Artificial Intelligence Collaboration and Indirect Regulatory Lag

Forbes

a day ago

WASHINGTON, DC - MAY 16: Samuel Altman, CEO of OpenAI, testifies before the Senate Judiciary ... More Subcommittee on Privacy, Technology, and the Law May 16, 2023 in Washington, DC. The committee held an oversight hearing to examine A.I., focusing on rules for artificial intelligence. (Photo by)
Steve Jobs often downplayed his accomplishments by saying that 'creativity is just connecting things.' Regardless of whether this affects the way you understand his legacy, it is beyond the range of doubt that most innovation comes from interdisciplinary efforts. Everyone agrees that if AI is to exponentially increase collaboration across disciplines, the laws must not lag too far behind technology. The following explores how a less obvious interpretation of this phrase will help us do what Jobs explained was the logic behind his genius
The Regulatory Lag
What most people mean when they say that legislation and regulation have difficulty keeping pace with the rate of innovation because the innovation and its consequences are not well known until well after the product hits the market. While that is true, it only tells half of the story. Technological innovations also put more attenuated branches of the law under pressure to adjust. These are second-order, more indirect legal effects, where whole sets of laws—originally unrelated to the new technology—have to adapt to enable society to maximize the full potential of the innovation. One classic example comes from the time right after the Internet became mainstream. After digital communication and connectivity became widespread and expedited international communication and commercial relations, nations discovered that barriers to cross-border trade and investment were getting in the way. Barriers such as tariffs and outdated investment FDI partnership requirements—had to be lowered or eliminated if the Internet was to be an effective catalyst to global economic growth.
Neoliberal Reforms
When the internet emerged in the 1990s, much attention went to laws that directly regulated it—such as data privacy, digital speech, and cybersecurity. But some of the most important legal changes were not about the internet itself. They were about removing indirect legal barriers that stood in the way of its broader economic and social potential. Cross-border trade and investment rules, for instance, had to evolve. Tariffs on goods, restrictions on foreign ownership, and outdated service regulations had little to do with the internet as a technology, but everything to do with whether global e-commerce, remote work, and digital entrepreneurship could flourish. These indirect legal constraints were largely overlooked in early internet governance debates, yet their reform was essential to unleashing the internet's full power.
Artificial Intelligence and Indirect Barriers
A comparable story is starting to unfold with artificial intelligence. While much of the focus when talking about law and AI has been given to algorithmic accountability and data privacy, there is also an opportunity for a larger societal return from AI in its ability to reduce barriers between disciplines. AI is increasing the viability of interdisciplinary work because it can synthesize, translate, and apply knowledge across domains in ways that make cross-field collaboration more essential.
Already we are seeing marriages of law and computer science, medicine and machine learning, environmental modeling, and language processing. AI is a general-purpose technology that rewards those who are capable of marrying insights across disciplines. In that sense, the AI era is also the era of interdisciplinary problem-solving.The boundary-blurring opportunities triggered by AI are up against legal barriers to entry across disciplines and professions. In many professions, it requires learning a patchwork of licensure regimes and intractable definitions of domain knowledge to gain the right to practice or contribute constructively. While some of these regulations are generally intended to protect public interests, they can also hinder innovation and prevent new interdisciplinary practices from gaining traction.
To achieve the full potential of AI-enabled collaboration, many of these legal barriers need to be eliminated—or at least reimagined. We are starting to see some positive movements. For example, a few states are starting to grant nurse practitioners and physician assistants greater autonomy in clinical decision-making, and that's a step toward cross-disciplinary collaboration of healthcare and AI diagnostics.
For now, this is a move in the right direction. However, In some other fields, the professional rules of engagement support silos. This must change if we're going to be serious about enabling AI to help us crack complex, interdependent problems. Legislators and regulators cannot focus exclusively on the bark that protects the tree of change, they must also focus on the hidden network of roots that that quietly nourish and sustain it.