The Artificial Intelligence Index Report
The “Artificial Intelligence Index Report 2024,” published by Stanford University’s Institute for Human-Centered Artificial Intelligence (HAI), offers a detailed analysis of AI trends and developments across various sectors.
Now in its seventh edition, this report stands as one of the most comprehensive studies on the evolution of Artificial Intelligence, covering technical advancements, public perceptions, economic impacts, and regulatory measures on a global scale. As AI’s influence continues to expand, this year’s edition broadens its scope to include new metrics, such as AI training costs, responsible AI practices, and AI’s role in scientific and medical progress.
AI’s influence is not only expanding across industries but also penetrating scientific research, healthcare, and public policy.
The report’s mission is to provide rigorously vetted and well-documented data, facilitating a clear understanding of AI’s progress for policymakers, researchers, business leaders, and the public. The analysis ranges from technical advancements and ecosystem development to public perception and policy measures that promote innovation while managing associated risks.
In 2023, AI advancements accelerated, particularly in language models, the emergence of multimodal models, a dramatic rise in generative AI investment, and a substantial increase in AI-related regulations. This comprehensive summary will explore all critical areas of the report, including research and development, technical performance, responsible AI, economic impact, contributions to science and medicine, education, policy and governance, diversity, and public opinion.
Research and Development
The report identifies significant trends in Artificial Intelligence research, focusing on publications, patents, foundational models, and collaborations between industry and academia.
AI research shows steady growth, characterized by an increased output of scientific publications, a rise in patent approvals, and enhanced international collaboration.
AI Publications
- Between 2010 and 2022, the number of AI publications nearly tripled, growing from 88,000 to over 240,000. This reflects sustained interest in AI among academia and scientific communities. The most recent year (2022) saw a modest increase of 1.1%.
- AI research continues to be dominated by the academic sector, which accounted for 81.1% of all AI publications in 2022, followed by industry at 7.9%. Conferences and journals remain the main platforms for publication, both seeing a significant rise in output since 2015.
- Most AI research focuses on machine learning, computer vision, and pattern recognition, indicating a trend toward visual and classification-oriented applications.
AI Patents
- The number of AI patents granted worldwide also experienced substantial growth, increasing by 62.7% from 2021 to 2022. Since 2010, granted patents have increased more than 31 times, indicating rapid innovation.
- China leads global AI patent approvals, accounting for 61.1% of the total, followed by the United States with 20.9%. However, the U.S. share of AI patents has decreased from 54.1% in 2010, reflecting a shift in innovation toward East Asia.
- Training costs for state-of-the-art AI models have reached unprecedented levels, with models like GPT-4 and Gemini Ultra requiring $78 million and $191 million, respectively, for computing alone, underscoring the resource intensity of leading AI developments.
Foundational Models and Collaboration
- In 2023, 149 foundational models were released, more than doubling the number released in 2022, with 65.7% being open source. This shift reflects growing collaboration and openness in AI research. Industry-academic collaborations reached a new high, producing 21 notable models.
- The industry continues to lead in frontier AI research, producing 51 notable models in 2023, compared to 15 from academia. This dominance is primarily due to the financial and computational resources available in the private sector, allowing companies to drive advanced AI developments.
Technical Performance
The technical performance of Artificial Intelligence has seen marked improvements in areas such as image processing, visual reasoning, and English comprehension, although challenges remain in more complex tasks like advanced mathematics and strategic planning.
Advances in AI Capabilities
- AI models have achieved or exceeded human performance in several standard tests, particularly in image classification and text comprehension. However, progress in more difficult tasks, such as competition-level mathematics and strategic planning, remains limited.
- Multimodal models like GPT-4 and Google’s Gemini represent a significant shift, as they can handle text, images, and even audio. These capabilities make them more flexible, enabling a wider range of practical applications and enhancing interaction with complex environments.
New Benchmarks
- As Artificial Intelligence models reach performance saturation on traditional benchmarks, new and more challenging evaluation criteria have emerged. These include SWE-bench for coding and AgentBench for agent-based behaviors, aiming to test more advanced AI capabilities.
