Why Organizations Will Be Adopting Trust & Security in AI at an Accelerated Pace

Rodrigo Vargas | January 18, 2023

Artificial Intelligence delivers innovation, opportunities, and also risks. As such, organizations require new ways of approaching trust, risk, and security to protect their environments and improve business outcomes.

Rodrigo Vargas, Encora’s Delivery Director in Central & South America, delivers a poignant look at one of the most prominent trends of 2023: Trust & Security in AI. Sharing his leadership perspective on this topic, Mr. Vargas is among the accomplished Innovation Leaders who collectively present the top 10 technology trends that will re-engineer the next generation of technology in 2023.

Mr. Vargas focuses on Trust & Security in AI, a rising trend that helps organizations derive more value from their AI technologies

 

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What is Trust & Security in AI, and what is its use? 

As AI becomes more prevalent, transformative, and advanced, there’s a growing need to trust AI models, especially those used in life-or-death situations and mission-critical business decisions. The reality is that AI operations can be compromised at any stage of the AI life cycle, whether by benign mistakes or malicious attacks.  
 
AI privacy breaches, security incidents, data leaks, etc., have serious and negative consequences, which is why organizations must be swift in finding new ways to look for vulnerabilities in AI that frequently go unnoticed. Traditional forms of trust and security are growing obsolete, and it’s time for IT leaders to focus their time and resources on supporting AI trust and security initiatives to help improve AI outcomes, business goals, and user acceptance.  

 In short, trust and security in AI allow for model governance, fairness, reliability, robustness, effectiveness, data protection, and trustworthiness. It includes solutions, techniques, and processes for making models easy to understand and explain, protecting AI data, running models, and resisting attacks from the outside.

 

Why is Trust & Security in AI a trend that will shape businesses in 2023? 

Similar to how the General Data Protection Regulation (GDPR) significantly boosted privacy-preserving technologies and techniques, we can expect the upcoming AI Act1 in the European Union. The AI Act will require businesses to undergo transformative adoption periods that factor in developing, implementing, and using AI/ML-based products centered around trust, risk, and security. 

 

Why did Encora select it as a rising trend in 2023? 

With many organizations using thousands of AI models and many more working on new applications, it has become more important to make sure that these models can be explained, that the data used to train them follows standards or best practices that protect people's privacy, and that these models will act in a fair way.

 

What makes Trust & Security in AI different from traditional enterprise trust and security systems/technologies? 

In traditional means of approaching trust and security in AI, most of the focus is on limiting access to both data and computing systems/resources. In AI, trust and security are more about where the data comes from and how reliable it is, as well as how the systems themselves act. 

 

Can you speak about your experience with Trust & Security in AI? 

Having worked on all parts of an AI/ML system's development lifecycle, I can say from experience that trust and security must be thought about from the very beginning. The team must also be made aware of how important it is to include trust and security in how they think about and build the system, just like speed or computing performance.

 

In your experience, where do clients stand on the topic? 

I've been lucky enough to work with companies where everyone, from the top executives to the newest engineers, has always kept in mind how important it is to think about trust and security when building a world-class AI/ML product.

 

How can Encora help clients evolve? 

Encora can help and support clients by putting in place and improving MLOps, DataOps, and DevOps processes and tools to speed up model development. At the same time, higher-level, more value-added services can be offered to properly set up an AI governance framework and work as a business partner to align AI development with the organization's strategy and the goals and challenges of end-user adoption.

 

How will Trust & Security in AI impact software & digital product engineering? 

To handle the new ‘rules’ of security, risk, and compliance, teams will need to use new methods and tools. Also, new processes will need to be put in place, which will change how teams deliver models that are ready for production. Models will need to go through more steps to make sure that not only functional requirements are met, but also trust, fairness, and privacy requirements.

 

How are organizations benefiting from Trust & Security in AI today? 

The benefits are twofold. On the one hand, organizations can get access to more data because they can guarantee that the data will be kept private and safe. On the other hand, providers, organizations, and people don't have to blindly trust that their data will be handled properly. As such, organizations can see more people use their models because people trust them more.

 

Who stands to benefit from Trust & Security in AI the most? 

End users, of course! Everyone will be able to trust that the "judgment" by AI models is fair and accurate. Also, organizations and governments will be able to rest easy knowing that privacy and risk management are top priorities and that everything possible is being done to protect data and make sure that models can be explained.

 

How does Trust & Security in AI fit into larger IT and business initiatives? 

There is a direct link between AI trust and security and how organizations handle data and processes that don't involve AI. AI trust and security can only help organizations improve their security controls and risk management processes so that everything is covered from both a technical and a business point of view. The tools and practices that AI trust and security brings to an organization add to what it already has or is putting in place, and they strengthen the organization's overall security strategy. 

 

What does Trust & Security in AI mean for privacy and compliance? 

Data privacy is one of the most important parts of AI trust and security. Since data protection is so important in highly regulated industries like finance and healthcare, a strong AI trust and security framework makes it easier for organizations to achieve regulatory compliance. 

 

 

Our sincere gratitude to Rodrigo Vargas, one of Encora’s Innovation Leaders and the Delivery Director in Central & South America.  
 

The trend, Trust & Security in AI is one of ten featured in Encora’s 2023 Technology Trends eBook. You can read more about this and all the other trends by downloading the eBook. 
 

“Most organizations that use AI Trust & Security initiatives do so to meet regulations, and because they only care about pleasing regulators, they don't do a good job of managing risks. AI Trust & Security needs cross-functional teams that work collectively, from legal, compliance, security, IT, and data analytics teams, to achieve model and data integrity.” 

Rodrigo Vargas 

 

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References 

  1. The AI Act, The Artificial Intelligence Act 
    https://artificialintelligenceact.eu/  

 

About Encora 

Encora is a digital engineering services company specializing in next-generation software and digital product development. Fast-Growing Tech organizations trust Encora to lead the full Product Development Lifecycle because of our expertise in translating our clients’ strategic innovation roadmap into differentiated capabilities and accelerated bottom-line impacts. 

Please let us know if you would ever like to have a conversation with a client partner and/or one of our Innovation Leaders about accelerating next-generation product engineering within your organization.

 

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