In the heart of the digital age, artificial intelligence (AI) it has crept into every crevice of our existence online. Suggestions buying custom filters, anti-spam, by the chatbot assistance to the sophisticated systems of monitoring of the network, the AI has become the architect is invisible to our digital experience. This ubiquitous interplay between AI and digital life raises, however, a series of questions urgent privacy. In this article, we will take a journey of exploration to discover the challenges and ethical dilemmas that emerge from the encounter between the unstoppable progress of the IA and the fundamental right to privacy, tracing the possible routes to navigate in this complex scenario, and continues to evolve.
IA and Data Collection: in An Era of always-on Connectivity
The engine of artificial intelligence, the vital sap that feeds the intellect and allows you to “learn”, it is the data. And in the digital era, we live in an era of always-on connectivity, in which we are constantly immersed in a continuous flow of information. Each of our online interaction, every click, every message, every search is recorded and potentially used by the systems of IA.
But as it happens, exactly, this collection of data? The methods are many and often subtle. When you browse a website, cookies track our activities, learning which pages you visit, which products you look at, how long we linger on a given item. Social media collect detailed information about our interests, our preferences, our connections, analyzing the posts that we publish the pages that follow, the interactions that we have with other users. The devices IoT (Internet of Things), including smart speaker or wearable device, record information on our location, our health, our daily habits.
This enormous amount of data can be grouped into different categories. There are location data, which reveals where we are at any given time. There are our preferences, expressed through the “likes” on social, online purchases, the content we see on streaming. There are our communications, such as emails that we send or messages that you exchange with our friends.
It is important to emphasize the extent of this data collection. This is not a collection of random and fragmentary, but a continuous and systematic, often centralized in a huge database. This centralization, if from one side it offers advantages to the training systems of IA powerful, on the other hand, raises deep concerns for privacy. If all of the information on our digital lives are concentrated in a single place, with the risk that they might be misused or fall into the wrong hands is extremely high.
In short, the era of AI is also the era of the collection of massive data, and this fact puts us in front of one of the ethical challenges the most important of our time: how to reconcile the technological innovation with respect for the privacy of the individual?
Key Technologies: Profiling, Surveillance and Recognition
The artificial intelligence has given rise to a practice that was both pervasive and delicate: the profiling. In simple words, the profiling is as a digital magnifier extremely powerful, able to analyze the traces that we leave behind us in our online lives and to build, starting from these tracks, a real “digital portrait” of who we are. The profiling systems operate by an impressive amount of data and the history of our purchases, the interactions that we have on social media, the web pages we visit, our movements, our likes, our research online... a continuous flow of information, processed by sophisticated algorithms, allow us to draw a detailed picture of our tastes, our habits, our preferences, and even, in some cases, our vulnerability.
This ability to “focus” our stretches digital has multiple applications. The profiling is widely used in advertising, introducing ads that are supposed to correspond to our interests. We find it is also used in credit scoring, where the AI analyzes financial data and behavior to evaluate our creditworthiness. And even in the processes of personnel selection, some systems use AI to sift through the curriculum and our online traces in search of the ideal candidate.
But this technology, so powerful, is not without risks. If used without due care, the profiling can open the door to practices that are highly problematic. The risk of discrimination it is always this: the algorithms, trained on data that reflect the social injustices that exist, can end up penalising certain groups of people, perpetuating the dynamics of exclusion. The manipulation is another threat: the profiles thus obtained can be used to influence our opinions and our choices, guiding us in a direction that we would not have spontaneously undertaken. And finally, there is the risk of restriction of the choices: profiling, presenting only the content and offerings, in line with our profile, you can close in on a bubble, allowing us to discover different points of view and expand our horizons. In essence, the profiling is a technology with enormous potential, but we must learn to use it wisely, balancing the benefits with the need to protect our rights and our freedom.
If the profiling is the magnifying glass of the IA, the automated surveillance can be thought of as a digital eye ever watchful, able to observe, record and interpret our behavior in ways that, until recently, belonged to the realm of science fiction. The automated surveillance is based on the ability of AI to analyze, in real time, a myriad of data from cameras, microphones, sensors, mobile devices and other sources, to track our movements, follow our interactions, and to predict and even our intentions.
