Responsible AI: Algorithms composed of Artificial Intelligence have been helping to overcome challenges and transform several sectors, mainly in the financial market.
However, to maximize the potential of AI, taking advantage of its benefits and at the same time transmitting transparency and trust, fairly impacting everyone involved in its application, more than an explainable AI is needed. In this case, companies need to rely on Responsible Artificial Intelligence.
Follow this article to understand what Responsible Artificial Intelligence is and its benefits. And why apply this approach to your company’s processes?
What Is Responsible Artificial Intelligence?
Generally, we can conceptualize Responsible Artificial Intelligence as a standard for deploying AI technologies to ensure they are more reliable, secure, and impartial.
More than that, Responsible Artificial Intelligence emerges as a practical way to ensure that AI and machine learning models are more explainable, robust, ethical, and efficient.
Developing a Responsible AI that follows these precepts defines the degree of maturity companies have about AI resources. And the more mature the organization is in this sense, the greater the growth and transformation of the business.
Machine Learning And Building Predictive Models: Applications And Advantages
In a market where data analysis has become crucial for companies to direct their priorities more assertively, terms such as machine learning and predictive models are increasingly common.
After all, today, most organizations have realized that basing their decision-making solely on guesswork and intuition is a mistake. You must guide your actions based on data to optimize results, increase profitability, and gain a competitive advantage.
And that’s exactly what predictive analytics offer; they extract valuable data to predict actions to ensure the best results through data science, statistics, and, mainly, AI techniques such as machine learning.
Machine Learning And Predictive Models: Understand The Advantages
Having data to support corporate decisions is important, but more is needed. Mainly considering that currently, most companies work with a large flow of information daily.
Therefore, it is essential to have solutions enabling an advanced and automated analysis of a large volume of data. In this regard, the use of machine learning in building predictive models makes all the difference.
After all, through this technique, organizations leave the descriptive analysis focused only on the past to give way to a more advanced analysis, which focuses not only on historical data but also on using this information to predict future scenarios.
With a good machine learning system applied in the construction of predictive models, the risks and opportunities are seen in advance, giving a greater margin of time for making better decisions.
Why Apply A Responsible Artificial Intelligence Approach To Processes?
A company that adopts Responsible Artificial Intelligence in its processes adds several benefits not only from an ethical and moral point of view but also from medium and long-term commercial advantages. And several companies are already realizing the full potential of Responsible AI.
Most companies today already see regulatory compliance as a competitive advantage. As a result, this can generate short-term benefits that make it possible not only to attract and retain more customers but also to build a relationship of trust with investors.
Key Benefits And Challenges Of Responsible AI
Responsible Artificial Intelligence has great relevance for organizations. In addition to assisting in the development of more powerful governance strategies, Responsible AI also provides several other benefits.
About the consumer, it allows the development of more inclusive products and services, which are satisfactory in all user profiles, bringing more security and transparency, attributes that help retain customers and increase the organization’s credibility.
In addition, with a Responsible AI, it is also possible to:
- Generate more impartial and representative AI algorithms ;
- Empower employees to govern technology and innovation effectively;
- Raise the level of data privacy and security ;
- Mitigate risks ethically by establishing systems that benefit customers and markets.
Linked to the benefits, there are still some challenges that Responsible Artificial Intelligence imposes on companies. One is the need for a standard for implementing the risk management framework required for Responsible AI.
There is also a need for a greater diversity of talent with a unique emphasis on ethics and artificial intelligence in the workplace. Not to mention the difficulty of measuring results since the success of its implementation is measured based on non-traditional KPIs.
Implementing Responsible Artificial Intelligence in corporate processes can lead companies to find innovative ways to achieve their goals, generate safer and more reliable products and services and earn more.
However, for this to happen, it is necessary to unite the pillars of Responsible AI, such as fairness, transparency, empathy, and robustness, to build a sustainable vision and thus achieve long-term success.