Fetching the paper…
Reading the bibliography…
Although artificial intelligence (AI) is solving real-world challenges and transforming industries, there are serious concerns about its ability to behave and make decisions in a responsible way.
Capability maturity model
M.C. Paulk et al. 1993 · 1993
Earlier work this paper cites.
Software Architecture in Practice
L. Bass, P. Clements, and R. Kazman. 2003 · 2003
Earlier work this paper cites.
Basic Concepts and Taxonomy of Dependable and Secure Computing
A. Avizienis et al. 2004 · 2004
Earlier work this paper cites.
Generating Complete, Unambiguous, and Verifiable Requirements from Stories, Scenarios, and Use Cases
D. Firesmith. 2004 · 2004
Earlier work this paper cites.
YouTube Video Recommendations
YouTube. 2005 · 2005
Earlier work this paper cites.
Using thematic analysis in psychology
V. Braun and V. Clarke. 2006 · 2006
Earlier work this paper cites.
H2O Driverless AI
H20.ai. 2011 · 2011
Earlier work this paper cites.
ISO/IEC25010:2011 systems and software engineering–systems and software quality requirements and evaluation (square)–system and software quality models
ISO. 2011 · 2011
Earlier work this paper cites.
UML based Security Function Policy Verification Method for Requirements Specification. In COMPSAC’13 . 832–833
A. Noro and S. Matsuura. 2013 · 2013
Earlier work this paper cites.
Pachyderm: The Data Foundation for Machine Learning
Pachyderm. 2014 · 2014
Earlier work this paper cites.
AWS Machine Learning
AWS. 2015 · 2015
Earlier work this paper cites.
Azure Machine Learning
Microsoft. 2015 · 2015
Earlier work this paper cites.
Hidden Technical Debt in Machine Learning Systems. In NIPS’15 . 2503–2511
D. Sculley et al. 2015 · 2015
Earlier work this paper cites.
Tesla autopilot
Tesla. 2015 · 2015
Earlier work this paper cites.
neptune.ai
Neptune. 2016 · 2016
Earlier work this paper cites.
National Certification Scheme
NHMRC. 2016 · 2016
Earlier work this paper cites.
Amazon SageMaker
AWS. 2017 · 2017
Earlier work this paper cites.
CARLA: An Open Urban Driving Simulator. In Proceedings of the 1st Annual Conference on Robot Learning (PMLR, Vol. 78) , S. Levine, V. Vanhoucke, and K. Goldberg (Eds.). PMLR, 1–16
A. Dosovitskiy et al. 2017 · 2017
Earlier work this paper cites.
TensorFlow Extended
TensorFlow. 2017 · 2017
Earlier work this paper cites.
The Case for an Ethical Black Box. In Towards Autonomous Robotic Systems . 262–273
A. Winfield and M. Jirotka. 2017 · 2017
Earlier work this paper cites.
How Modern News Aggregators Help Development Communities Shape and Share Knowledge. In ICSE’18 . 499–510
M. Aniche et al. 2018 · 2018
Earlier work this paper cites.
Baidu Apollo minibus
Baidu. 2018 · 2018
Earlier work this paper cites.
Data Statements for Natural Language Processing
E. Bender and B. Friedman. 2018 · 2018
Earlier work this paper cites.
IBM AI Fairness 360
IBM. 2018 · 2018
Earlier work this paper cites.
Watson Studio
IBM. 2018 · 2018
Cited alongside, same era.
Kubeflow
Kubeflow. 2018 · 2018
Cited alongside, same era.
Operationalizing Human Values in Software: A Research Roadmap. In ESEC/FSE’18 . 780–784
D. Mougouei et al. 2018 · 2018
Cited alongside, same era.
XAI - An eXplainability toolbox for machine learning
A. Saucedo, U. Iqbal, and S. Krishna. 2018 · 2018
Cited alongside, same era.
Black Box Fairness Testing of Machine Learning Models. In ESEC/FSE’19 . 625–635
A. Aggarwal et al. 2019 · 2019
Cited alongside, same era.