- Artificial Intelligence-driven data generation, through models like SegmentAnything, has proven critical for improving technical performance. The creation of robust datasets facilitates greater accuracy and efficiency, allowing faster progress in complex tasks.
Human-Centric Evaluation
- AI model evaluations have started to depend more on human assessments, shifting focus from computer-based metrics to user feedback and real-world applications. This shift emphasizes aligning AI capabilities with human expectations and practical use cases.
Responsible Artificial Intelligence
Implementing and using Artificial Intelligence responsibly faces several challenges, particularly regarding standardized evaluations, political deepfakes, and transparency among AI developers.
Challenges in Evaluation and Regulation
- The lack of standardized benchmarks for evaluating responsible AI complicates comparisons of risks among models from different developers. This limits the ability to conduct a coherent assessment of risks and limitations for the most advanced models.
- Political deepfakes, already used to influence elections, are becoming easier to generate and harder to detect, posing a significant threat to electoral integrity and public trust.
Vulnerabilities in Language Models
- Researchers have identified complex vulnerabilities in language models that can be exploited through adversarial prompts, causing AI to generate unintended outputs, including copyrighted content or biased responses.
- The lack of transparency among AI developers, especially concerning the disclosure of training data and methodologies, hinders efforts to improve the safety and robustness of AI systems.
Ethical and Legal Issues
- The generation of copyrighted content by AI models raises significant legal questions about intellectual property violations. Additionally, political biases detected in models like ChatGPT have generated concerns about their potential influence on user opinions.
Economic Impact
Artificial Intelligence has had a substantial economic impact, influencing investment, productivity, and the labor market. However, it has also contributed to a decline in tech-related job listings.
AI Investment and Job Market Trends
- While global private Artificial Intelligence investment fell for the second consecutive year, funding for generative AI surged nearly eightfold, reaching $25.2 billion in 2023. The United States led with $67.2 billion in private investment, far exceeding China’s $7.7 billion.
- Organizational adoption of Artificial Intelligence increased, with 55% of companies using AI in at least one business unit in 2023, up from 50% in 2022. AI has been a key driver of productivity and revenue growth, although it has also led to a decline in AI-related job postings, which fell from 2.0% to 1.6% of total U.S. job postings between 2022 and 2023.
Artificial Intelligence in Industrial Automation
- AI-powered industrial robots, particularly in China, represent a significant portion of global installations. By 2022, China led with 52.4% of global robot installations, emphasizing its dominant role in AI-enabled manufacturing.
Science and Medicine
AI has driven significant advancements in science and medicine, improving both the efficiency of scientific discoveries and medical diagnostics and treatments.
Artificial Intelligence in Scientific Advancements
- AI has accelerated scientific discovery, with tools like AlphaDev enhancing algorithm efficiency and GNoME aiding material discovery. This has enabled progress across multiple scientific fields, enhancing research and the development of new technologies.
- In medicine, models like AlphaMissence have improved genetic mutation classification, increasing diagnostic and prognostic accuracy. In 2023, medical AI models achieved a 90.2% accuracy rate on the MedQA benchmark, representing a 22.6 percentage point improvement from the previous year.
Approval of Artificial Intelligence-Related Medical Devices
- The U.S. Food and Drug Administration (FDA) approved more AI-related medical devices than ever before, reaching 139 in 2022, a 12.1% increase from the previous year. AI is increasingly being used for real-world medical applications, contributing to improved healthcare.
Education
The report highlights trends in computer science (CS) education, from basic to university levels, noting the growing integration of Artificial Intelligence-related programs.
Trends in Computer Science Education
- The number of CS bachelor’s graduates continues to rise, while master’s and PhD graduates have seen slower growth or slight declines since 2018.
- There is a significant “brain drain” from academia to industry, with 70.7% of AI PhDs moving into industry roles in 2022. Migration from industry back to academia remains limited, negatively impacting long-term academic training and research.
