Report on United States Immigration Policy and its Impact on Artificial Intelligence Leadership and Sustainable Development Goals

This report analyzes the divergence between the United States’ stated goal of leadership in Artificial Intelligence (AI) and its recent immigration policies. These policies present significant challenges to achieving key Sustainable Development Goals (SDGs), particularly those related to innovation, economic growth, quality education, and reduced inequalities.

Executive Summary

Despite campaign-era promises to facilitate immigration for high-skilled graduates, the current administration’s actions have created an environment of uncertainty and restriction for international talent. This policy instability directly undermines the human capital pipeline essential for AI innovation. By creating barriers for international students and skilled workers, the U.S. risks ceding its competitive edge and failing to meet its commitments under the 2030 Agenda for Sustainable Development.

The Role of International Talent in Sustainable Innovation and Growth

The contribution of immigrants to the U.S. technology sector is critical for fostering innovation and economic growth, directly aligning with SDG 9 (Industry, Innovation, and Infrastructure) and SDG 8 (Decent Work and Economic Growth).

Immigrant Contributions to the AI Sector

• SDG 9: A report from the National Foundation for American Policy (NFAP) indicates that 77% of leading U.S. AI companies were founded or co-founded by first- or second-generation immigrants, highlighting their role in driving technological innovation.
• SDG 8: Immigrants have founded over half of U.S. startup companies valued at $1 billion or more, creating jobs and stimulating economic growth. Of the top 48 U.S.-based AI companies, immigrants from India and China have founded nine and eight, respectively.

The Educational Pipeline and SDG 4: Quality Education

U.S. universities serve as a crucial incubator for global talent, a key component of SDG 4. However, retaining this talent is essential for translating educational investment into sustainable development.

• 42% of top U.S.-based AI companies were founded by individuals who first entered the country as international students.
• International students constitute 70% of full-time graduate students in AI-related fields, forming the backbone of the future AI workforce.

Policy Instability and its Detriment to Sustainable Development

Recent administrative actions, characterized by abrupt policy reversals, have undermined the stability and predictability required for strong institutions, as outlined in SDG 16 (Peace, Justice, and Strong Institutions).

The F-1 Visa Revocation Incident

In early April, the abrupt revocation of 1,800 F-1 and J-1 visas created significant disruption. While the decision was later reversed, the incident has had lasting consequences:

1. Undermining SDG 16: The policy whiplash erodes trust in U.S. institutions and demonstrates a lack of predictable, well-managed migration policies.
2. Impact on SDG 4: Affected students face administrative hurdles and, in some cases, have been forced to abandon their studies, directly impeding their access to quality education.
3. Exacerbating SDG 10 (Reduced Inequalities): A disproportionate number of affected students were from India and China and were pursuing degrees in technology, highlighting systemic inequalities in the immigration process. Nine of 21 known lawsuits involved students in computer or data science.

Systemic Barriers to Talent Retention

The U.S. immigration framework contains long-standing systemic barriers that prevent the retention of high-skilled talent, hindering progress toward multiple SDGs.

Challenges in High-Skilled Visa Programs

• H-1B Visa Program (SDG 8): This program is critical for the tech industry, with 65% of recipients employed in computer-related fields. However, denial rates peaked at 15% during the previous Trump administration, and the low probability of success in the visa lottery creates significant uncertainty for graduates and employers, hampering economic growth potential.
• Green Card Backlogs (SDG 10): Per-country caps on employment-based green cards create discriminatory wait times. Indian and Chinese nationals face the longest delays, with an estimated 400,000 Indian applicants unlikely to receive permanent residency in their lifetimes. This contravenes SDG Target 10.7, which calls for orderly, safe, and responsible migration.

Global Competition and the Risk of Talent Drain

Restrictive U.S. policies stand in stark contrast to the proactive talent acquisition strategies of competitor nations, potentially leading to a “brain drain” that weakens the U.S. capacity for innovation and global partnership (SDG 17).

