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August 17, 2023

How to build a Responsible AI Culture in your company

Artificial intelligence has become the great technological revolution of the last decade and has already become an element present in our daily lives, often without us being aware of it.

Its countless applications to automate processes and improve business productivity have led to its rapid adoption. However, being a constantly evolving technology, it can generate some misgivings when it comes to creating a culture around AI. Therefore, its implementation requires a change of mentality in the company and employees, as well as a commitment to responsible AI to ensure its correct use and alignment with the values of each company. We analyze what responsible AI is and how to create an appropriate culture around it.

Generative AI Incursion

Recent advances in Generative AI have opened up a range of opportunities and are also posing a major challenge for businesses and their leaders.

This new revolution has put companies in a race to realize the value of AI quickly, but also public pressure to effectively manage the ethical, privacy, and security risks of this technology.

Some companies have reacted by blocking some generative AI tools for their employees, and some governments by banning their use in public administrations, which has been the trigger for regulating this technology in institutions such as the European Union.

While it may sound somewhat alarming, the good news is that the AI revolution is only in its infancy, and companies are at the right time to make responsible AI a powerful capability in their business policies. However, the investment and effort required to implement such a strategy is often underestimated.

BGC has conducted a global survey of executives to understand the degree of concern about this issue and shows that, on average, responsible AI maturity improved marginally from 2022 to 2023. In addition, the proportion of companies that are responsible AI leaders has increased from 16% to 29%, which is quite encouraging and shows the importance of focusing on this issue.

What is Responsible AI

The term responsible AI refers to the creation and use of AI systems that are developed and used ethically and fairly to minimize the risks associated with their use, as well as artificial intelligence that is transparent, people-centered, and safe.

Businesses must be committed to creating artificial intelligence systems for the benefit of all, and to this end, there are several principles underpinning responsible AI.

Principles underpinning Responsible AI

The six principles of responsible AI are the basis for building technology that benefits all and does not discriminate against or harm humans. They are:

  • Equity: stereotyping based on demographics, culture, or other factors should be reduced.
  • Reliability and security: systems should be developed in a way that is consistent with each company’s design ideas, values, and principles so as not to cause harm to the world.
  • Privacy and security: Special focus should be placed on ensuring that personal and organizational data is not leaked or disclosed.
  • Inclusion: AI systems must empower and interact with people worldwide without leaving minority communities behind.
  • Transparency: Developers must be clear and open about how and why they use AI, as well as understand AI behavior.
  • Responsibility: we are all responsible for how technology affects the world, so we must apply our principles consistently and consider them in what we do.

Benefits of implementing Responsible AI

According to McKinsey & Co, AI is poised to transform roles and increase performance in functions such as sales and marketing, customer operations, and software development. In the process, it could unlock billions of dollars to the tune of more than US$4.4 trillion a year.

Since most jobs involve or will involve AI, workers need to understand its benefits and see it as a teammate that will help them save time, money and help their talents shine even brighter.

Some of the advantages involved are:

  • Increased confidence in decisions: by developing ethical and fair AI systems, businesses and individuals can rely on technology to make important decisions without worrying about potential biases.
  • Increased equity and fairness: helps ensure that all members of society have equal opportunities and access to services or resources.
  • Improved quality of life: they can help provide more accurate medical diagnoses, personalized recommendations, or complex social and logistical solutions.
  • Improved productivity and sustainability: automating routine tasks increases companies’ efficiency and productivity, reducing human errors, and providing faster and more accurate solutions. In addition, it can be a great commitment to sustainability and corporate social responsibility by optimizing resource use or reducing waste intelligently.

The challenge of bias and discrimination

Eliminating bias is one of the main challenges for responsible AI, which is why combining efforts in this regard is so important.

If care is not taken when creating algorithms, models can get into dangerous territory, especially if the wrong data is given, which can lead to unfair or inclusive AI. AI models respond to what is learned, so it is not the technology itself that is to blame but the data we train it on together. Prioritizing gender equality and social justice is crucial when designing a Machine Learning model that avoids bias and is based on the principles of Responsible AI mentioned above.

Some of the strategies that can be used to address this issue include:

  • Diverse and unbiased training data: Collecting more diverse, truthful, and representative data from across society can help reduce bias, as well as introduce equitable ML techniques.
  • Checking and auditing data: this is one of the most important parts because if bias or discrimination is identified, the model or data can be adjusted to correct it.
  • Evaluate the models on an ongoing basis: it is important to do this step to detect any biases that may arise in the future. By monitoring the models’ results, you can adjust at any point in time.

To create a roadmap that considers all of the above, the most important thing is planning and communication between all parts of the organization:

  • Awareness of the need to incorporate AI into work systems
  • Willingness to participate and support the new way of working
  • Training in best practices for incorporating this technology into daily dynamics
  • Reinforcement to sustain change

Establishing a Responsible AI Strategy

Generative AI has succeeded in democratizing this technology by making it available to everyone, not just to tech experts. However, this mass access increases the challenges of AI, such as unauthorized development and use by teams that do not have expertise in the field.

Responsible AI needs to be integrated throughout the organisational structure, but improving awareness and measures of responsible AI requires changes in operations and culture. Therefore, the right choice is to rely on a technology partner that understands the importance of this type of business approach.

Responsible AI facilitates faster innovation and minimizes risk, so companies that ride the next wave of regulation by following responsible business practices will be able to satisfy regulators, shareholders, and customers with cutting-edge, secure products and services.

Responsible AI Partner of the Year

At Plain Concepts, we have been recognized as Microsoft’s Responsible AI Partner of the Year thanks to our focus on education and awareness of the ethical aspects and responsible use of AI based on two main pillars: internal training and customer communication.

Internally, we provide regular training to our employees on the ethical aspects of AI, promoting a deep understanding of the challenges and best practices in this area. With customers, we focus on education and advice, providing them with clear and accurate information on ethical issues and responsible use, guiding them in making ethical decisions in their projects.

We provide you with different tools to better understand and know how the different algorithms developed respond. We adapt to new legislative changes and your needs to embark on a joint path toward efficiency and responsibility. If you want to know how do not hesitate to contact us, and our experts will be able to advise you.

Elena Canorea
Elena Canorea
Communications Lead