Defining AI in Policy versus Practice
December 23, 2019 Β· Declared Dead Β· π AAAI/ACM Conference on AI, Ethics, and Society
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
P. M. Krafft, Meg Young, Michael Katell, Karen Huang, Ghislain Bugingo
arXiv ID
1912.11095
Category
cs.CY: Computers & Society
Cross-listed
cs.AI,
cs.LG,
physics.soc-ph
Citations
97
Venue
AAAI/ACM Conference on AI, Ethics, and Society
Last Checked
4 months ago
Abstract
Recent concern about harms of information technologies motivate consideration of regulatory action to forestall or constrain certain developments in the field of artificial intelligence (AI). However, definitional ambiguity hampers the possibility of conversation about this urgent topic of public concern. Legal and regulatory interventions require agreed-upon definitions, but consensus around a definition of AI has been elusive, especially in policy conversations. With an eye towards practical working definitions and a broader understanding of positions on these issues, we survey experts and review published policy documents to examine researcher and policy-maker conceptions of AI. We find that while AI researchers favor definitions of AI that emphasize technical functionality, policy-makers instead use definitions that compare systems to human thinking and behavior. We point out that definitions adhering closely to the functionality of AI systems are more inclusive of technologies in use today, whereas definitions that emphasize human-like capabilities are most applicable to hypothetical future technologies. As a result of this gap, ethical and regulatory efforts may overemphasize concern about future technologies at the expense of pressing issues with existing deployed technologies.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Computers & Society
π
π
The Cartographer
R.I.P.
π»
Ghosted
Artificial Intelligence: the global landscape of ethics guidelines
R.I.P.
π»
Ghosted
The role of artificial intelligence in achieving the Sustainable Development Goals
R.I.P.
π»
Ghosted
Green AI
R.I.P.
π»
Ghosted
Principles alone cannot guarantee ethical AI
R.I.P.
π»
Ghosted
Tackling Climate Change with Machine Learning
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted