Impact Of Driverless Cars On Australia's Economy: Ethical And Business Essay.

Utilitarianism and the Role of Automobile Industry

Question:

How Driverless Trucks Could Change Australia?

The case scenario demonstrates how the current infrastructure of advanced information technology is getting positively as well as negatively impacted with the innovation of driverless cars. This is referred to as one of the most exciting and advanced technologies within the horizon that could have terrible consequences for Australia’s ripping communities. From the consideration of the business aspects it has been found that, driverless car or self driving car is an automated technology that is basically a robotic vehicle (Driverless-trucks, 2017). Without the help of the human intervention a vehicle must be able to navigate it as a qualifying one. The intervention is a preliminarily determined destination over the roads which is not been adopted for its general usage. The technology is beneficial because it reduces the pressure from the human and the efficiency of a machine always stands greater than man power. Though, designs of this kind of machines are costlier than the traditional one but due to its operational excellence, most of the large vehicle manufacturing companies have started designing these self driving cars.

Utilitarianism is the theory that provides maximized utility to the actions. Since last 7 to 8 years the automobile industries have become a source of economic growth and innovation in Australia ()Bojarski et al., 2016). The capability of driving has become a symbol for mobility and independence which spans the generation.

 Automobile industries bring effective profits in the society by playing innovative as well as significant roles. Through, the rate of inefficiency is increasing that is relevant to the automobile usability is continuously staggering. There are many manufacturing agencies that have made self driving cars a reality.  The self driving cars or an intelligent car works with all the preliminarily determined activities and operations as well. The additional technologies include self steering, LIDAR, GPS, DGPS and digital maps (Brett 2016). In order to track different objectives in the mid road or road side, the automated steering system is found to be very much beneficial.  The steering system holds a camera as well. The optical remote sensing technology is also used by the automated car development department. With the help of the GPS tracker the automated car developing system will be able to understand about the detail track through which the car might driver to send the consumers to their desired destination.

Deontology theory is referred to as normative ethical position that helps to judge the morality o different actions. Though this innovative technology helps the business owners to gain effective benefit from the marketplace but at the same time name ethical and non ethical aspects are also associated to this technology those might affect the general operation and functional flow of the automotive car manufacturing company (Howard and Dai 2014). The operational and functional requirements of the self driving cars are similar to the traditional cars like the self driving cars also run with the help of petrol (Hee Lee, Faundorfer and Pollefeys 2013). However, the Tesla car manufacturing company manufactures cars that run through the help of solar energy. After analyzing the features of the self driving cars it has been found that, the future of the self driving is under broad question.

Self-Driving Cars and Technological Advancements

In the self driving technology of Australia, vast amount of ethical challenges and questions are present.  As this kind of cars are operated with the help of technology only thus if the technology fails then accidents might occur. The self driving cars use radar sensor to detect the mod road obstacles (Boeglin 2015). However, if the technology fails working then it will not be able to identify the obstacles and thus accident also might occur.

Virtue ethical theory is referred to as one of the most major normative approaches. In the self driving technology the affected people might be both the passengers and the professional car or truck drivers. With the increasing number of self driving cars the numbers of requirements for the drivers are also getting reduced (Azmat, Schuhmayer and Kummer 2016). From a wide area survey in Australia it has been found that, many fatal crash have been occurred in Australia with the self driving cars. Complete dependency over technology is very much difficult like if the technology fails then there will no one to detect the obstacles in the path. Again in the middle of the path if the passengers need to change their destination then that will also be a difficult job for the technology (Driverless-trucks, 2017). A fully driverless car is replacing the professional drivers thus they are losing their job which is a big ethical issue from the business aspect. Professional theories and professional automated car driving applications are required to be applied by the system developers (Chen et al., 2017). Again ultrasonic sensors are also there those are widely used by the manufacturers. If the self driving cars become a norm in Australia then, another ethical concern associated to loss of job might occur.