Contrasting International Policies

• Countries like Canada, the United Kingdom, and Australia offer more streamlined and welcoming pathways to residency for skilled workers.
• Canada attracted nearly 40,000 foreign-born graduates from U.S. universities between 2017 and 2021.
• The U.K. has introduced a “High Potential Individual” visa specifically to recruit graduates from top global universities, including 20 in the U.S.

These trends suggest that other nations are capitalizing on the failures of the U.S. system, diverting talent that could otherwise contribute to American innovation and economic vitality.

Conclusion: Aligning Immigration Policy with Sustainable Development Goals

The current trajectory of U.S. immigration policy is misaligned with the nation’s goal of leading the world in AI. More importantly, it creates significant obstacles to achieving the Sustainable Development Goals.

To secure its leadership in innovation and fulfill its global commitments, the United States must:

1. Promote SDG 16: Establish consistent, transparent, and predictable immigration policies insulated from short-term political shifts.
2. Advance SDG 8 and SDG 9: Reform high-skilled visa programs and eliminate green card backlogs to retain the talent that fuels innovation and economic growth.
3. Uphold SDG 10: Create equitable pathways to residency for all high-skilled graduates, regardless of their country of origin.

Leadership in the 21st century requires investment in human capital. By dismantling systemic barriers and fostering a welcoming environment for global talent, the U.S. can ensure its leadership in AI is both dominant and sustainable.

Analysis of Sustainable Development Goals in the Article

1. Which SDGs are addressed or connected to the issues highlighted in the article?

• SDG 4: Quality Education – The article extensively discusses international students pursuing higher education in the U.S., particularly in advanced fields like AI, and the policies affecting their ability to study.
• SDG 8: Decent Work and Economic Growth – The article focuses on highly skilled migrant workers, their contribution to the U.S. economy through innovation and entrepreneurship in the tech sector, and the challenges they face in the labor market due to visa policies.
• SDG 9: Industry, Innovation, and Infrastructure – The central theme is the U.S. race for leadership in Artificial Intelligence (AI), which is a key driver of modern industry and innovation. The article links this leadership directly to the ability to attract and retain scientific and technological talent.
• SDG 10: Reduced Inequalities – The article highlights the unequal and challenging pathways for nationals from specific countries (India and China) to remain in the U.S., despite their significant contributions, pointing to inequalities within and among countries regarding migration and opportunity.
• SDG 16: Peace, Justice, and Strong Institutions – The discussion of “abrupt policy changes,” visa revocations without clear recourse, and the call for “consistent, forward-looking immigration policies” relate to the need for effective, accountable, and transparent institutions.

2. What specific targets under those SDGs can be identified based on the article’s content?

1. SDG 4: Quality Education
   • Target 4.b: By 2020, substantially expand globally the number of scholarships available to developing countries, in particular least developed countries, small island developing States and African countries, for enrolment in higher education, including vocational training and information and communications technology, technical, engineering and scientific programmes, in developed countries and other developing countries.
     
     Explanation: The article focuses on the presence and importance of international students, particularly from India and China, in U.S. higher education, specifically in “AI-related fields” and “computer science, data science, or other tech-related fields.” While not about scholarships directly, it addresses the flow of students to developed countries for scientific programs, which is the essence of this target. The visa policies discussed are a critical mechanism affecting this flow.
2. SDG 8: Decent Work and Economic Growth
   • Target 8.2: Achieve higher levels of economic productivity through diversification, technological upgrading and innovation, focusing on high-value added and labour-intensive sectors.
     
     Explanation: The article argues that U.S. leadership in AI, a high-value-added and innovative sector, is fueled by immigrant talent. It states that “77% of the top AI companies in the United States were founded or co-founded by first- or second-generation immigrants,” directly linking migration to technological upgrading and economic productivity.
   • Target 8.8: Protect labour rights and promote safe and secure working environments for all workers, including migrant workers, in particular women migrants, and those in precarious employment.
     
