Artificial intelligence (AI) is the imitation of human intellect in computer systems that are capable of carrying out tasks that ordinarily require human intelligence, such as speech recognition, visual perception, and problem-solving. AI systems can complete complicated tasks without explicit programming because they are built to learn from data, adapt to new inputs, and improve over time.

With its numerous uses across numerous industries, AI has made enormous strides in recent years, revolutionizing both our personal and professional lives.

The following are some well-known applications of AI:-

• Natural Language Processing (NLP): It enables machines to comprehend and produce human language. Chatbots and virtual assistants like Siri are excellent examples of NLP applications.
• Machine learning: Algorithms powered by AI enable systems to evaluate massive volumes of data and make predictions or judgments based on patterns and insights. This has uses in the financial, medical, and marketing sectors.
• Computer Vision: AI-enabled devices are now able to decipher visual data from pictures and movies. This is applied in surveillance technology, self-driving automobiles, and facial recognition systems.
• Robotics: AI-driven robotics entails the creation of devices that can autonomously carry out physical activities. Manufacturing, healthcare, and exploration all use robots.
• Personalisation and recommendation systems: AI algorithms examine user behavior to offer tailored product, service, and content suggestions. Platforms like Netflix, Amazon, and social media feeds all make this clear.
• Healthcare: By assisting in disease diagnosis, drug discovery, and customized treatment strategies, AI is changing healthcare. It improves medical imaging and helps medical practitioners make wiser choices.

 History of Artificial intelligence

Thousands of years ago, when ancient philosophers were debating matters of life and death, the concept of “artificial intelligence” first emerged. In ancient times, inventors made things called “automatons” which were mechanical and moved independently of human intervention. The word “automaton” comes from ancient Greek, and means “acting of one’s own will.”One of the earliest accounts of an automaton dates back to 400 BCE and mentions a mechanical pigeon built by a Plato buddy. One of the most well-known automatons was built by Leonardo da Vinci around the year 1495, many years later.

Citation- “What Is the History of Artificial Intelligence (AI)?” Tableau, http://www.tableau.com/data-insights/ai/history. Accessed 6 Aug. 2023.“What Is the History of Artificial Intelligence (AI)?” Tableau, http://www.tableau.com/data-insights/ai/history. Accessed 6 Aug. 2023.

Right to privacy

Legally speaking, numerous international accords and legislation acknowledge and defend the right to privacy. In Article 12 of the 1948-adopted Universal Declaration of Human Rights (UDHR), it is stated that “no one shall be subjected to arbitrary interference with his privacy.” Similar to this, Article 17 of the International Covenant on Civil and Political Rights (ICCPR) reiterates the importance of private rights.

Hence, International agreements like the Universal Declaration of Human Rights and the International Covenant on Civil and Political Rights acknowledge the right to privacy as a fundamental human right that shields people from illegal access to their personal information and activities.

Legislation like the GDPR and national privacy legislation like the California Consumer Privacy Act further protect this right. From an ethical standpoint, privacy is essential for preserving people’s autonomy, independence, and sense of dignity by allowing them to express themselves freely without worrying about being watched. However, there are issues with the expanding use of AI systems that gather and interpret enormous volumes of data. It’s critical to strike a balance between AI development and privacy protection, which calls for responsible behavior and careful thought on the parts of policymakers, corporations, and society as a whole.

History of right to privacy

The Indian Supreme Court with nine-judge bench under JS Khehar, ruled on 24 August 2017, that the right to privacy is a fundamental right for Indian citizens per Article 21 of the Constitution and additionally under Part III rights. The court specifically adopted the three criteria that must be met before any Article 21 right can be infringed upon: legality (i.e., through an existing law); necessity (i.e., a legitimate state objective); and proportionality (i.e., a rational connection between the invasion’s intended goal and the methods used to achieve it).

Citation- “Right to Privacy – Wikipedia.” Right to Privacy – Wikipedia, 1 June 2013, en.m.wikipedia.org/wiki/Right_to_privacy.

AI and Data Collection

Huge volumes of data are crucial for AI systems to learn from and improve upon. The AI system is fed with a variety of representative data during this procedure, known as “training data,” to enable it to identify patterns and make precise predictions. The AI’s decision-making abilities get more honed and potent the more high-quality data it has access to.

There are many ways to get data, and the following are some of the main sources:

• Cameras and Image Data: AI-powered computer vision systems evaluate visual information using image data from cameras. Applications for this include surveillance, object detection, and facial recognition.
• Social media platforms: User-generated data from posts, comments, likes, shares, and interactions is gathered in massive quantities by social media platforms. In order to comprehend user preferences and habits, AI systems examine this data.
• Online Activity: AI systems monitor and examine users’ online activity, including search history, website and app interactions, and browsing history. Targeted advertising and customised recommendations are made using this data.
• Biometric Information: For the purposes of identification and authentication, AI can process biometric information such as fingerprints, facial features, and speech patterns.
• Medical Imaging and Genetic Data: Patient records, medical imaging, and genetic data are used by AI applications in healthcare to support diagnosis, treatment planning, and medical research.

