NeuralDoc-Automating Code Translation Using Machine Learning

Harsha, S.; Sohoni, Aditya; Chandrasekaran, K.

doi:10.1007/978-981-16-6940-8_11

Cited by 2 publications

(1 citation statement)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Public compute resources should be compatible and interoperable with a wide range of models and software packages, in order to support the range of research projects that would be conducted. System performance can vary considerably depending on the hardware and software on which it is run (Nelaturu et al, 2023;Gundersen et al, 2022), and common ML software frameworks can lose more than 40% of their key functionality when ported to non-native hardware (Mince et al, 2023). Future research could aim to propose solutions that address these observed defects.…”

Section: Open Problemsmentioning

confidence: 99%

AI Governance Multi-stakeholder Convening

Greene

2022

The Oxford Handbook of AI Governance

View full text Add to dashboard Cite

This chapter offers reflections and advice on AI ethics and governance from a year spent leading Partnership on AI’s multi-stakeholder Affective Computing and Ethics project, involving more than 200 engineers, scientists, lawyers, privacy and civil rights advocates, bioethicists, managers, executives, journalists, and government officials, mostly in the United States, United Kingdom, and European Union, in discussions about AI related to emotion and affect and its potential impacts on civil and human rights, with a goal of developing industry best practices and better technology policy. The author’s reflections from that year draw lessons on convening, multi-disciplinary collaboration, and affective computing and AI ethics and governance. The chapter offers a blueprint for creating the shared knowledge foundation non-technical participants need to apply their expertise. It presents question exploration as a tool for evaluating ethics risk and using “What is notice good for?” shows how a well-chosen question can serve as a catalyst for group or individual exploration of the issues, leading to insights and answers. It includes a curated list of 42 questions, catalysts for AI and ethics discussion for industry, university, news media, and policy teams; multi-disciplinary, multi-stakeholder AI ethics and governance convenings; and for individual writing and thinking, to take scholars and practitioners a step beyond or to the side of what they have been thinking about—about AI and ethics.

show abstract

Section: Open Problemsmentioning

confidence: 99%