Artificial Intelligence (AI) has the potential to significantly impact society and individuals. As AI becomes more prevalent in our daily lives, it's important to consider the ethical implications of its development and use.

Responsible AI practices involve considering the potential impacts of AI on society and ensuring that it is designed and used in a way that is fair, transparent, and accountable. In this article, we will explore the principles of fairness, transparency, and accountability in artificial intelligence.

The 3 main pillars of responsible AI

Responsible AI refers to the development and use of artificial intelligence in a way that is ethical, fair, transparent, and accountable. This involves considering the potential impacts of AI on society and taking steps to ensure that it is developed and used in a manner that is responsible and respects the rights and interests of all stakeholders. Responsible AI practices can help to ensure that AI is a positive force for good in the world, rather than a source of harm or discrimination.

As AI becomes more integrated into various industries and systems, it's crucial that we consider the potential consequences of its development and use. A responsible approach to AI is grounded in three main principles developed below.

Fairness

It is important to ensure that AI systems do not discriminate against certain groups of people, as this can lead to harmful consequences and perpetuate existing inequalities.

One of the key ethical considerations when it comes to AI is the issue of fairness. AI systems should not discriminate against certain groups of people based on things like race, gender, or age. This is particularly important in areas like face authentication, where AI is used to give individuals access to products and services such as online banking, crypto wallets, or check-in at a hotel. Ensuring that AI is fair and unbiased is crucial for promoting equality and justice.

One way to help prevent discrimination is to use diverse and representative data sets when training AI systems. This can help ensure that the AI system is not biased toward certain groups.

It is also important to evaluate AI systems for bias before they are deployed. There are a number of ways to do this, including testing the AI system on a diverse set of inputs and examining the results to see if there are any patterns of bias. It is also a good idea to have a diverse group of people involved in the development and evaluation process to help identify potential issues of bias.

Transparency

Transparency is another key ethical consideration when it comes to AI. The principle of transparency in AI refers to the idea that AI algorithms and decision-making processes should be explainable and understandable to both developers and users. This is important for several reasons. First, it helps to build trust in AI systems, as people are more likely to trust and use systems that they understand.

Second, it can help to identify and mitigate any potential biases or errors in the AI system, as understanding how the AI system is making decisions allows developers and users to more easily identify and address any problems.

Finally, explainable AI can also help to ensure that the AI system is being used in an ethical and responsible manner, as the decision-making process is more transparent and open to scrutiny.

For us, transparency is also our users having full control of their own data and being able to choose when, how, and to whom users show their personal data in order to access a specific product or service.  

Accountability 

Accountability is also an important aspect of ethical AI. Whenever an AI system is being used, it has to have clearly identified responsible entities. Whether it is those who develop, those who deploy, or those who make use of it in their applications, in each case, the entities responsible should be clearly identified and should be held accountable for any negative impacts they may have. This could include things like loss of jobs or discrimination against certain groups of people.

In order to ensure accountability, it is important to establish clear guidelines and standards for the development and use of AI, and to have mechanisms in place for holding individuals and organizations accountable when those guidelines and standards are not followed. This could involve a combination of technical, legal, and ethical approaches, and may involve establishing processes for reporting and addressing any problems or issues that arise. Ensuring accountability in AI is important for building trust in technology, and for ensuring that it is used in a responsible and ethical manner.

Overall, it's crucial that we consider the ethical implications of AI development and its use in order to ensure that it is a positive force for good in the world. By considering issues of fairness, transparency, and accountability, we can help to ensure that AI is developed and used in a responsible and ethical manner.

Our commitment to fairness, transparency, and accountability in AI

In the way we see it, facial biometrics can be used by companies and individuals in a private and fair manner, reducing the likelihood of misuse or harmful use of biometric data. We believe that individuals should own their data instead of leaving it up to third parties to enable them to access their daily necessities.

Following this ambition, we're part of the Responsible AI consortium, a partnership with companies and institutions that work to develop cutting-edge technology products based on AI. This is the largest consortium dedicated to responsible AI. It aims to connect several key organizations, from universities to start-ups and enterprises, to develop fair, explainable AI that minimizes prejudice and the negative impacts of biased technology. Being part of this working group is a key milestone for realizing our vision.