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Advanced Driver Assistance Systems and Animals

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Abstract

Advanced driver assistance systems are widely used. Some support and inform the driver. Others relieve him or her of certain tasks—and transform the human-guided system into a semi-autonomous one. For some years also fully autonomous systems have been on the roads, so-called self-driving cars, as prototypes of companies and within research projects. From the perspective of ethics—both of the special fields of ethics like animal ethics, information ethics and technology ethics and of machine ethics which can be understood as a counterpart to human ethics—advanced driver assistance systems raise various questions. The aim of this paper is to derive suggestions from animal ethics and other disciplines for the improvement and development of the systems. The basis are literature analysis and own classifications and considerations. The result is that there are many possibilities to expand existing systems and to develop new functions in the context with the aim to reduce the number of animal victims.

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Notes

  1. The term “car IT” means not only ADAS, but also navigation systems and dashboard cameras (dashcams) [18].

  2. A central publication in this field is “Machine Ethics” by Michael and Susan Leigh Anderson as editors [1]. Important is also “Moral Machines” by Wallach and Allen [33]. With respect to “Machine Ethics”, it can be said in summation that some authors refer critically to Isaac Asimov and his famous Three Laws of Robotics and reflect upon the basic meanings and implications of machine ethics. Some authors discuss deontological or teleological normative models with respect to the use for machine morality. James Gips focusses on virtue ethics. Bruce M. McLaren promotes a case-based reasoning, and Marcello Guarini gives a neural network approach.

  3. We are not going to discuss problematic terms and concepts of machine ethics in depth. In its brief existence, this young discipline has produced many articles and books related to these issues. As examples we mention [1] as well as [33].

  4. Bentham wrote in “An Introduction to the Principles of Morals and Legislation”: “The question is not, Can they reason? nor Can they talk? but, Can they suffer?” [14].

  5. A team around Dah-Jye Lee has developed an algorithm suitable for distinguishing between species: “The team has also tested their algorithm on a dataset of fish images from BYU’s biology department that included photos of four species: Yellowstone cutthroat, cottid, speckled dace and whitefish. The algorithm was able to distinguish between the species with 99.4 % accuracy.” [20].

  6. We would like to emphasize here that these facts do not automatically lead to decisions. They can be a part of the chain of reasoning, and the needs and priorities of engineers, producers and customers must be weighed up against each other.

  7. Such traffic signs are elements of the gamification of road traffic. This approach plays a part in many contexts, for example in learning and marketing. An interesting feature is that the smileys are signs used in computer-based communication and understood not only by humans, but by machines as well.

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  1. School of Business, Institute for Information Systems, University of Applied Sciences and Arts Northwestern Switzerland FHNW, Bahnhofstrasse 6, 5210, Windisch, Switzerland

    Oliver Bendel

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Bendel, O. Advanced Driver Assistance Systems and Animals. Künstl Intell 28, 263–269 (2014). https://doi.org/10.1007/s13218-014-0332-1

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