AI privacy concerns:

The ways AI uses to collect data present serious privacy concerns, such as facial recognition software surveillance, possible data breaches that could result in identity theft, biased profiling and discrimination, a lack of informed consent, and the secondary use of data without user knowledge.

Concerns about healthcare privacy as well as a lack of accountability and transparency in automated decision-making are also significant problems. These difficulties are made more difficult by the malicious use of personal information.

Strong rules, open AI systems, and user empowerment are necessary for privacy protection in the age of AI in order to strike a balance between advancing technology and preserving fundamental privacy rights.

AI and personalisation

Targeted adverts, content suggestions, and personalized services are just a few examples of how AI algorithms exploit personal data to generate personalized experiences in several facets of our lives. To deliver customized information and services, the process entails gathering and evaluating data from users’ interactions, habits, preferences, and historical activities.

How AI achieves customization is as follows:

By examining user data, artificial intelligence (AI) enables targeted advertising, content recommendations, and personalized services. To achieve a balance between customisation and privacy protection, however, these personalization efforts pose privacy issues that need to be addressed. Informed consent is required, as are data minimization, anonymization, and clear algorithms.

Personalization improves user convenience and pleasure, but it also creates privacy issues. To ensure that users’ rights are upheld, a balance between personalization and privacy protection must be struck.

Among the most important factors are:

• Consent: Before collecting and using a user’s personal information for customised experiences, businesses must get that person’s express, informed consent.
• Data minimization: To prevent the accumulating of unnecessary or irrelevant data, AI systems should only gather and store the data required for providing individualized experiences.
• Anonymisation and Aggregation: To preserve individual identities while allowing for individualized insights, personal data should, if possible, be anonymized or aggregated.
• Transparent Algorithms: Businesses should be open and honest about how their AI algorithms work and how they handle user data to personalize experiences.
• Data Security: To protect personal information from breaches and illegal access, strong data security measures must be in place.

Users should have access to, and be able to review, amend, and remove, their personal information and preferences.

• Ethics: When utilizing AI for personalisation, businesses should be aware of ethical issues, such as avoiding discriminatory behaviors.

AI and Privacy Laws:

In order to address the problems brought on by AI technology, it is essential to implement existing privacy laws and regulations. These regulations frequently place a strong emphasis on data protection, consent, accountability, and transparency.

• Data protection: Strict criteria for handling personal data are established by privacy regulations like GDPR to guard against unauthorized access, breaches, and abuse.
• Consent: Users’ informed consent is crucial in ensuring that they are aware of the objectives for which their data will be used and have the option to provide or withdraw consent.
• Fairness and Transparency: With consumers having access to their data and disclosure requirements for data collection and processing, transparency is prioritized.

Limiting the use of information for specific purposes is a common requirement of privacy regulations. This stops businesses from utilizing data for purposes except from those that were initially revealed to users.

• Data Minimization: It is suggested to gather and store only the minimum amount of personal data possible.
• Privacy Impact Assessments (PIAs): To evaluate potential privacy issues, privacy impact assessments (PIAs) may be required for emerging AI systems. While deploying AI responsibly, these policies seek to safeguard individuals’ data and privacy rights.

The rapid improvements in AI technology present problems for current privacy legislation despite these restrictions. Large-scale data processing by AI can result in complicated data interactions that may not be sufficiently covered by conventional consent processes. As AI develops, it becomes clear that privacy regulations need to be updated and modified to handle new issues.

AI Methods That Protect Privacy:

Differential privacy and federated learning are two successful methods that can be used to safeguard user data while yet enabling AI systems to learn from it.

• Differential Privacy: Before being analyzed, each data point is given noise through differential privacy. As a result, it is more difficult to distinguish individual data inside the aggregated dataset because no individual’s specific information is accessible.
• Federated Learning: Using federated learning, AI models can be locally trained on client computers or server computers without sending raw data to a centralized server. This strategy enables the model to gain knowledge from shared experience while maintaining the privacy of the data.
• Homomorphic Encryption: With homomorphic encryption, data can be handled without first being decrypted, guaranteeing anonymity even while calculations are being done.

These methods let AI systems utilise various data sources without directly accessing or disclosing private user data. Using AI techniques that protect privacy can increase user confidence and compliance with privacy laws.

AI and corporate responsibility:

Corporate responsibility in AI technology involves several crucial facets to ensure consumer privacy:

* Data Protection: Businesses must prioritize data protection and invest in robust security measures to safeguard user data from breaches and unauthorized access.

