Crafting a Responsible AI Strategy
Rebecca Jones
By Rebecca Jones, general manager of Mosaicx
We find ourselves at a crossroads where AI is no longer just a buzzword but a new reality, reshaping the business landscape. The transformative power of AI is clear to all of us, yet we’re still developing our collective picture of how to govern and manage these intelligent systems responsibly.
As businesses embrace AI-enabled technology and solutions, laying the groundwork for responsible and reliable implementations is paramount.
This article shares helpful tips for establishing such strategies.
We at Mosaicx suggest seeking advice from your legal team to determine your optimal course of action.
What is Responsible AI?
What exactly does “responsible” mean? Gartner defines responsible AI as “an umbrella term for aspects of making appropriate business and ethical choices when adopting AI. These include business and societal value, risk, trust, transparency, fairness, bias mitigation, explainability, sustainability, accountability, safety, privacy and regulatory compliance.
“Responsible AI encompasses organizational responsibilities and practices that ensure positive, accountable and ethical AI development and operation.”
Responsible AI aims higher than technology that works efficiently. It's about systems that ethically and empathetically understand their impact on people and society.
It means algorithms that don’t just run flawlessly but also respect the privacy of partners and customers, ensure fairness and are held accountable.
Create a Framework
The ways we can use AI to our benefit are numerous and constantly evolving. It’s critical for businesses to prioritize safety, practicality and user benefit to maximize the potential.
This approach means integrating ethical considerations at every development stage, from initial design to deployment.
There are several ways that businesses can approach building a responsible framework. Decision-makers can consider asking themselves the following questions to kickstart and guide the process:
What steps are we taking to identify and mitigate potential biases in our AI algorithms?
How can we make our systems more transparent to users and stakeholders?
How are we safeguarding the privacy of user data in our applications?
What efforts are we making to give users insights into how decisions are reached?
What mechanisms are in place to monitor our system’s decisions and actions?
What steps are we taking to stay abreast of emerging AI and machine learning regulations?
How do we plan to adapt our models as societal and ethical norms evolve?
In what ways are we seeking feedback from users to improve our AI-enabled processes?
Beyond the outlined questions, decision-makers can strive to foster a continuous improvement and learning culture within their organizations.
This process might involve engaging with the broader AI community, sharing best practices and contributing to the collective wisdom that propels responsible AI forward.
The responsible integration is not merely a destination; it's an ongoing journey that requires commitment, adaptability and a shared vision for a future where technology aligns seamlessly with societal values.
Build Trust Through Transparency and Accountability
Customer trust is integral to a company’s success. One way to foster customer trust around AI integrations is by communicating transparently.
That involves demonstrating how the system works, what data it uses and how the business protects this data.
Accountability is equally important. If errors occur, businesses must take responsibility and address them promptly. Taking accountability might involve making necessary adjustments to the system or improving data protection measures.
A framework that prioritizes transparency and accountability ensures that trust in your AI system grows stronger over time.
Clear Benchmarks and Regular Testing
Clear benchmarks act as a lighthouse, guiding the system towards its intended purpose. Benchmarks set quantifiable goals, such as accuracy rates or user engagement levels, which the business can regularly measure.
The journey doesn’t end at setting these benchmarks. Organizations must continually test their solutions. Regularly evaluate the AI against these standards to identify areas for improvement and ensure the system remains efficient and effective.
Think of it as a cycle of constant refinement, where each iteration makes the AI more intuitive, safe and aligned with its purpose. Rely on feedback from real users to guide innovations over time.
Keep in mind that we recommend seeking guidance from your legal team during the development and implementation of an ethical framework.
The AI landscape is dynamic, with new use cases emerging quickly.
Ultimately, a responsible strategy merges technological prowess with ethical sensitivity. It’s about understanding the best applications and continuously nurturing and monitoring these systems to ensure they remain aligned with human values and societal norms.
When built responsibly, AI can be a trusted ally in our digital world.
This Communication Intelligence magazine Contributed Advisory is the professional courtesy of Rebecca Jones, the general manager of Mosaicx, a leading provider of customer service AI and cloud-based technology solutions for enterprise companies and institutions.
She joined the West Technology Group, owner of Mosaicx, in January 2021, after a 25+ year career focused on growing businesses, people and client success.
She serves as a member of the board of the Families for Effective Autism Treatment (FEAT) of Louisville, KY, is an executive sponsor for Women of West, volunteers for The Molly Johnson Foundation that supports children with special needs and additionally champions causes promoting women in technology, including the IWL Foundation (Integrating Women Leaders Foundation), Tech Up for Women and CCWomen.