     Explanation: The article describes the precarious situation of international students and graduates on F-1 and H-1B visas. The “abrupt” visa revocations, the fear of detention, and the uncertainty of the H-1B lottery create an insecure environment for these migrant workers, who are “vulnerable to sudden policy changes.”
3. SDG 9: Industry, Innovation, and Infrastructure
   • Target 9.5: Enhance scientific research, upgrade the technological capabilities of industrial sectors in all countries, in particular developing countries, including, by 2030, encouraging innovation and substantially increasing the number of research and development workers per 1 million people and public and private research and development spending.
     
     Explanation: The article’s core argument is that to “lead the world in AI,” the U.S. must retain its research and development talent. It highlights that “international students make up 70% of full-time graduate students in AI-related fields” and that “60% of foreign Ph.D. recipients in the U.S. say they face difficulties staying in the country,” which directly impacts the number of available R&D workers crucial for innovation.
4. SDG 10: Reduced Inequalities
   • Target 10.7: Facilitate orderly, safe, regular and responsible migration and mobility of people, including through the implementation of planned and well-managed migration policies.
     
     Explanation: The article critiques the U.S. immigration system for its failure to provide “orderly” and “responsible” pathways for highly skilled migrants. It describes “systemic barriers,” “visa policy whiplash,” and long green card backlogs, especially for Indian and Chinese nationals, as evidence of poorly managed migration policies that contrast with the “streamlined paths” offered by competitors like the U.K. and Canada.
5. SDG 16: Peace, Justice, and Strong Institutions
   • Target 16.6: Develop effective, accountable and transparent institutions at all levels.
     
     Explanation: The article points to a lack of institutional effectiveness and transparency. The incident where “1,800 international students… had their visas abruptly revoked with no warning or recourse, and many without explanation” is a clear example of unaccountable institutional action. The article concludes by calling for “consistent, forward-looking immigration policies insulated from short-term political shifts,” which is a plea for stronger, more predictable institutions.

3. Are there any indicators mentioned or implied in the article that can be used to measure progress towards the identified targets?

1. For Target 4.b & 9.5 (Education & Innovation Talent):
   • Percentage of full-time graduate students in AI-related fields who are international students (mentioned as 70%).
   • Percentage of top U.S.-based AI companies founded by individuals who came to the U.S. as international students (mentioned as 42%).
   • Number of students from specific countries (India and China) affected by visa policy changes (mentioned as more than 300 each).
   • Percentage of foreign Ph.D. recipients in the U.S. who face difficulties staying in the country (mentioned as 60%).
2. For Target 8.2 (Economic Growth & Innovation):
   • Percentage of top AI companies founded or co-founded by first- or second-generation immigrants (mentioned as 77%).
   • Percentage of U.S. startup companies valued at $1 billion or more founded by immigrants (mentioned as “more than half”).
   • Number of H-1B visa sponsors that are major tech companies (Amazon, Google, and Microsoft are listed as the largest sponsors).
3. For Target 8.8 & 10.7 (Migrant Worker Protection & Migration Policies):
   • The denial rate for H-1B visas (mentioned as peaking at 15% in 2018).
   • The odds of winning the H-1B visa lottery (mentioned as about 1 in 4, plummeting to 1 in 7).
   • The number of Indian applicants in the employment-based green card backlog who are unlikely to receive status within their lifetimes (mentioned as 400,000).
   • The number of foreign-born graduates from U.S. universities attracted by other countries, such as Canada (mentioned as nearly 40,000 from 2017 to 2021).
4. For Target 16.6 (Strong Institutions):
   • The number of international students whose visas were abruptly revoked without warning (mentioned as 1,800).
   • Qualitative descriptions such as “visa policy whiplash,” “abrupt policy changes,” and lack of “recourse” or “explanation” serve as indicators of institutional unpredictability and lack of transparency.

4. Table of SDGs, Targets, and Indicators

Source: brookings.edu