AI, which stands for artificial intelligence, is a technological advancement where machines or robots mimic human intelligence to carry out tasks. As more and more online retailers, streaming services, and healthcare systems adopt AI technology, many people have likely experienced some form of it without even knowing.
While AI is still a relatively new technology, its impact has been swift. It makes shopping simpler, healthcare smarter, and daily life more convenient. Businesses are also recognizing its benefits: Nearly 80% of company executives say they’re deploying AI and seeing value from it.
Recently, AI has come up in discussions about cybersecurity, information, and data privacy. This guide will dive deeper into how AI is affecting data privacy and how it can be protected.
What Privacy Issues Arise from AI?
Although AI technology has many benefits for businesses and consumers, it also gives rise to several data privacy issues. The most visible ones are:
Data Exploitation
The big draw of AI is its ability to gather and analyze massive quantities of data from different sources to increase information gathering for its users, but that comes with drawbacks. Many people don’t realize the products, devices, and networks they use every day have features that complicate data privacy or make them vulnerable to data exploitation by third parties. In some cases, the data collection performed on these systems, including personal data, can be exploited by businesses to gain marketing insights, which they then utilize for customer engagement or sell to other companies.
Identification and Tracking
Some AI applications, such as self-driving cars, can track one’s location and driving habits to help the car understand its surroundings and act accordingly. While this technology can help make cars safer and smarter, it also opens more opportunities for his/her personal information to become part of a larger data set that can be tracked across different devices in his/her home, work, or public spaces.
Inaccuracies and Biases
Facial recognition has become a widely adopted AI application used in law enforcement to help identify criminals in public spaces and crowds. But like any AI technology, it provides no guarantee of accurate results. In some instances, this technology has led to discriminatory or biased outcomes and errors that have been shown to disproportionally affect certain groups of people.
Prediction
AI can use machine-learning algorithms to assume what information you want to see on the internet and social media —and then serve up information based on that assumption. You may notice this when you receive personalized Google search results or a personalized Facebook newsfeed. This is also known as a “filter bubble”. The potential issue with filter bubbles is that someone might get less contact with contradicting viewpoints, which could cause them to become intellectually isolated.
Vulnerability to Attacks
While AI has been shown to improve security, it can also make it easier for cybercriminals to penetrate systems with no human intervention. According to a recent report, the impact of AI on cybersecurity will likely expand the threat landscape and introduce new threats, which could cause significant damage to organizations that don’t have adequate cybersecurity measures in place.
Is this type of Data Collection Legal?
Data collection, in most cases, is legal. In fact, in some developed countries, like The United States, there is no holistic federal legal standard for privacy protection of the internet or apps. Some governmental standards concerning privacy rights have begun to be implemented at the state level, however. As an example, one can see the Consumer Privacy Act, that requires businesses to notify users of what type of information is being gathered, provide a method for users to opt out of some portions of the data collection, control whether their data can be sold or not, and not discriminate against the user for doing so. The European Union also has a similar law known as the General Data Protection Regulation (GDPR).
These laws have required companies to provide more transparency about the way they collect, store, and share one’s information with third parties.
The lack of holistic regulations does not mean that every company out there is unconcerned about data privacy. Some large companies, including Google and Amazon, have recently begun to lobby for updated internet regulations, which would ideally address data privacy in some way. While the methods for the protection of data security that could be implemented as part of such an undertaking are unclear, data privacy is a topic that will continue to affect us all now and into the future.
How is Digital Privacy
Protected?
Both organizations and individuals can do their part to protect digital data privacy. For organizations, that starts with having the right security systems in place, hiring the right experts to manage them, and following data privacy laws. Here are some other general data protection strategies to help enhance one’s data privacy:
Anonymous Networks
One way one can protect his/her digital privacy is to use anonymous networks and search engines that use aggressive data security while browsing online. Freenet, I2P, and TOR are some examples. These anonymous networks use end-to-end encryption so that the data one sends or receives can’t be tapped into. Another option is to use Duckduckgo, which is a search engine dedicated to preventing you from being tracked online. Unlike most other search engines, Duckduckgo does not collect, share or store one’s personal information.
Encryption
Most legitimate websites use what’s called “secure sockets layer” (SSL), which is a form of encrypting data when it’s being sent to and from a website. This keeps attackers from accessing that private data. Look for the padlock icon in the URL bar and the “s” in the “https://” to make sure one is conducting secure, encrypted transactions online.
Open-Source Web Browsers and Operating Systems
It’s important to choose web browsers that are open-source, such as Firefox, Chrome, or Brave. These browsers can be audited for security vulnerabilities, making them more secure against hackers and browser hijackers.
Consider an Android Cellphone
Unlike Microsoft or Apple phones, Android smartphones use open-source software that doesn’t require one’s data for functionality. Therefore, many experts believe an Android phone comes with fewer privacy risks.
