# Artificial Intelligence Index Report 2023

arXiv: https://arxiv.org/abs/2310.03715 · HTML: https://mlsanity.com/paper/2310.03715/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Oct 2023.

## Built on by (most cited first, 13 of 13)

- [ForecastBench: A Dynamic Benchmark of AI Forecasting Capabilities](https://mlsanity.com/paper/2409.19839/) (2024)
- [Training Machine Learning models at the Edge: A Survey](https://mlsanity.com/paper/2403.02619/) (2024)
- [Explainable AI (XAI) in Image Segmentation in Medicine, Industry, and Beyond: A Survey](https://mlsanity.com/paper/2405.01636/) (2024)
- [Telecom Language Models: Must They Be Large?](https://mlsanity.com/paper/2403.04666/) (2024)
- [On the Workflows and Smells of Leaderboard Operations (LBOps): An Exploratory Study of Foundation Model Leaderboards](https://mlsanity.com/paper/2407.04065/) (2024)
- [Why You Should Not Trust Interpretations in Machine Learning: Adversarial Attacks on Partial Dependence Plots](https://mlsanity.com/paper/2404.18702/) (2024)
- [Simulation-Based Benchmarking of Reinforcement Learning Agents for Personalized Retail Promotions](https://mlsanity.com/paper/2405.10469/) (2024)
- [YOCO: A Hybrid In-Memory Computing Architecture with 8-bit Sub-PetaOps/W In-Situ Multiply Arithmetic for Large-Scale AI](https://mlsanity.com/paper/2312.11836/) (2023)
- [Bias in Text Embedding Models](https://mlsanity.com/paper/2406.12138/) (2024)
- [Reciprocal Learning](https://mlsanity.com/paper/2408.06257/) (2024)
- [AOLO: Analysis and Optimization For Low-Carbon Oriented Wireless Large Language Model Services](https://mlsanity.com/paper/2503.04418/) (2025)
- [Epistemic Deference to AI](https://mlsanity.com/paper/2510.21043/) (2025)
- [Big Tech-Funded AI Papers Have Higher Citation Impact, Greater Insularity, and Larger Recency Bias](https://mlsanity.com/paper/2512.05714/) (2025)

## Abstract (arXiv)

Welcome to the sixth edition of the AI Index Report. This year, the report introduces more original data than any previous edition, including a new chapter on AI public opinion, a more thorough technical performance chapter, original analysis about large language and multimodal models, detailed trends in global AI legislation records, a study of the environmental impact of AI systems, and more. The AI Index Report tracks, collates, distills, and visualizes data related to artificial intelligence. Our mission is to provide unbiased, rigorously vetted, broadly sourced data in order for policymakers, researchers, executives, journalists, and the general public to develop a more thorough and nuanced understanding of the complex field of AI. The report aims to be the world's most credible and authoritative source for data and insights about AI.