Re-thinking data strategy and integration for artificial intelligence: concepts, opportunities, and challenges
A Aldoseri, KN Al-Khalifa, AM Hamouda - Applied Sciences, 2023 - mdpi.com
The use of artificial intelligence (AI) is becoming more prevalent across industries such as
healthcare, finance, and transportation. Artificial intelligence is based on the analysis of …
healthcare, finance, and transportation. Artificial intelligence is based on the analysis of …
A review on fairness in machine learning
An increasing number of decisions regarding the daily lives of human beings are being
controlled by artificial intelligence and machine learning (ML) algorithms in spheres ranging …
controlled by artificial intelligence and machine learning (ML) algorithms in spheres ranging …
ChatGPT and a new academic reality: Artificial Intelligence‐written research papers and the ethics of the large language models in scholarly publishing
This article discusses OpenAI's ChatGPT, a generative pre‐trained transformer, which uses
natural language processing to fulfill text‐based user requests (ie, a “chatbot”). The history …
natural language processing to fulfill text‐based user requests (ie, a “chatbot”). The history …
Toxicity in chatgpt: Analyzing persona-assigned language models
Large language models (LLMs) have shown incredible capabilities and transcended the
natural language processing (NLP) community, with adoption throughout many services like …
natural language processing (NLP) community, with adoption throughout many services like …
Lamda: Language models for dialog applications
We present LaMDA: Language Models for Dialog Applications. LaMDA is a family of
Transformer-based neural language models specialized for dialog, which have up to 137B …
Transformer-based neural language models specialized for dialog, which have up to 137B …
On the opportunities and risks of foundation models
AI is undergoing a paradigm shift with the rise of models (eg, BERT, DALL-E, GPT-3) that are
trained on broad data at scale and are adaptable to a wide range of downstream tasks. We …
trained on broad data at scale and are adaptable to a wide range of downstream tasks. We …
On the dangers of stochastic parrots: Can language models be too big?🦜
EM Bender, T Gebru, A McMillan-Major… - Proceedings of the 2021 …, 2021 - dl.acm.org
The past 3 years of work in NLP have been characterized by the development and
deployment of ever larger language models, especially for English. BERT, its variants, GPT …
deployment of ever larger language models, especially for English. BERT, its variants, GPT …
Auto-debias: Debiasing masked language models with automated biased prompts
Human-like biases and undesired social stereotypes exist in large pretrained language
models. Given the wide adoption of these models in real-world applications, mitigating such …
models. Given the wide adoption of these models in real-world applications, mitigating such …
Realtoxicityprompts: Evaluating neural toxic degeneration in language models
Pretrained neural language models (LMs) are prone to generating racist, sexist, or otherwise
toxic language which hinders their safe deployment. We investigate the extent to which …
toxic language which hinders their safe deployment. We investigate the extent to which …
Five sources of bias in natural language processing
D Hovy, S Prabhumoye - Language and linguistics compass, 2021 - Wiley Online Library
Recently, there has been an increased interest in demographically grounded bias in natural
language processing (NLP) applications. Much of the recent work has focused on describing …
language processing (NLP) applications. Much of the recent work has focused on describing …