The techniques of automated surveillance are varied and evolving. Facial recognition, for example, allows you to identify the people starting from the images of the surveillance cameras, opening scenarios, ranging from the monitoring of public places and access control in restricted areas. The behavioral analysis, however, concentrates on the interpretation of the actions and movements of people, looking for abnormalities or signs that could have predicted a suspicious behavior. And let's not forget the tracking systems of the location, and through our smartphones and other devices, know where we are in every moment.
The applications of these technologies are vast and varied. They are used in urban surveillance, to monitor the streets, parks and other public spaces, often with the justification of preventing crime and ensuring the safety of citizens. See them at work in the control of the employees, in some work environments, to verify their productivity or to prevent undesirable behaviors. And let's not forget their potential use in the context of airport security, to identify travelers at risk.
But, as we can easily guess, the automated surveillance brings with it a number of ethical risks of no small account. The violation of personal freedom is one of these: the awareness of being constantly observed can induce an effect chilling, inhibiting our spontaneity, limiting our freedom of expression and altering radically the way we behave. L’abuse of power is another real threat: the ability to oversee large scale can become an instrument of control in the hands of authoritarian regimes or organizations with goals that are not transparent. And let's not forget the the risk of errors: the systems of IA are not infallible, and their interpretations can be inaccurate or even wrong, with consequences that are potentially very serious for the people involved.
Ultimately, the automated surveillance is a powerful technology, but that is not neutral. Its use requires a public debate with breadth and depth, and a particular attention to safeguards ethical and legal requirements that must be put in place to protect our rights and our freedoms.
The artificial intelligence is not confined to observe our actions; some of its applications try to peer into a deep, trying to decipher our emotions. It is here that comes into play with recognition of the emotions, a technology that is ambitious and aims to identify and classify our emotional states from physiological signals, and behavioral.
But how do they work exactly these systems? They analyze a variety of data: the facial expressions captured by the cameras, the tone of voice, as recorded by the microphones, the rhythm of the words, the posture of the body, the physiological data collected from sensors (such as the heart rate or skin conductance), and even the content of the messages that we write. Complex algorithms seek then to correlate these signals with the emotions are considered to be “basic” (such as happiness, sadness, anger, fear, disgust, and surprise), to provide a “reading” of the emotional state of the individual.
The applications of this technology are many and potentially disruptive. Some companies are experimenting to analyze the reactions of consumers to the products and advertisements, measure the effectiveness of their marketing strategies. Others see it as a tool to improve the selection of staff, evaluating the “emotional competencies” of the candidates or to monitor the state of wellbeing of the students in the school. And there are proposals to use in the field of security, for example, to identify potential terrorists in airports.
However, the recognition of emotions is a technology that raises major ethical questions, related to:
- The the fragility of the foundations of science: The correlation between the physical signals and emotions is not always unambiguous and precise. The emotional states of human are complex and influenced by a myriad of factors in individual and cultural.
- The risk of inaccuracy and error of interpretation: Systems for the recognition of emotions can easily lead to false positives or false negatives, classifying incorrectly an expression or a mood.
- The potential manipulation: If these technologies were used to “read” our emotions in a hidden and non-consensual, may be used to influence our choices, our decisions, or our behavior.
- The breach of confidentiality: The in-depth analysis of the emotions of an individual can reveal information that is highly personal and sensitive, jeopardizing your privacy.
In conclusion, the recognition of emotions is a technological frontier that requires a particularly careful and responsible, able to balance the potential with the profound ethical implications.
The Framework of Ethics and Law: Rules, Principles and Protections
Navigate the complex terrain of the IA and privacy, which requires not only a technical understanding of the technologies in the game, but also a solid compass ethics and an adequate knowledge of the legal framework of reference. We can't let that technological innovation is proceeding without rules, running the risk of infringing the fundamental rights of the people.
Let's start from the regulations. At a global and regional level have been introduced a series of laws and regulations designed to protect personal data and to ensure the responsible use of AI. The General Regulation on Data Protection (GDPR) in Europe, is an emblematic example. This regulation lays down a series of key principles that must guide the management of personal data, including:
- The lawfulness, fairness and transparency: The data must be collected and used in a lawful manner, and in a way that protects the stakeholders and providing them with clear information about the treatment.
- The limitation of purposes: The data must be collected for specified, legitimate purposes, and may not be used for any other purpose without the consent of the interested party.