Growth of AI-Related Programs
- Globally, AI-related degree programs have tripled since 2017, with universities worldwide expanding their offerings to meet the growing demand for AI expertise. The United Kingdom and Germany lead in producing graduates in computer science-related fields in Europe.
Policy and Governance
Artificial Intelligence-related policies and regulations have significantly increased in both the U.S. and the European Union, reflecting growing legislative attention to the technology.
Artificial Intelligence Regulations and Policy Developments
- AI-related regulations in the U.S. grew by 56.3% between 2022 and 2023, with a total of 25 regulations passed. The European Union’s AI Act and President Biden’s Executive Order on AI represent landmark regulatory initiatives in 2023.
- Globally, mentions of AI in legislative proceedings doubled from 1,247 in 2022 to 2,175 in 2023, highlighting the global reach of AI policy discussions.
Challenges in Artificial Intelligence Governance
- The diversity of regulatory agencies involved in AI oversight has increased, reflecting rising concerns about its impact. In 2023, 21 U.S. regulatory agencies issued AI-related regulations, up from 17 in 2022.
Diversity
The report highlights changes in ethnic and gender representation in CS education, emphasizing both progress and persistent disparities.
Ethnic and Gender Representation in CS Education
- The proportion of CS graduates from Asian, Hispanic, and Black ethnic groups has increased over the past decade. However, gender gaps persist at all educational levels, although they are slowly narrowing.
Diversity in K-12 CS Education in the U.S.
- K-12 CS education in the U.S. has become more diverse, with increased participation from female and minority students. However, access remains uneven, particularly in larger and suburban schools, limiting equity in technology education.
Public Opinion
Public opinion on Artificial Intelligence shows growing awareness of its potential impact, though significant concerns remain.
Rising Awareness and Concerns
- Global awareness of AI’s potential impact has increased, with 66% of respondents anticipating significant effects on their lives within the next 3-5 years, up from 60% in 2022. Nervousness about AI also rose, with 52% of respondents expressing concerns in 2023.
- Optimism about AI’s economic benefits remains low, with only 37% believing it will improve their jobs. Younger and higher-income demographics are more optimistic about AI’s potential to enhance the economy, health, and entertainment.
Conclusions and Future Implications
The “Artificial Intelligence Index Report 2024” highlights a rapidly evolving AI landscape marked by accelerated technical advancements, significant economic impact, and increased regulatory scrutiny.
AI’s influence is not only expanding across industries but also penetrating scientific research, healthcare, and public policy. However, challenges persist in areas like responsible AI, ethical standards, and equitable access to AI technologies.
Future Implications
- Economic Shifts: AI’s rapid adoption could lead to more pronounced productivity gains but also contribute to job market disruptions. Ensuring reskilling and workforce adaptation will be critical to managing these shifts.
- Ethical and Responsible AI: Standardizing benchmarks for responsible AI is essential to ensure fair comparisons of models’ risks. Regulatory bodies will need to establish clearer guidelines to address ethical issues, data transparency, and biases in AI systems.
- Global Competition: The growing dominance of China in AI patents and development, alongside the U.S.’s leadership in private investment, suggests a sustained geopolitical competition for AI supremacy. This competition could lead to regional variations in AI standards and applications, affecting global collaboration.
- Public Perception and Trust: Building public trust in AI will require transparent governance, ethical AI practices, and education initiatives to demystify AI’s role in society. Public sentiment will influence both consumer adoption and regulatory measures.
- Scientific Advancements: AI’s role in accelerating scientific discovery and healthcare innovations suggests a broader potential for breakthroughs across disciplines. Ensuring ethical deployment in medicine and science will be crucial for achieving positive outcomes.
The report demonstrates that while AI possesses significant transformative potential, its development and integration require strategic and careful management to ensure growth that is inclusive, transparent, and ethically sound. Adopting a balanced approach will be critical for maximizing the benefits of AI while effectively mitigating associated risks.