SESAR is defining a new air traffic management system, with new technologies and high automation levels, for instance, systems that perform actions without explicit human intervention. Those will cause changes in the allocation of liability mainly on the operators. Some allocation issues, such as those concerning the relation between humans and automated systems, likely common in the future, are not contemplated in the current legal system. It is necessary to characterise to what extent new automatic tools may shift liability for accidents from operators to technology, namely from operators to manufacturers, organisations and system developers. Particular attention deserves the liability for software mistake, crucial for safety-critical systems, such as ATM. Additional layers of complexity are added by automatic and autonomous systems and hybrid man-machine units. This paper outlines the modeling framework that will be adopted in the ALIAS project (Addressing Liability Impact of Automated Systems), based on describing ATM as a socio-technical system. In such a system both technical and social aspects (humans and norms) are crucial for design and functioning, and the allocation of liabilities may be viewed as a governance-mechanism enabling the enhancement of the functioning of ATM. This will lead to the development of a methodological tool to support the introduction of any technology in complex systems, particularly in ATM, ensuring to take all the relevant legal aspects into consideration at the right stage of the design, development and deployment process.
Automation and liability in ATM as fundamental issues in socio-technical systems
CONTISSA, GIUSEPPE;SARTOR, GIOVANNI;
2011
Abstract
SESAR is defining a new air traffic management system, with new technologies and high automation levels, for instance, systems that perform actions without explicit human intervention. Those will cause changes in the allocation of liability mainly on the operators. Some allocation issues, such as those concerning the relation between humans and automated systems, likely common in the future, are not contemplated in the current legal system. It is necessary to characterise to what extent new automatic tools may shift liability for accidents from operators to technology, namely from operators to manufacturers, organisations and system developers. Particular attention deserves the liability for software mistake, crucial for safety-critical systems, such as ATM. Additional layers of complexity are added by automatic and autonomous systems and hybrid man-machine units. This paper outlines the modeling framework that will be adopted in the ALIAS project (Addressing Liability Impact of Automated Systems), based on describing ATM as a socio-technical system. In such a system both technical and social aspects (humans and norms) are crucial for design and functioning, and the allocation of liabilities may be viewed as a governance-mechanism enabling the enhancement of the functioning of ATM. This will lead to the development of a methodological tool to support the introduction of any technology in complex systems, particularly in ATM, ensuring to take all the relevant legal aspects into consideration at the right stage of the design, development and deployment process.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
