Regardless of who wins the US presidency, AI policy may be the same — here’s why

The AI policy landscape: Continuity amidst political rhetoric: Despite recent campaign rhetoric, there is significant continuity in AI policy between the Trump and Biden administrations, with both building on foundations laid during Obama’s presidency.

• The Trump administration made AI a national technology priority, implementing many recommendations from Obama-era reports on AI and big data.
• Biden’s executive order on AI, which Trump has vowed to overturn, actually echoes and expands upon two executive orders Trump himself signed during his presidency.
• Key initiatives in Biden and Harris’s AI efforts, such as the National AI Research Resource, originated from legislation passed near the end of Trump’s term.

Shared priorities and bipartisan momentum: Both major parties and administrations have demonstrated alignment on several core AI policy goals, despite surface-level disagreements.

• Common objectives include supporting private-sector innovation, establishing federal funding for AI research, preparing the American workforce for economic changes, and setting safety standards for AI technology.
• There is bipartisan support for laws regulating deepfake disinformation, combating nonconsensual AI-generated sexual imagery, protecting consumer privacy, and preventing AI-enabled fraud.
• Even initiatives focused on preventing algorithmic discrimination and ensuring fair AI outcomes were present in Trump-era policies, despite recent Republican rhetoric opposing such measures.

Public concern and growing demand for regulation: The rapid advancement of AI technology has brought these issues to the forefront of public consciousness, increasing pressure for substantive policy action.

• Polling consistently shows that a majority of adults from both major parties support government regulation of AI, with demand for regulation potentially growing.
• Americans broadly support Biden’s executive order on AI, which aims to preserve consumer and civil rights while spurring innovation.
• The release of ChatGPT less than two years ago has made AI a household topic and common concern, elevating public expectations for accountability from any administration.

Potential challenges to policy continuity: Despite the historical bipartisan approach to AI policy, recent political rhetoric suggests potential shifts in the future.

• Trump has promised to overturn Biden’s executive order on AI “on day one” if elected, framing it as part of a culture war rather than addressing substantive issues.
• The GOP platform has criticized Biden’s executive order as “dangerous” and imposing “Radical Leftwing ideas” on the technology.
• Some Republicans have expressed resistance to concepts like “algorithmic discrimination” and AI civil rights protections, despite similar language appearing in Trump-era policies.

Industry engagement and implementation progress: The tech industry and civil society have shown support for many existing AI initiatives, potentially complicating efforts to drastically alter the policy landscape.

• Major AI companies have entered voluntary agreements with the government and advised on AI regulation.
• Many initiatives from Biden’s executive order have already been implemented, creating momentum that may be difficult to reverse.
• There is broad industry and civil society support for federal safety standards and research funding in AI.

Broader implications: The challenge of partisan politics in rapidly evolving tech policy: The pace of AI advancement may outstrip the ability of traditional political divides to shape policy effectively.

• When Obama, Trump, and Biden were elected, the current state of AI technology was largely unforeseen, highlighting the challenge of creating forward-looking policies in a rapidly evolving field.
• The broad public concern and bipartisan momentum behind AI regulation may force any future administration to maintain some level of continuity in approach, regardless of campaign rhetoric.
• The gap between political posturing and the substantive needs of AI governance could potentially lead to more technocratic, less partisan policy-making in this domain.