* Privacy by Design: AI systems should be developed with privacy in mind, incorporating privacy features and considerations from the very beginning of the design process.

* Transparency: Businesses should be transparent about their data acquisition, AI algorithms, and how user data is used for personalization and decision-making.

* Accountability: Companies must take responsibility for the decisions made by their AI systems and be prepared to explain and justify their actions.

* User Empowerment: Providing users with control over their data and clear options for managing consent and preferences is essential for maintaining user privacy.

* Ethical Standards: Companies should adopt ethical standards for the usage and development of AI to address potential biases and discriminatory actions.

By adhering to these principles, businesses can play a pivotal role in safeguarding consumer privacy and promoting the responsible and ethical use of AI technologies.

AI and surveillance:

Privacy rights are being questioned by AI-powered monitoring equipment like smart cameras. Among the problems these technologies cause include mass surveillance, a lack of permission, false positives, and biased algorithms. Strong regulation is necessary due to the risk of abuse and invasion of privacy. Clear objectives, openness, restrictions on data retention, informed consent, responsibility, and protection of biometric data should all be important components of regulation. Prudent and well-considered regulations are necessary to strike a balance between the advantages of AI-powered surveillance and safeguarding privacy and civil liberties.

AI and government surveillance:

AI-powered surveillance tools are being used more often by governments around the world for a range of objectives, including law enforcement, national security, and public safety. While these technologies can offer useful resources for crime prevention and investigation, they also present serious issues with the privacy rights of individuals.

The following are some possible effects on privacy:

• Mass surveillance: AI-powered surveillance systems are capable of continually monitoring enormous populations, which enables pervasive and intrusive monitoring of people’s daily activities.
• Facial recognition and identification: By combining surveillance cameras and facial recognition technology, it is possible to track and identify people in real time, possibly compromising privacy in public areas.
• Social and Political Control: AI surveillance’s massive data collecting capabilities can be used to track citizens’ actions, relationships, and political activity, which could lead to the repression of dissent and the violation of civil liberties.
• Discriminatory Acts: Biases in AI algorithms may lead to disproportionate surveillance of and targeting of particular demographic groups, which constitutes discriminatory acts.
• Lack of Oversight: Governments’ use of AI surveillance may not have enough checks and balances, which could result in abuses of authority and infringement of citizens’ private rights.

It is crucial to build strong legal frameworks and supervision procedures in order to stop abuse and preserve citizens’ privacy. To ensure that the use of AI surveillance technology complies with the principles of transparency, strict checks and balances should be in place.

• AI Ethics and Privacy: The moral and ethical issues surrounding the creation and application of AI technologies are at the center of AI ethics. The following ethical issues are related to privacy:
• Respect for Autonomy: Individuals ought to be allowed to decide how their personal information is used and make informed choices about it.
• Data privacy and security should be prioritized by AI developers and users, who should also take steps to protect sensitive data from unwanted access and breaches.
• Fairness and non-discrimination: AI algorithms ought to be created without prejudice or discrimination, guaranteeing that everyone is treated equally.
• Transparency: Users should be able to comprehend the reasoning behind AI algorithms’ judgments, and AI systems themselves should be transparent.

Informed Consent: Getting users’ informed consent for data collection and processing is crucial for preserving their right to privacy.

Accountability: Those who create and use AI systems, as well as the organizations that use them, should be held responsible for the results and effects of their work.

Privacy protection is being incorporated into AI design and development.

Future Obstacles and Their Solutions

• Several difficulties surrounding AI’s effect on privacy will probably emerge as it develops:
• Data Security and Breach Prevention: As AI systems are used more frequently for data processing and decision-making, data security and breach prevention are more important than ever.
• AI-powered Surveillance: To strike a balance between security and privacy, there must be strict rules and control due to the rise of AI surveillance technologies that could result in widespread privacy violations.
• Privacy Concerns with Biometric Data: The usage of biometric data, such as facial recognition, will bring up issues with the safeguarding of people’s unique identifiers and the possibility for abuse.
• AI in Healthcare: The application of AI in healthcare may give rise to privacy issues involving private genetic and medical data.

Conclusion:

The right to privacy must be protected at all costs in a future powered by artificial intelligence. Although AI technologies have the potential to positively alter many facets of society, they also create serious ethical and privacy concerns. Governments, businesses, and individuals must understand how crucial it is to protect privacy rights while utilizing the advantages of AI.

To guarantee that AI developments respect people’s right to privacy, effective checks and balances, privacy protection in AI development, and increasing transparency and accountability are crucial elements. By placing a higher priority on privacy, society may strike a balance between advancing technology and upholding fundamental human rights, paving the way for a time when AI is used ethically and responsibly for the benefit of all.

---

Author: Kashish Maggo

---