Amazon SageMaker Model Monitor
AWS. 2019 · 2019
Cited alongside, same era.
From Efficiency to Effectiveness: Delivering Business Value Through Software. In Software Business . 3–10
Improving reproducibility in machine learning research
J. Pineau et al. 2020 · 2020
Later among the works it cites.
Explainability Fact Sheets: A Framework for Systematic Assessment of Explainable Approaches. In FAT’20 . 56––67
K. Sokol and P. Flach. 2020 · 2020
Later among the works it cites.
LinkedIn Fairness Toolkit (LiFT)
S. Vasudevan and K. Kenthapadi. 2020 · 2020
Later among the works it cites.
Fairness Testing of Machine Learning Models Using Deep Reinforcement Learning. In TrustCom’20 . 121–128
W. Xie and P. Wu. 2020 · 2020
Later among the works it cites.
Amazon Product Recommendations
Amazon. 2021 · 2021
Closest in time.
National AI Engineering Initiative
H. Barmer et al. 2021 · 2021
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
J. Bosch. 2019 · 2019
Cited alongside, same era.
LEAF: A Benchmark for Federated Settings
S. Caldas et al. 2019 · 2019
Cited alongside, same era.
Explainable AI
Google. 2019 · 2019
Cited alongside, same era.
Non-Functional Requirements for Machine Learning: Challenges and New Directions. In RE’19 . 386–391
J. Horkoff. 2019 · 2019
Cited alongside, same era.
The global landscape of AI ethics guidelines
A. Jobin, M. Ienca, and E. Vayena. 2019 · 2019
Cited alongside, same era.
FactSheets: Increasing trust in AI services through supplier’s declarations of conformity
Arnold et al. M. 2019 · 2019
Cited alongside, same era.
Legal requirements on explainability in machine learning
A. Bibal et al. 2021 · 2021
Closest in time.
Building resilient medical technology supply chains with a software bill of materials
S. Carmody et al. 2021 · 2021
Closest in time.
Australia’s AI Ethics Principles
DISER (Australian Government). 2020 · 2021
Closest in time.
Governing AI safety through independent audits
G. Falco et al. 2021 · 2021
Closest in time.
Software Architecture Challenges in ML Systems. In ICSME’21 - NIER Track
G. Lewis, I. Ozkaya, and X. Xu. 2021 · 2021
Closest in time.
Human Perceptions on Moral Responsibility of AI. In CHI ’21
G. Lima, N. Grgić-Hlača, and M. Cha. 2021 · 2021
Closest in time.
sigstore
Linux Foundation. 2021 · 2021
Closest in time.
FLRA: A Reference Architecture for Federated Learning Systems. In Software Architecture . Springer International Publishing, Cham, 83–98
Sin Kit Lo, Qinghua Lu, Hye-Young Paik, and Liming Zhu. 2021 · 2021
Closest in time.
A Survey on Bias and Fairness in Machine Learning
N. Mehrabi et al. 2021 · 2021
Closest in time.
Software Architecture for ML-based Systems: What Exists and What Lies Ahead. In WAIN’21
H. Muccini and K. Vaidhyanathan. 2021 · 2021
Closest in time.
NVIDIA DRIVE Sim - Powered by Omniverse
NVIDIA. 2021 · 2021
Closest in time.
Tools for trustworthy AI
OECD. 2021 · 2021
Closest in time.
Artificial Intelligence Market Size, Share & Trends Analysis Report
Grand View Research. 2021 · 2021
Closest in time.
The Minimum Elements For a Software Bill of Materials (SBOM)
The United States Department of Commerce. 2021 · 2021
Closest in time.
Responsible AI and moral responsibility: a common appreciation
D. W. Tigard. 2021 · 2021
Closest in time.
Ethics and Governance of Artificial Intelligence Evidence from a Survey of Machine Learning Researchers
B. Zhang et al. 2021 · 2021
Closest in time.
AI and Ethics - Operationalising Responsible AI
L. Zhu et al. 2021 · 2021
Closest in time.