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Impact Of Artificial Intelligence On Data Privacy

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By: Gabriel Schram

November 27, 2020

Online data has become an increasingly valuable asset in the current state of technological advancement. Private data is seemingly leaked at every turn with little to no regulation regarding its collection, and features of new applications and products seem more like vulnerabilities. The magnitude of available data and capability for data storage has paved the way for advancing and widening the distribution of artificial intelligence (AI). AI has completely changed the way that information is taken in and processed. The daily lives of technology users have come to use AI regularly, whether they know it or not. The scope of AI has expanded to include user data.

AI has kindled innovation in transportation, health and medicine, marketing, agriculture, education, cybersecurity, and public services. However, the cost of this innovation is a drastically altered threat landscape in cyberspace. The new threat landscape incorporates private data collection on internet users. A better understanding of this impact can be explained by defining AI, examining how it is being used to collect data, and what the collected data is being used.

What is Artificial Intelligence?

Artificial Intelligence makes it possible for computers to learn from and recognize data. AI allows computers to carry out complex tasks, respond to stimuli, and make decisions that a human would otherwise make. Darrell West (2018) has a strong definition of artificial intelligence, defining it as "machines that respond to stimulation consistent with traditional responses from humans, given the human capacity for contemplation, judgment, and intention."

AI has completely revolutionized the way that people interact with each other and technology. The amount of data at its disposal directly affects the effectiveness of AI. However, AI is also capable of storing data for future decisions. Although the term "Artificial Intelligence" started being used in 1956, its resurgence is greatly due to today's advanced data collection and storage capability.

Machine Learning (ML) is a subset of Artificial Intelligence. ML encompasses the algorithms that allow computers to improve processes and decision making with the gaining of information. These algorithms act as a set of instructions for AI programs and adjust to new inputs. Deep Learning (DL) stems from ML and consists of multiple processing layers that recognize speech, images and can be used to make predictions.

AI has made way for some of the most advanced innovations that technology has to offer. Most of us interact with AI regularly. This is because industries across the spectrum make use of AI in their system processes.

How does AI Contribute to Data Collection?

The collection of data is greatly done by using devices and applications that have quickly become necessary to thrive in the industry and everyday life. Technologies such as smartphones, smart cars, fitness trackers, and many other smart home devices have become widely used and depended on. Statista estimates 275.66 million active smartphone users in the US in 2020; they predict this number to increase in the coming years (2020). All the listed devices provide a type of data as output or leak data as a part of their regular use.

Major online platforms share their users' data with designated third parties, particularly advertisers. Consumers' spending and web browsing habits are tracked using AI so specific ads can be pushed; better suggestions can be made, and provide continued business likeness. In addition to spending and web browsing habits, other popular applications track users' location, who they talk to, where they work, their interests, daily routines, and other personally identifiable information. All of this data is collected and analyzed with the use of AI-based tools and algorithms.



What is Collected Data Used For?

Data being collected provides users with better suggestions for content browsing and online shopping habits. More critically, local authorities can use location data to use amber alerts and other emergency notifications better. The uses for collected data are growing in innovation before the eyes of everyday users. For example, social platforms use AI to identify fake accounts, companies develop ML-based bots for potential clients to chat with, and games use this technology to create opponents.

Large amounts of data being collected have become a business for online platforms. Surveillance companies are turning to AI-based initiatives for the mass collection of user data. This type of technology is then sold to foreign governments, police departments, federal agencies, and other third-party customers. This model has proven to be effective with the Chinese surveillance system Skynet.

Final Thoughts

AI is making a significant impact on data privacy. The enhanced ability to store and collect data has led to a drastic increase in the use of AI. Major companies are taking advantage of this capability by collecting massive amounts of private and public data; this is working to their benefit. With very little regulation on this data collection, companies will continue to increase their use of AI in private data collection. Smart devices have become a societal norm and have led to a boom of data being exposed. Smart devices leak user information, and the result is a market for what is referred to as big data. This trend is expected to continue with a dramatic increase in user activity as a side-effect of COVID-19.

AI in cybersecurity has further contributed to the protection of users' data. Specifically, it is being used to monitor and respond in real-time to incorrect use or data theft. Moreover, AI-based privacy tools are being developed to evaluate encrypted data and alert users of malicious websites.

There are still capabilities to be discovered with AI, and current policy and legislation don't even cover the current capabilities. The overall impact of AI on data privacy is yet to be determined. User data is being collected so willingly and being used in increasingly varied ways. The danger is that much of this leaked data seems irreversible. Once AI makes this impact, the only option is to continue forward.

References

Statista. (2019). Number of smartphone users in the united states from 2018 to 2024 (in millions)*. Retrieved from https://www.statista.com/statistics/201182/forecast-of-smartphone-users-in-the-us/#:~:text=This%20statistic%20shows%20the%20number,estimated%20to%20reach%20275.66%20million.&text=Advances%20in%20telecommunication%20technology%20have%20been%20significant%20in%20recent%20years. West, D. (2018). What is artificial intelligence? Retrieved from https://www.brookings.edu/research/what-is-artificial-intelligence/

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