Responsible AI: What It Is and Why It Matters

9 minute read | 22 Aug 2023

By Ken Jaroenchisakon Madhav Srimadh Bhagavatam

In a split second, AI can discover a pattern, offer a suggestion, make a recommendation, steer a vehicle, render a judgment, approve a loan, and more. Because it can affect so many areas of human life — including account opening, medical diagnoses, hiring, home ownership, school admittance, and law enforcement — it’s critical that AI systems be designed, managed, and fine-tuned in an ethical way.

Responsible AI is the art and science of ensuring that AI delivers ethical results. Responsible AI principles should be part of all phases of building, using, and managing AI: from the way developers build AI models and datasets, to managing how AI applications operate through analytics and observability tools to monitor for biased or unintended results.

The goal of responsible AI is to help people achieve more than ever before without jeopardizing privacy, personal agency, or uniqueness. To achieve these goals, Responsible AI supports:

  • Transparency
  • Human oversight
  • Customer opt-out
  • Data privacy and security
  • Fairness and avoiding bias
  • Environmental sustainability

Merely intending for an AI system to be responsible isn’t enough. The ultimate measure of any AI system is its impact on customers and society overall. Responsible AI aims to ensure this impact is always ethical.

Principles for Responsible AI

What goes into making an AI solution responsible? Here are six key principles.

#1: Transparency

People should be able to understand how an AI product works and how it achieves its results.

Transparency in AI means avoiding “black box” solutions where data goes in and data comes out, but no one can understand how data is transformed and analyzed in between. Instead, the algorithms are transparent. People can understand how responsible AI algorithms work and how they produce results.

A related concept to transparency is explainability. Companies should be able to explain the results of their AI systems.

For example, if an AI banking product recommends that a person be turned down for a loan, everyone involved, including the loan applicant, should be able to understand how that decision was made, what factors were considered, how they were weighted, and so on.

At Boomi, we’re committed to being transparent about how our AI algorithms work, how and where they are used within the platform, and how AI affects data integration and application workflows.

For example, the Boomi AI Explain feature helps users understand how Boomi AI built the optimal integration process. With just a click of a button, you can see exactly which decisions Boomi AI made to achieve its results, and why.

#2: Human Oversight

People should be able to monitor AI systems and intervene in AI-powered operations if they need correction.

AI systems should be designed and deployed in a such a way that people can monitor them, analyze their results, and fine-tune them if necessary to ensure they are operating as designed and in compliance with established guidelines, including ethical guidelines. At any phase of an AI solution’s operation, people should be able to intervene if necessary, stopping automated processes and analyzing AI activity.

When AI systems provide human oversight, they promote accountability. They give AI developers, operators, and users the ability to be held accountable for the results an AI system delivers.

Boomi ensures that its AI algorithms are subject to human oversight and control. Customers can review and override AI-driven decisions whenever they like. Also, our engineering team conducts rigorous reviews of our AI models, using test cases to ensure data quality.

#3: Customer Opt-Out

Customers should be able to opt-out of any AI system or feature they don’t want to use.

In addition, customers should be fully informed about the design, purpose, and scope of AI systems, so they can make informed decisions about whether or not to use a specific system. They should always have the ability to opt out of using AI-powered systems.

At Boomi, customers always have the ability to opt out of sharing their anonymized metadata for use in Boomi’s AI services such as Boomi Suggest and Boomi AI. However, by opting out, customers miss out on the benefits of using smart features like intelligent recommendations that help them integrate and automate faster.

#4: Data Privacy and Security

AI systems should respect data privacy and keep data secure.

AI systems should not ingest data they have not been given permission to ingest. Responsible AI systems will not jeopardize the data privacy of customers or other third parties. They will not expose private data, such as personal identifiable information (PII), to the public or build models using data that belongs to other people or organizations without their explicit permission.

Boomi AI prioritizes data privacy and security and ensures user metadata is collected, stored, and processed in a way that is compliant with laws and regulations.

Our AI solutions use only anonymized metadata when building their AI models. The data is anonymous, meaning that it can never be linked to specific customers or accounts. Also, Boomi AI solutions work with metadata, such as configuration parameters, not actual customer data passing through Boomi integrations and automations. Customer data remains entirely private.

In addition, Boomi customer data and metadata never leaves the Boomi platform. And Boomi AI solutions never ingest customers data from other sites or other third-party services such as OpenAI.

#5: Fairness and Avoiding Bias

AI systems should be inclusive, avoid bias, and deliver results that are fair to all parties.

AI developers and operations managers should ensure that AI algorithms do not discriminate against individuals or groups based on factors such as race, gender, or age. They should regularly monitor AI algorithms for any unfairness or discrimination. And they should ensure that data used for training algorithms does not perpetuate long-standing patterns of discrimination or bias.

For example, training hiring algorithms based on decades-long practices that are known to be discriminatory guarantees that AI will simply perpetuate these practices, rather than correct them.

At Boomi, we are committed to avoiding bias in our AI algorithms. Many of our algorithms work only on metadata, not personal data that might lead to bias. In addition, when appropriate, we train our AI models on diverse data sets that reflect the diversity of our users. We also audit AI algorithms to identify and address any biases or unfairness.

We also manually conduct AI model reviews and apply rigorous test cases to ensure no biases are included in the models and that our AI models are fair. Boomi employees are involved in every step of designing and testing algorithms and models for fairness.

#6: Environmental Sustainability

AI systems should be as energy-efficient as possible to promote environmental sustainability.

It’s easy for people to forget that highly scalable data systems, such as AI systems with large datasets, have the potential to consume lots of power, creating a massive “carbon footprint.”

“AI is itself a significant emitter of carbon,” Nature Magazine notes. “[Researchers at the University of Massachusetts Amherst] estimated that the carbon footprint of training a single big language model is equal to around 300,000 kg of carbon dioxide emissions. This is of the order of 125 round-trip flights between New York and Beijing.”

Another study estimates that a single ChatGPT request consumes 100 times the energy of a Google search.

At Boomi, we evaluate the environmental impact of our AI systems and strive to minimize their carbon footprint. This includes being frugal with data resources, building AI algorithms in energy efficient ways, and, when possible, using renewable resources.

Additional Peace of Mind: FedRAMP Authorization

In addition to following these principles for Responsible AI, Boomi has developed all its AI capabilities in compliance with U.S. Federal Risk and Authorization Management Program (FedRAMP) Authorization Moderate Impact standards. This government-wide program provides a rigorous, standardized approach to assessing the security design and operations of cloud services.

Knowing that Boomi’s AI features comply with FedRAMP guidelines should provide customers additional peace of mind about the security and responsible design of these features.

Responsible AI for Integration and Automation

The Boomi platform adheres to all these principles for all its AI capabilities. As a result, Boomi customers can take advantage of AI for building integrations and automations quickly, confident that their data will never be misused. They can also be confident that Boomi’s algorithms have been designed to act the way a responsible person would, free from bias.

Learn more about Boomi AI, a suite of capabilities that harness the power of generative AI to integrate and automate faster.