- The data minimisation: Must be collected only the minimum amount of data necessary to achieve the purpose.
- L’accuracy: The data should be accurate and, where necessary, updated.
- The limitation of the conservation: The data must be retained for the time strictly necessary.
- L’integrity and confidentiality: Data must be protected from unauthorized access and security breaches.
- The empowerment: Organizations that deal with the data are responsible for compliance with the GDPR and must demonstrate that it has adopted appropriate measures.
But laws alone are not enough. We need an ethical approach to wider, that is based on some fundamental principles:
- The consent: Individuals must have the right to decide if and how their data is collected and used.
- The transparency: Individuals must be informed in a clear and understandable way about how their data are processed by the systems of IA.
- L’accountability: Organizations must be accountable for the decisions taken by their systems of IA, and must be ready to give an account of their actions.
- The non-discrimination: The systems of IA must not be used to discriminate against or disadvantage certain groups of people.
Finally, it is important to mention some techniques and innovative approaches that can help to protect privacy in the age of AI. Privacy-Enhancing Technologies (PET), and the Federated Learning are just a few examples, and offer new ways to process the data while preserving the privacy of individuals.
Ultimately, to build a digital future in which AI and privacy to co-exist in harmony is a complex challenge, but indispensable. Requires a joint effort on the part of legislators, businesses, researchers and citizens should work together to define an ethical framework, and legal and solid to develop innovative technological solutions that put at the center of the rights and freedoms of the people.
Case Study: AI and Privacy in Practice
To fully understand the scope of the implications of AI on privacy, it is useful to move from theory to practice, by considering some concrete examples of how these technologies are being applied in the real world. The applications are different and, often, they question the complex.
Take for example the facial recognition and its use by the forces of law and order. Some departments have started to adopt systems able to identify people starting from the images of the surveillance cameras, with the stated goal of capturing criminals or prevent terrorist acts. But this practice is not without risks. We think of the case of Clearview AI, a company that has created a giant database of faces taken from each corner of the web, powering a system of facial recognition by the unprecedented power. The use of this technology has triggered a wave of protests, concerns, and even interventions by the data protection authorities, who have sanctioned the company for the aggressive mode with which she gathered and used the biometric information. The debate is open and focuses on the balance (which is often hard to find) between the effectiveness of these tools in the fight against crime and the risk of a surveillance mass that compresses our fundamental freedoms.
Another area in which the IA and privacy are intertwined in intricate ways is one of the personalized advertising. The algorithms analyze our browsing habits online, the history of our purchases, the interactions that we have on the social network to show ads that are assumed to be more in line with our interests. This practice is the backbone of many online business models, but even here there are important questions. The social media platforms, for example, use sophisticated algorithms to select content that we see in our feeds, and we often don't have a clear awareness of how we make those decisions. This raises questions about the transparency of these processes and on the potential (not the remote) for the manipulation of our thoughts and our behaviors. In this regard, the GDPR and other privacy regulations introduce stringent constraints to the profiling of users and require their explicit consent to the collection and use of data for advertising purposes.
Finally, we cannot ignore the impact of AI on the privacy in health carewith the spread of wearable devices such as smartwatch. These small accessories technology to collect an impressive amount of data about our health, from heart rate to the level of physical activity, through the quality of sleep. The analysis of these data using the AI promises to revolutionize medicine, allowing earlier diagnosis, personalized treatments and a constant monitoring of well-being. However, open disturbing scenarios if the data is so sensitive from falling into the wrong hands or be used for purposes of discrimination. Let's say, for example, a company that uses the biometric data of employees to decide whether to promote them or sack them, or an insurance company, which increases the premiums to those who have a risk profile of “non-optimal”.
These concrete examples help us to understand that the AI is not an abstract entity, but a technology that has a profound effect on our daily lives, and that the issue of privacy is increasingly central in this new scenario. For this reason, you can't just reacting to problems as they come up, but we have to adopt a proactive approach, which integrates the data protection from the design stage of the systems of IA, and build control mechanisms and responsibilities well defined. At the same time, it is essential to promote an informed public debate and a greater awareness among the users, so that everyone can exercise more control over their data and contribute to the shaping of a digital future in which AI and the privacy to really live in harmony.
