From the device that plays music from the command of our voice to banking applications, Artificial Intelligence (AI) is increasingly present in our day. Along with the benefits provided to ordinary users and companies, this technology also raises questions about the relationship between ethics and Artificial Intelligence, which is due to the large volume of information accessed by it.

Like any other technological tool involving data, AI cannot be used indiscriminately. Otherwise, your company may be exposed to data leakage or the inappropriate use of information and, consequently, the application of legal penalties.

Want to know more about this subject of huge importance? In this post, we talk to Alexandre Penazzo, Head of Data Architecture at Engineering, who clarifies the relationship between these two concepts. Come with us to take your doubts!

What Is Ethics?

Derived from the Greek, the term ethics means ”behavior”, ”habit”. In the modern world, it is meant as a set of moral principles and values that rule the behavior of individuals or social groups.

With the digital transformation, the concept of ethics in the online world also emerged, which consists of guaranteeing the safety, dignity and privacy of people in the virtual environment, taking into account moral values ​​and current legislation.

What Is Artificial Intelligence?

AI is defined as systems or machines capable of simulating human reasoning, managing to perform tasks that previously could only be performed by people. In addition, it is also characterized by continuous improvement as it collects new information.

The popularization of AI is essential for automating tasks, gaining agility in industrial operations and improving the quality of product delivery.

How Important Is Ethics In AI?

The growing use of Artificial Intelligence in personal life and in companies raises an important question: how far can our data and information be stored, analyzed, shared, sold or even manipulated with suggestions to influence us?

Exposure of personal data can jeopardize the security of users of AI tools. In view of this, laws are being made and followed all around the glob to protect sensitive information and data that may be used in your advantage or against you. An example of this is the General Law for the Protection of Personal Data ( LGPD ), which came into force in Brazil in 2020.

”The use and definitions of ethics are very important so that you are not suggested to make purchases, choose products and even be influenced to make decisions about what should or should not be done”, points out the Head of Data Architecture at Eng.

Why Should Ethics And Artificial Intelligence Go Together?

Although it is of very big use for society as a whole, the adoption of AI tools can cause a number of problems if used improperly, such as data theft and fraud.

One of the main pillars of digital ethics is to allow and create mechanisms so that there are no mass layoffs in many sectors, but a way to train and qualify people in these new markets that will emerge and, without a doubt, will need skilled work.

Thinking about data, AI systems have proven to be very efficient, especially in repetitive work, validation and recognition of patterns and trends.

”These activities are stressful for humans and time-consuming. At the same time, I observe a movement of large technology companies creating free online training so that people understand and adapt to this reality”, highlights Alexandre Penazzo.

How Do Ethics Impact The Use Of AI In Companies?

Since they perfect themselves, the lack of control and ethics can make AI tools make serious mistakes. On the other hand, the use of ethics to guide this technology brings positive impacts for companies. See what they are.

More Responsibility In Working With AI

In 2016, Microsoft released machine learning using Twitter as a data source and platform. However, in less than 24 hours, the robot became racist. The case became famous and generated a great warning about how we should be concerned about keeping systems trained and updated with good data sources.

The adoption of disruptive technologies such as AI is a concern because most Machine Learning algorithms are built to independently perform decision-making. According to Alexandre Penazzo, for this to be fair, the code and database used for training must have well-defined criteria and objectives.

With the curations made by people to validate if the information is really what was expected and if the codes are running correctly, the creation of mechanisms for alerts and notifications of deviations in behavior and the accuracy of decision-making, increased responsibility of services based on AI systems.

Gain Transparency In Projects

When we talk about transparency in projects that use AI, it is necessary to keep in mind that everything starts with data sources, which are usually decentralized and, many times, are reflections of old systems, electronic spreadsheets, photos, instant messages and videos.

When it comes to AI tool providers, great care must be taken to establish normalizations, extract data and detect problems without exposing sensitive data belonging to customers or employees.

”For this, there are specific techniques. One of them is Data Loss Prevention (DLP), which is characterized as a set of tools and processes that prevent the loss, misuse or unauthorized access of confidential data”, informs the representative of Eng.

Risk Reduction

Mitigating errors is an essential action in all computational projects, especially in those that use the decision-making process. Applying DLP to data usage and manipulation increases business security.

DLP software acts on the classification of regulated, confidential and critical data for organizations, recognizing possible violations of policies established by the business or that are part of a predefined policy package, which is commonly accelerated by regulatory compliance.

Upon detecting a violation, DLP sends alerts for error correction and reinforces security and encryption, in addition to initiating protective actions that prevent end users from sharing data in the wrong way and end up exposing the company to external threats.

”DLP also generates reports that meet compliance and audit criteria, which allows the company to identify areas of vulnerability and anomalies that must be analyzed. In this way, we can guarantee automated security to the protection process and reduce risks to computational projects”, completes Alexandro Penazzo.

What Are The Problems Of Using Unethical AI?

The lack of ethics in the adoption of products for decision-making can lead to numerous problems with major consequences. Recently, it became public that Facebook shared data from its users to Amazon, Google and Spotify, which caused immediate damage to the organization, which saw the value of its shares plummet.

A company that uses data to accelerate its business is not unethical, but strategic. However, using data to influence, tend and even manipulate information undoubtedly has serious consequences for the company and its external or internal customers.

An organization that works with ethics and Artificial Intelligence respects sensitive data, preserving the security of personal information handled in its operations, which conveys greater credibility to the market and customers. Therefore, an ethical stance on the use of AI helps businesses adapt to digital transformation and grow responsibly.

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