From Concerns to Solutions: Harnessing Agile Governance for AI and Machine Learning


What do you think of AI and machine learning? Specifically, OpenAI and AI chatbots like ChatGPT?

The CEO of OpenAI warns that AI “can go quite wrong”. Apple is concerned about external AI tools. Leaders like Elon Musk, Steve Wozniak, and hundreds of others have even gone so far as to publicly advise pausing all work on AI, in an open letter to the AI labs industry. But pauses do not happen in practice; human nature does not allow for such unnatural states. This is why we have regulations.

In an ideal world, regulation and governance provide the happy guardrails that shape healthy innovation, supporting businesses and citizens. Unfortunately, regulators have been failing us. What we need is creative innovation within regulation itself, regtech.

Regtech, or regulatory technology, could help bridge what some see as a contradiction in terms: Agile governance.

According to the World Economic Forum (WEF), “Regtech is the application of various new technological solutions that assist highly regulated industry stakeholders, including regulators, in setting, effectuating, and meeting regulatory governance, reporting, compliance, and risk management obligation.” And WEF projected the Regtech market to grow from $7.6B in 2021 to $19.5B by 2026.

In other words, agile governance uses the principles of innovation to support a better society, automating tasks and using technology to translate complex regulations into code, so both the regulated and regulator do their jobs more effectively and collaboratively.

“For the regulated, it strengthens compliance while enabling agility to anticipate and dynamically respond to changing regulatory needs. For the regulator, it enables more transparency as well as agility in modifying requirements to meet new risks more timely.”

This means the relationship evolves to be more iterative and regulation is designed for the user.

So, how do we go about agile governance? There are three initial steps to be taken:

  1. The regulation industry must be more open to new engagement models that will power more agile regulatory processes and outcomes. Any innovation requires collaboration.
  2. They need to explore new design models, perhaps ones more akin to game-changing customer experience platforms to help enable iterative work.
  3. Regulators with more data and sharper analytical tools will make better decisions for all of us—they need new applications, platforms, and possibly even partnerships to support this.

The urgent need for agile regulatory practices is acute. More of our focus should be on the future of regulation than is currently spared. If we’re at a point where Elon Musk is publicly advocating for less innovation, we’re already behind schedule.

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