Responsible AI doesn’t impede innovation – it supports it. Here’s why

Reading Time: 3 minutes

Authors:  

Kush Wadhwa | Chief Executive Officer

Date: 7 May 2024

Following the passing of the AI Act, it’s not entirely surprising that the conversation around responsible AI is surging. In medtech, for instance, there are concerns that the Act doesn’t fully align with the EU’s current Medical Device Regulations 

What I have found surprising, however, are concerns that AI governance could hinder innovation. This is a fallacy. By instilling responsible principles in AI from the start – whether transparency, non-malfeasance, explainability, or any other principles that your use cases call for – you can make sure that innovation and compliance go hand in hand. When you take this approach, new regulations won’t be a blocker.  

I believe that deploying responsible AI can actually help organisations achieve better outcomes, and ultimately carve out an innovative edge. Here’s why. 

 

When you mitigate risks, you can scale with confidence 

 

In business, it’s often thought that you need to move fast and break things to build a competitive advantage. Yet AI isn’t the area to do so.  

If you deploy an AI product without making sure it has the right principles for your intended use cases, you run the risk of scaling inefficiencies as you innovate. Let’s consider fintech products as an example. Failing to course correct an AI solution could mean embedding inaccurate data into a credit risk assessment algorithm, and ultimately perpetuating demographic bias. 

As McKinsey summarises: 

“Without clear rules and guidelines in place from the outset, ML models become increasingly difficult and more time intensive to correct as they develop, which limits their scalability.” 

Whether you’re using machine learning or generative AI, innovating with responsible principles at the core can reduce the risk of multiplying inaccuracies. It gives you the opportunity to factor in your organisation’s values and test your use cases in a microcosm before you scale. This will help you develop products and solutions that achieve your desired outcomes, with the confidence that you’re getting it right. 

 

With a culture of responsibility, you can innovate continuously  

 

In the first wave of AI, we saw technologies like machine learning and natural language processing. In the second, we’re seeing the rise of generative AI models, like ChatGPT. Clearly, AI isn’t an investment that you can make once and then forget about. 

What you can do, however, is build infrastructure that allows you to keep using AI responsibly as you iterate. When you do this from the outset, your organisation will be in a strong position to deploy new AI technologies as and when they evolve. You can begin to see AI as your co-pilot for innovation, while protecting your employees, consumers, and stakeholders as you scale. 

Yes, building a responsible infrastructure means it might take longer to deploy AI throughout your organisation. But this isn’t an impediment – it’s an investment in sustainable innovation.  

 

By staying responsible, you future-proof your innovation 

 

AI is evolving at a very fast pace. It’s extraordinarily powerful and unlike any technology before it. The idea that you could remove bias from it once, and then never again, is simply not true.  

By committing to ongoing AI assurance, you can make sure that your AI continues to work appropriately within its intended context. This in turn will help you to future-proof your innovations, while also preparing to comply with new regulations as they emerge.  

Of course, it’s important not to only shoot for compliance, as this is just one rung on the responsible AI ladder. The AI Act is a good example here.  We’re yet to fully understand how the Act will be operationalised, so it could be tempting to wait and see which boxes need to be ticked before deploying an AI solution. However, by waiting on the sidelines, you’re likely to lose out to competitors.  

Alternatively, by keeping responsibility and trustworthiness principles at the core of your AI, you’ll be prepared to always keep innovating.  

 

Use responsible AI at scale with Trilateral Research 

This is a great time for organisations to develop and deploy AI. The potential for AI-enabled innovation continues to grow, without being impeded by emerging regulations. While I strongly believe that legislators need to be clearer about what is expected from organisations, I’m also confident that responsible and trustworthy AI can help you innovate in the right ways and grow in the right direction. 

At Trilateral Research, we take an interdisciplinary approach to helping organisations deploy responsible AI at scale. With experts in data protection, research, sociotech insights, and more, we help our clients innovate with the confidence that they are achieving the right outcomes. To learn more about our responsible AI services, including our end-to-end AI governance tool, STRIAD:AI Assurance, please get in touch.  

 

You can also follow me on LinkedIn for more insights. 

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