others, referred to as participatory surveillance. Data about location can also be accidentally published, for example, when someone posts a picture with a store as a background. Caution should be exercised when posting information online. Social networks vary in what they allow users to make private and what remains publicly accessible.

Without strong security settings in place and careful attention to what remains public, a person can be profiled by searching for and collecting disparate pieces of information, leading to cases of cyberstalking or reputation damage. Cookies are used on websites so that users may allow the website to retrieve some information from the user’s internet, but they usually do not mention what the data being retrieved is.

In 2018, the General Data Protection Regulation (GDPR) passed a regulation that forces websites to visibly disclose to consumers their information privacy practices, referred to as cookie notices. This was issued to give consumers the choice of what information about their behavior they consent to letting websites track; however, its effectiveness is controversial.

Some websites may engage in deceptive practices such as placing cookie notices in places on the page that are not visible or only giving consumers notice that their information is being tracked but not allowing them to change their privacy settings. Apps like Instagram and Facebook collect user data for a personalized app experience; however, they track user activity on other apps, which jeopardizes users’ privacy and data.

By controlling how visible these cookie notices are, companies can discreetly collect data, giving them more power over consumers. Artificial intelligence can be seen as a hindrance to protecting information privacy as they collect data widely. According to the International Association of Privacy Professionals, about 68% of consumers globally express concern about their privacy online with 57% agreeing that AI can be a threat to their data.

These concerns have intensified as generative AI tools, which learn from data scraped from the web, have become more widely adopted. AI privacy concerns can be linked to unregulated data collection methods, opaque algorithms, and data persistence. Algorithmic opacity means not understanding exactly how and where AI is getting their data and sources from. The lack of clear visibility can make it difficult for someone to understand how their information is being found and used.

Data persistence is data existing for an extended period of time online that can also be without consent. As of now in the United States there are not any explicit federal laws governing AI in terms of data collection. Laws such as the Health Insurance Portability and Accountability Act (HIPAA) and Gramm Leach Bliley Act can regulate companies but it excludes AI. There are state legislatures being enacted. The state of Utah in the United States passed the Artificial Intelligence Policy Act in March of 2024.

The White House Office of Science and Technology Policy created the “Blueprint for an AI Bill of Rights” in 2022 which explained frameworks for data privacy and AI and having AI systems collect user consent prior to using their data. Many researchers have created additional frameworks to address AI and data privacy including data minimization requirements, auditing of AI, and giving users an option to opt out of data collection when using AI.