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How AI Could Help Solve The Privacy Problems It Has Created
It is no secret that privacy issues and concerns sit at the forefront of business actions, online activity, and government decisions. For example, artificial intelligence (AI) is now used in several of the applications that drive the digital workplace. This is why many enterprise managers are starting to question the implications and ramifications this will have for privacy. And this is not merely speculation; privacy issues stemming from the use of AI raise serious concerns for businesses and consumers.
Privacy issues also arise in response to the data breaches, scandals, as well as personal data leaks that have considerably eroded confidence in information technology and information systems.
Did you know that separately, tech giants, such as Google and Apple, have been the subject of reports that uncovered the potential misuse of voice recordings collected to enhance assistants like Google Assistant and Siri?
And that is not all; in April, Bloomberg also revealed that Amazon hires contract workers in order to annotate several thousands of hours of audio from many Alexa-powered devices. This prompted the company to quickly roll out user-facing tools that can delete cloud-stored data.
As you can see, finding enough data is one of the constant problems for many enterprises. And the unending quest to gather data to train and improve AI software has sometimes led many companies and organizations into the ethically-dubious territory. Many collect and use consumers’ sensitive information without clear and explicit consent.
You should know that substantial research indicates exactly how deep artificial intelligence has dug into the technology that’s in place to protect and secure customers and application users’ privacy.
For example, according to the Gartner Security and Risk Survey in 2019, by 2023, more than 40 percent of privacy compliance technology and systems will rely on AI, up from 5 percent in 2019.
This is why privacy leaders and chief information officers are under constant pressure to make sure that all personal data that their company’s process is brought in scope and under control. However, it is worth noting that this is difficult and expensive to achieve without technology aid.
AI in Privacy
So, what role will artificial intelligence play in privacy? Note that there are many areas where we’ll see AI taking a pivotal role in privacy as well as data governance, both now and in the coming years.
How can AI Help
Privacy and compliance officers can use AI to mitigate many privacy problems. For example, a Verizon’s Data Breach Investigations Report shows that about 52 percent of data breaches and incidents involve hacking.
You may know that most existing methods and techniques to detect hacking and cyberattacks rely heavily on patterns. It is worth noting that these techniques and methods can flag suspicious activity by carefully studying and analyzing previous attacks and breaches and identifying how the hacker or attacker’s behavior and patterns deviate from the norm.
Did you know that it is the type of thing that AI excels in: studying and reviewing existing information in order to recognize similar patterns and trends in new data?
It is also possible for developers to minimize privacy issues and challenges in the development stage before production. And this way, companies can still realize the many technological benefits of artificial intelligence without infringing on an individual’s privacy.
And to help improve privacy, it is best to add AI to your company’s data governance strategy and assign resources not only to AI product development but also to AI privacy, monitoring, and security, to get the best results.
Use Good Data Hygiene
Your company should only collect the data types needed to create the AI and keep the data secure. It is also essential to only maintain it for as long as is required to accomplish the purpose.
Use Good Data Sets
It is crucial for developers to build AI using fair, accurate, and representative data sets. And where possible, these professionals should develop AI algorithms that can audit as well as ensure the overall quality of other algorithms.
Also, note that AI bots can offer a “privacy concierge” function. This is where they can recognize, route as well as service privacy data requests considerably faster and more affordably than humans.
This is quite similar to how other artificial intelligence bots handle increasingly complex and sophisticated requests today.
Another excellent way that AI may help mitigate privacy issues and concerns is by preserving and improving data privacy when the models are being developed. Did you know that one promising and effective development is known as federated learning? Note that Google leverages in its Gboard smart keyboard in order to predict which word should be typed next.
You should know that federated learning develops a final deep neural network using data stored on several different devices, like cellphones, instead of a single central data repository. As you can see, the main benefit of using federated learning is that the original consumer data never leaves the local devices. This helps protect privacy to some degree.
However, no technique or method is without its flaws; and federated learning usually requires regular communication among several nodes during the learning process.
This means that for machine learning models to easily exchange parameters, they require significant amounts of memory and processing power.
Managing Sensitive Data
Did you know that AI can also play an important role in handling sensitive data? This is especially true for tasks in which confidential or sensitive data may get exposed to a human operator needlessly.
For instance, this is applicable to routing requests for medical and healthcare records between various providers where there’s a need to aggregate data but also a desire to offer an additional layer of privacy. This means that it is possible to use AI in the near future to handle considerably larger amounts of sensitive consumer data in ways that eliminate humans from the equation, thus simplifying the process of keeping the data secure.
It is crucial for the algorithms we use to be trained on the best available datasets and to do this in a way that best protects the privacy of individuals. And the successful future of artificial intelligence requires us to rethink and reconsider our approach to data protection.
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