How AI Could Write Our Laws

Second, we need to strengthen disclosure requirements for lobbyists, whether they are fully human or AI-assisted. State lobbyist disclosure laws are a shambles. North Dakota, for example, only requires lobbying reports to be filed annually, so by the time disclosure is made, policy is likely already decided. The lobbying disclosure scorecard, created by Open Secrets, a group that studies the influence of money on US politics, tracks nine states that don’t even require lobbyists to report their compensation.

Ideally, it would be good for the public to see all communications between lobbyists and legislators, whether it is in the form of a proposed amendment or not. In the absence, let’s give society the benefit of reviewing what lobbyists lobby and why? Lobbying is traditionally an activity that takes place behind closed doors. Right now, many states are strengthening it. they actually exempt testimony publicly given to the legislature from being presented as lobbying communications.

In those jurisdictions, if you make your position public, you are no longer lobbying. Let’s do the opposite. require lobbyists to disclose their positions on issues. Some jurisdictions already require a position statement (“yes” or “no”) for registered lobbyists. And in many (but not all) states, you can do a public records request for meetings with a state legislator and hope to get something substantial back. But we can expect more. lobbyists may be asked to proactively publish, over several days, a brief summary of what they are asking policymakers to do at meetings and why they believe it is in the public interest.

We cannot count on corporations to be forthcoming and completely honest about the reasons for their lobbying positions. But having their intentions on the record would at least provide a basis for accountability.

Finally, consider the role of AI-assisted technologies on the labor market for lobbying firms and lobbyists themselves. Many observers are justifiably concerned about the possibility of artificial intelligence replacing or devaluing the human work it automates. If AI’s potential for automation eventually commoditizes the work of political strategizing and messaging, it could indeed put some professionals on K Street out of a job.

But don’t expect it to derail the careers of the astronomically highest-paid lobbyists, former members of Congress and other insiders who have come through the revolving door. There is no shortage of reform ideas to limit the ability of lobbyist-turned-public officials to sell access to their colleagues still in government, and they should be adopted and, just as importantly, maintained and implemented in successive Congresses and administrations.

None of these solutions are truly original, specific to AI threats, or even primarily focused on micro-regulation, and that’s the problem. Good governance must and can withstand threats from different methods and actors.

But what makes the risks posed by AI particularly pressing now is how quickly the field is evolving. We expect the scale, strategies and effectiveness of lobbyists to evolve over years and decades. Meanwhile, advances in artificial intelligence seem to be making impressive strides at a much faster pace, and it’s still accelerating.

The legislative process is a constant battle between parties trying to control the rules of our society as they are updated, rewritten, and expanded at the federal, state, and local levels. Lobbying is an important tool for balancing different interests through our system. If it is well regulated, perhaps lobbying can support policy makers in making fair decisions on behalf of us all.

Nathan E. Sanders is a data scientist and affiliate of the Berkman Klein Center at Harvard University. Bruce Schneier is a security technologist and fellow and lecturer at the Harvard Kennedy School.

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