Machine Learning for Safety-Critical Applications: Opportunities, Challenges, and a Research Agenda (2025)

Chapter: 2 State of the Art, Promises, and Risks of Machine Learning

Previous Chapter: 1 Engineering Safety-Critical Systems in the Age of Machine Learning
Suggested Citation: "2 State of the Art, Promises, and Risks of Machine Learning." National Academies of Sciences, Engineering, and Medicine. 2025. Machine Learning for Safety-Critical Applications: Opportunities, Challenges, and a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/27970.
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Suggested Citation: "2 State of the Art, Promises, and Risks of Machine Learning." National Academies of Sciences, Engineering, and Medicine. 2025. Machine Learning for Safety-Critical Applications: Opportunities, Challenges, and a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/27970.
Page 29
Suggested Citation: "2 State of the Art, Promises, and Risks of Machine Learning." National Academies of Sciences, Engineering, and Medicine. 2025. Machine Learning for Safety-Critical Applications: Opportunities, Challenges, and a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/27970.
Page 30
Suggested Citation: "2 State of the Art, Promises, and Risks of Machine Learning." National Academies of Sciences, Engineering, and Medicine. 2025. Machine Learning for Safety-Critical Applications: Opportunities, Challenges, and a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/27970.
Page 31
Suggested Citation: "2 State of the Art, Promises, and Risks of Machine Learning." National Academies of Sciences, Engineering, and Medicine. 2025. Machine Learning for Safety-Critical Applications: Opportunities, Challenges, and a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/27970.
Page 32
Suggested Citation: "2 State of the Art, Promises, and Risks of Machine Learning." National Academies of Sciences, Engineering, and Medicine. 2025. Machine Learning for Safety-Critical Applications: Opportunities, Challenges, and a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/27970.
Page 33
Suggested Citation: "2 State of the Art, Promises, and Risks of Machine Learning." National Academies of Sciences, Engineering, and Medicine. 2025. Machine Learning for Safety-Critical Applications: Opportunities, Challenges, and a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/27970.
Page 34
Suggested Citation: "2 State of the Art, Promises, and Risks of Machine Learning." National Academies of Sciences, Engineering, and Medicine. 2025. Machine Learning for Safety-Critical Applications: Opportunities, Challenges, and a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/27970.
Page 35
Suggested Citation: "2 State of the Art, Promises, and Risks of Machine Learning." National Academies of Sciences, Engineering, and Medicine. 2025. Machine Learning for Safety-Critical Applications: Opportunities, Challenges, and a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/27970.
Page 36
Suggested Citation: "2 State of the Art, Promises, and Risks of Machine Learning." National Academies of Sciences, Engineering, and Medicine. 2025. Machine Learning for Safety-Critical Applications: Opportunities, Challenges, and a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/27970.
Page 37
Suggested Citation: "2 State of the Art, Promises, and Risks of Machine Learning." National Academies of Sciences, Engineering, and Medicine. 2025. Machine Learning for Safety-Critical Applications: Opportunities, Challenges, and a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/27970.
Page 38
Suggested Citation: "2 State of the Art, Promises, and Risks of Machine Learning." National Academies of Sciences, Engineering, and Medicine. 2025. Machine Learning for Safety-Critical Applications: Opportunities, Challenges, and a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/27970.
Page 39
Suggested Citation: "2 State of the Art, Promises, and Risks of Machine Learning." National Academies of Sciences, Engineering, and Medicine. 2025. Machine Learning for Safety-Critical Applications: Opportunities, Challenges, and a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/27970.
Page 40
Suggested Citation: "2 State of the Art, Promises, and Risks of Machine Learning." National Academies of Sciences, Engineering, and Medicine. 2025. Machine Learning for Safety-Critical Applications: Opportunities, Challenges, and a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/27970.
Page 41
Suggested Citation: "2 State of the Art, Promises, and Risks of Machine Learning." National Academies of Sciences, Engineering, and Medicine. 2025. Machine Learning for Safety-Critical Applications: Opportunities, Challenges, and a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/27970.
Page 42
Suggested Citation: "2 State of the Art, Promises, and Risks of Machine Learning." National Academies of Sciences, Engineering, and Medicine. 2025. Machine Learning for Safety-Critical Applications: Opportunities, Challenges, and a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/27970.
Page 43
Suggested Citation: "2 State of the Art, Promises, and Risks of Machine Learning." National Academies of Sciences, Engineering, and Medicine. 2025. Machine Learning for Safety-Critical Applications: Opportunities, Challenges, and a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/27970.
Page 44
Suggested Citation: "2 State of the Art, Promises, and Risks of Machine Learning." National Academies of Sciences, Engineering, and Medicine. 2025. Machine Learning for Safety-Critical Applications: Opportunities, Challenges, and a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/27970.
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Next Chapter: 3 System Engineering with Machine Learning Components for Safety-Critical Applications
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