Stronger Security Systems
As AI advances, organizations need stronger security systems and more cybersecurity professionals to maintain those systems. For this reason, jobs in IT, data management, and data science are in demand like never before. If one is interested in being part of a security team that protects organizations and their data, getting an online degree in cybersecurity or computer science can put one on the right path.
Even with the best protections, a data breach can still happen. So it’s important to be cautious about what information one is sharing online or on the internet and use secure passwords that are unique for each website that one chooses to share his/her information with. In the event of a data breach, this can minimize the amount of sensitive information that is exposed.
Moreover, in the digital age, algorithms play an increasingly prominent role in shaping our lives. From personalized recommendations on streaming platforms to targeted advertising and even critical decision-making processes, algorithms have become ubiquitous. They rely on vast amounts of data to make predictions and automate tasks, offering numerous benefits to individuals and businesses. However, the rise of algorithms has also raised concerns about the potential infringement on individual rights and the need to strike a delicate balance between data utilization and privacy protection. This article explores the challenges and possible solutions to achieving this equilibrium.
The Power of Algorithms
Algorithms are powerful tools that enable organizations to process and analyze massive datasets, extract valuable insights and make informed decisions. They have revolutionized various industries, including finance, healthcare, and marketing. By leveraging machine learning and artificial intelligence, algorithms can identify patterns, predict outcomes, and optimize processes. This has led to enhanced efficiency, cost savings, and improved user experiences. For instance, recommendation algorithms on e-commerce platforms can suggest products tailored to individual preferences, enhancing customer satisfaction and driving sales.
Data Utilization: The Double-Edged Sword
While the utilization of data and algorithms offers undeniable benefits, it also raises concerns about privacy, discrimination, and the potential erosion of individual rights. The vast amount of personal data collected from individuals, such as their online behaviour, preferences, and even biometric information, has become a valuable commodity. This raises questions about consent, data ownership, and the potential for abuse. Moreover, algorithms are not immune to biases present in the data they are trained on, which can perpetuate or even amplify existing societal inequalities.
See page-11
>>From page–
Preserving Individual Rights
Protecting individual rights in the age of algorithms is crucial to preventing undue influence and harm. Several key principles should be considered:
• Informed Consent: Individuals must have the right to know what data is collected, how it will be used, and the potential consequences. Transparent and understandable privacy policies are essential, ensuring that individuals can make informed decisions about sharing their data.
• Data Minimization: Organizations should collect and retain only the necessary data to achieve their intended purposes. Minimizing data collection can reduce the risk of potential harm and privacy breaches.
• Anonymization and De-identification: Personal data should be properly anonymized or de-identified to protect individuals’ privacy. Removing identifying information makes it more challenging to link data to specific individuals, reducing the risk of re-identification.
• Algorithmic Transparency: The inner workings of algorithms should be made more transparent to external scrutiny. This allows for better understanding, accountability, and the identification of potential biases or discriminatory outcomes.
• Fairness and Accountability: Algorithms should be designed and regularly audited to ensure fairness, accuracy, and accountability. This includes addressing biases in training data, regularly testing for discriminatory outcomes, and providing mechanisms for individuals to appeal or challenge algorithmic decisions.
Regulatory Frameworks and Ethical Guidelines
Regulatory frameworks and ethical guidelines are necessary to strike an appropriate balance between data utilization and individual rights. Governments and regulatory bodies should establish clear laws and regulations that safeguard individuals’ privacy rights and ensure algorithmic accountability. These regulations should be designed to keep pace with technological advancements and be adaptable to changing circumstances.
In addition to legal measures, industry-wide ethical guidelines should be developed. These guidelines can encourage responsible data practices, promote algorithmic transparency, and provide mechanisms for independent audits and certifications. Organizations should be encouraged to adopt these voluntary standards, fostering a culture of responsible data utilization and respecting individual rights.
Education and Empowerment
To navigate the challenges of the age of algorithms, individuals must be educated and empowered. Public awareness campaigns, educational programs, and accessible resources can help individuals understand the implications of sharing their data and make informed decisions. Digital literacy should be prioritized, enabling individuals to protect their privacy rights, identify potential biases, and demand accountability from organizations utilizing algorithms.
In sum, the age of algorithms presents immense opportunities for innovation, efficiency, and personalization. However, it also demands careful consideration of individual rights and privacy protection. Balancing data utilization and individual rights requires a multi-faceted approach involving legal frameworks, ethical guidelines, and education. By prioritizing informed consent, data minimization, algorithmic transparency, fairness, and accountability, we can strive to harness the power of algorithms while preserving the fundamental rights of individuals in the digital age.
Reference: https://www.wgu.edu/blog/
