Human and Organizational Factors in AI Risk Management Proceedings of a Workshop (2025) / Chapter Skim
Currently Skimming:
3 Safety in Context
3 Safety in Context
Pages 22-30
The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.
From page 22... ...
Behrend offered an example of societal factors causing unintended negative impacts by describing the context and result of an AI-based surgical training. According to Behrend, students engaging in the training feared making mis takes that would be recorded by the training system.
|
From page 23... ...
Nguyen stated that governance agencies adopting AI tools play a unique role; they are in the position to make immediate changes in standards based on the risks that they surface. Missy Cummings, George Mason University, defined safety as the freedom from risk.
|
From page 24... ...
Prompted by Elish, the panelists discussed independent oversight strategies. Cummings argued that AI applications that can result in human injury or death should require oversight by a government entity.
|
From page 25... ...
To design tools that instead enhance worker efficiency, Nguyen stated, organizations should consider workers' rights organizations, professional organizations, and unions, which provide a clearer vision of worker needs as well as consequences of digital investments. Elish called attention to the popular phrase "human in the loop." Elish asked the panelists to expand on the challenges that impact the phrase.
|
From page 26... ...
Other subjects of risk mitigation often depend on spontaneous reporting, resulting in less harm reduction than desired. Bates expressed optimism for automated harm detection, which might in the future unearth safety concerns that currently struggle to be acknowledged.
|
From page 27... ...
In 2011, the National Institute for Occupational Safety and Health created a program called Total Worker Health to protect workers from harm and promote healthy habits. The job demand resource model and the job demand control model are examples of safety frameworks within the field of occupational psychology that identify risk factors related to demand, resources, and control.
|
From page 28... ...
Banks described an organization replacing ineffective pre-meetings with one person col lecting worker sentiment data and using ML to identify gaps, regularities, and common alities. This approach considered the needs of workers, impactful applications of new technology, and incentives workers might have to engage with the tool such as remov ing the ineffective meeting and identifying subjects that need further discussion.
|
From page 29... ...
Dorothy Carter, Michigan State University, expressed optimism for AI enabled risk mitigation in future National Aeronautics and Space Administration (NASA) missions to the Moon and Mars.
|
From page 30... ...
Behrend asked the panelists about concerns regarding trust development, inter disciplinary learning, and team functioning as humans begin to interface with machines more than each other. Carter argued that AI could help optimize knowledge transfer in multiteam systems by organizing groups around who has the proper expertise to solve a given problem.
|
Key Terms
This material may be derived from roughly machine-read images, and so is provided only to facilitate research.
More
information on Chapter Skim is available.