---
title: AI Impact on Society
url: https://www.ml-quant.com/papers/repec/aes-dbjour-v-14-y-2023-i-1-p-61-75/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: RePEc:aes:dbjour:v:14:y:2023:i:1:p:61-75
source_url: https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fwww.dbjournal.ro%2Farchive%2F34%2F34_5.pdf%3Bh%3Drepec%3Aaes%3Adbjour%3Av%3A14%3Ay%3A2023%3Ai%3A1%3Ap%3A61-75
featured: 2024-12-04
citations: unknown
topic: ML & AI Methods
---


# AI Impact on Society

The paper focuses on the influence of AI, particularly the chatbot ChatGPT, on education and the job market, based on a survey of Romanian corporate employees.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fwww.dbjournal.ro%2Farchive%2F34%2F34_5.pdf%3Bh%3Drepec%3Aaes%3Adbjour%3Av%3A14%3Ay%3A2023%3Ai%3A1%3Ap%3A61-75
- Identifier: RePEc:aes:dbjour:v:14:y:2023:i:1:p:61-75
- Released: 2023-03-13
- First featured: Quant Letter No. 77 (2024-12-04): https://www.ml-quant.com/issues/2024-12-04/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: ML & AI Methods

## Related

- [AgentClinic: a multimodal agent benchmark to evaluate AI in simulated clinical environments](https://www.ml-quant.com/papers/arxiv/2405.07960/): AI Evaluation in Clinical Environments: The paper introduces AgentClinic, a benchmark for assessing large language models in simulated clinical environments, highlighting the significant impact of biases on diagnostic accuracy and patient interactions.
- [Learning Performance-Improving Code Edits](https://www.ml-quant.com/papers/arxiv/2302.07867/): The research presents a framework for optimizing programs using large language models, achieving a mean speedup of 6.86, outperforming average individual programmers.
- [Generative agent-based modeling with actions grounded in physical, social, or digital space using Concordia](https://www.ml-quant.com/papers/arxiv/2312.03664/): Concordia is a library designed to help build and operate Generative Agent-Based Models (GABMs), using Large Language Models (LLMs) to simulate physical or digital environments.
- [Jamba-1.5: Hybrid Transformer-Mamba Models at Scale](https://www.ml-quant.com/papers/arxiv/2408.12570/): Transformer-Mamba Models: Jamba-1.5 is a new large language model with enhanced conversational and instruction-following capabilities, featuring a unique quantization technique for cost-effective inference.
- [MindSearch: Mimicking Human Minds Elicits Deep AI Searcher](https://www.ml-quant.com/papers/arxiv/2407.20183/): Mimicking Human Minds for Search: MindSearch is a Large Language Model-based framework that simulates human cognitive processes for web information seeking, greatly enhancing response quality.
- [VickreyFeedback: Cost-efficient Data Construction for Reinforcement Learning from Human Feedback](https://www.ml-quant.com/papers/arxiv/2409.18417/): An auction mechanism is introduced to enhance cost-efficiency in fine-tuning large language models using Reinforcement Learning from Human Feedback, focusing on quality feedback and model performance.
