Power to the people? Opportunities and challenges for participatory AI
Participatory approaches to artificial intelligence (AI) and machine learning (ML) are gaining
momentum: the increased attention comes partly with the view that participation opens the …
momentum: the increased attention comes partly with the view that participation opens the …
Can HR adapt to the paradoxes of artificial intelligence?
A Charlwood, N Guenole - Human Resource Management …, 2022 - Wiley Online Library
Artificial intelligence (AI) is widely heralded as a new and revolutionary technology that will
transform the world of work. While the impact of AI on human resource (HR) and people …
transform the world of work. While the impact of AI on human resource (HR) and people …
Holistic evaluation of language models
Language models (LMs) are becoming the foundation for almost all major language
technologies, but their capabilities, limitations, and risks are not well understood. We present …
technologies, but their capabilities, limitations, and risks are not well understood. We present …
Taxonomy of risks posed by language models
Responsible innovation on large-scale Language Models (LMs) requires foresight into and
in-depth understanding of the risks these models may pose. This paper develops a …
in-depth understanding of the risks these models may pose. This paper develops a …
Auditing large language models: a three-layered approach
Large language models (LLMs) represent a major advance in artificial intelligence (AI)
research. However, the widespread use of LLMs is also coupled with significant ethical and …
research. However, the widespread use of LLMs is also coupled with significant ethical and …
Improving language models by retrieving from trillions of tokens
We enhance auto-regressive language models by conditioning on document chunks
retrieved from a large corpus, based on local similarity with preceding tokens. With a 2 …
retrieved from a large corpus, based on local similarity with preceding tokens. With a 2 …
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 …
The pile: An 800gb dataset of diverse text for language modeling
L Gao, S Biderman, S Black, L Golding… - arXiv preprint arXiv …, 2020 - arxiv.org
Recent work has demonstrated that increased training dataset diversity improves general
cross-domain knowledge and downstream generalization capability for large-scale …
cross-domain knowledge and downstream generalization capability for large-scale …
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 …