Contract theory is the study of the way individuals and businesses construct and develop legal agreements. According to this theory, the ethical issues associated to the technology called self driving car is number of job loss of the professional drivers. As the number of self driving car gets increases in Australia, the manpower of the country will also get affected negatively. Lack of proper programming will interrupt the general application flow of the system. With the application of this innovative technology the requirement of human or manpower will get reduced which is beneficial for the business owners but at the same time sudden job loss is unethical.

If the technology is increasing everyday and according to that the numbers of drivers are getting reduced everyday then that is a biggest issue for the economy of Australia. If the self driving car does not require drivers then, at least for other applications like security etc it is necessary to hire human power (Driverless-trucks, 2017). However, no such law in invented by the ministry of Australia but it has been found that job loss is a serious issue that is needed to be resolved by the Australian Government very soon. The people who are losing their jobs must get another job sooner to avoid depression and disappointment.

Ethical Concerns with Self-Driving Cars

Conclusion

Technology is a gift to the society but at the same time improper application of the advanced technology can come as a curse. Proper programming technology should be incorporated to the system so that the technical issues associated to this self driving system might get minimized.  Both in large hotels and motels the self driving cars are used and wily accepted.  Well known car service providing companies like UBER, is also currently giving wide opportunities to the consumers with the advanced automated car or self driving cars.  Security of confidential data is a very perspective that is strictly required for the self driving cars. Again, sensor is another important thing that also needed to be incorporated to reduce the rate of unfortunate accidents. 

In the self driving car technology all the necessary applications are served by the advanced technology only. If, any such issues occur associated to the technology then, that could hamper the confidentiality of both the service providers and the passengers as well. In order to mitigate the security related issues it is necessary to adopt proper security technologies so that the financial personnel details of the passengers and employees do not get hijacked by the external attackers. Among these different technologies encryption and firewall and the advanced sensors are required to be installed so that, the security aspects could be maintained.

References

Azmat, M., Schuhmayer, C. and Kummer, S., 2016, May. Innovation in mobility: Austrian expert's perspective on the future of urban mobility with self-driving cars. In Innovation Arabia 9: Quality and Business Management Conference (Business Innovation-Imperative for knowledge Economy) (Vol. 9, pp. 142-160). HBMSU Publishing House.

Boeglin, J., 2015. The costs of self-driving cars: reconciling freedom and privacy with tort liability in autonomous vehicle regulation. Yale JL & Tech., 17, p.171.

Bojarski, M., Del Testa, D., Dworakowski, D., Firner, B., Flepp, B., Goyal, P., Jackel, L.D., Monfort, M., Muller, U., Zhang, J. and Zhang, X., 2016. End to end learning for self-driving cars. arXiv preprint arXiv:1604.07316.

Brett, J.A., 2016. Thinking Local about Self-Driving Cars: A Local Framework for Autonomous Vehicle Development in the United States (Doctoral dissertation).

Chen, S., Zhang, S., Shang, J., Chen, B. and Zheng, N., 2017. Brain Inspired Cognitive Model with Attention for Self-Driving Cars. arXiv preprint arXiv:1702.05596.

Driverless-trucks (2017). The jobs killer is coming. [online] NewsComAu. Available at: https://www.news.com.au/finance/business/travel/the-jobs-killer-is-coming-how-driverless-trucks-could-change-australia/news-story/4f5b8a42b0452703d62e00f3e7644d7b [Accessed 14 Sep. 2017].

Hee Lee, G., Faundorfer, F. and Pollefeys, M., 2013. Motion estimation for self-driving cars with a generalized camera. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 2746-2753).

Howard, D. and Dai, D., 2014. Public perceptions of self-driving cars: The case of Berkeley, California. In Transportation Research Board 93rd Annual Meeting (Vol. 14, No. 4502).

Kohl, C., Mostafa, D., Böhm, M. and Krcmar, H., 2017. Disruption of Individual Mobility Ahead? A Longitudinal Study of Risk and Benefit Perceptions of Self-Driving Cars on Twitter.

Yang, J. and Coughlin, J.F., 2014. In-vehicle technology for self-driving cars: Advantages and challenges for aging drivers. International Journal of Automotive Technology, 15(2), pp.333-340.