The Dangers of Stochastic Parrots: Can Language Models Be Too Big?
URI: https://gptkb.org/entity/The_Dangers_of_Stochastic_Parrots%3A_Can_Language_Models_Be_Too_Big%3F
GPTKB entity
Statements (69)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:Research_Institute
|
| gptkbp:bfsLayer |
4
|
| gptkbp:bfsParent |
gptkb:Open_AI
|
| gptkbp:addresses |
public perception of AI technology
|
| gptkbp:advocates_for |
responsible AI practices
transparency in AI training data |
| gptkbp:analyzes |
impact of AI on employment
impact on marginalized communities effects of AI on creativity effects of AI on social justice impact of AI on privacy rights relationship between AI and ethics relationship between AI and human rights |
| gptkbp:author |
gptkb:Emily_Bender
gptkb:Timnit_Gebru |
| gptkbp:calls_for |
diversity in AI research teams
increased collaboration between academia and industry greater accountability in AI systems greater awareness of AI's limitations greater diversity in AI datasets increased funding for AI ethics research more inclusive AI research practices more research on AI's societal impact |
| gptkbp:discusses |
data privacy concerns
importance of interdisciplinary research challenges in AI regulation environmental impact of training large models impact of AI on cultural norms impact of AI on democracy importance of ethical frameworks in AI research potential for misuse of AI technology role of AI in shaping future technologies role of AI in shaping public discourse |
| gptkbp:emphasizes |
importance of explainability in AI
|
| gptkbp:ends_at |
need for interdisciplinary approaches
|
| gptkbp:examines |
ethical considerations in AI deployment
ethical dilemmas in AI development impact of AI on global issues. potential biases in AI algorithms potential for AI to reinforce stereotypes relationship between AI and human values role of AI in decision making role of AI in education role of AI in society social consequences of AI language models |
| gptkbp:explores |
future of AI language models
|
| gptkbp:focuses_on |
ethical implications of large language models
|
| gptkbp:highlights |
need for ethical guidelines
bias in language models importance of ethical leadership in AI development need for ethical considerations in AI design need for ethical oversight in AI projects need for ethical training in AI education need for public engagement in AI policy importance of stakeholder engagement in AI development |
| gptkbp:is_cited_in |
previous work on AI accountability
|
| gptkbp:is_criticized_for |
lack of transparency in AI development
|
| gptkbp:proposed_by |
regulatory frameworks for AI
strategies for ethical AI implementation collaborative approaches to AI ethics framework for ethical AI development framework for evaluating AI systems guidelines for responsible AI use strategies for mitigating AI risks |
| gptkbp:published_by |
Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency
|
| gptkbp:published_year |
gptkb:2021
|
| gptkbp:suitable_for |
collaboration between technologists and ethicists
|
| gptkbp:user_reviews |
existing literature on AI ethics
|
| gptkbp:visitors |
scalability of AI models
|