ISY1000 Ethical Decisions in Software Development Assignment Sample

• Subject Code : ISY1000
• University : Australian Institute of Higher Education My Assignment Services is not sponsored or endorsed by this college or university.
• Subject Name : IT Computer Science

How Safe Are Self-Driven Cars

Executive Summary of Ethical Decisions in Software Development 

This document discusses the ethics and the ethical decisions that need to be incorporated in Software Development from time to time based on the requirements. The software developer being serving the society at large and following the ethics of programming the software thereby, developing a robust and an efficient program.

As an instance, suppose a software solution has been developed to serve the Human Resource Management system for any organization. This solution can be used by different organizations by just putting in the business rules in the customized settings section of the software. The module will help manage the Human Resources related functions within the same environment.

The program is thus beneficial to serve the society (the business purposes) and the programmer or the software developer is a contributor to the society.

Table of Contents

Introduction.

Code of Ethics and the reason for such incorporation.

Principles for software engineering code of ethics.

Considering the scenario for Self Driving Cars.

The Future of self driving cars.

Risks involved.

Conclusion.

References (Harvard Referencing)

Introduction to Ethical Decisions in Software Development

Ethics is a general term that signifies a set of common rules or regulations that are defined to be followed for serving a particular purpose with fulfillment and desire. Similarly in software technology, ethics is a set of principles followed to overcome a problem using a software based solution working in a team (De Los Reyes Jr et al. 2017). No matter what the problem is the solution is always developed based on a common set of ethics. By professional ethics we understand adjusting or working in a managed solution.

Associated with ethics is another important term called Ethical. The word Ethical is termed to define the good or bad intention of the software developer or any external technologist to intentionally scratch, corrupt or steal information from any system or solution (Halinen&Jokela 2016). This term is very much associated with computers, networks, modern standard, mini or micro gadgets and its security.

Code of Ethics and The Reason for Such Incorporation

The code of ethics is to define an ethical foundation where each of the members responsible in the team can appeal to serve a particular decision for developing a solid software solution (Boddington 2017). This helps define and identify a particular solution that stands ethical or unethical and can proceed to development of a robust solution by eliminating the unethical approaches in the team. The main purpose is to achieve a rock solid solution by serving the commitments to health, safety &welfare of the public or businesses.

Principles for Software Engineering Code of Ethics

The principles for software engineering are defined based on standard application of fair policy by the software engineer while working in a team to achieve a good solution (Jia& Xin 2018). The principles for software engineering are a mentioned below:

1. The act of a software engineer must be carried over keeping in mind the public interest (Davis 2017). Moreover, they should ensure that the interest of the employer and the client is always of high priority as the outcome of the module should signify a solution to overcome a problem using the software solution.

2. The software engineer must ensure that a high quality output is provided by implying the highest professional standards.

3. The software engineers who are seniors or those belong to the software managerial levels must follow an ethical approach in managing software development and maintenance activities (McNamara et al. 2018). Software engineers must follow ethical approaches in delivering professional solutions by implying professional judgments.

4. In software engineering working in a team and adapting to a managerial environment is of utmost importance. Thus, it is fair to support the colleagues, clients, vendors and the management to serve the purposes of ethics (Spiekermann& Winkler 2020). They must also adhere to a continuous knowledge upgradation or self learning practices to support the profession with ethics.

Though there aremany other codes of ethics that are evident in various sources as released from time to time, however, all serves the purposes for meeting the standards and contribute to the society at large.

Considering the Scenario for Self Driving Cars

What is the Self Driving all about?

Self driving is a feature developed using software technologies to partially automate the car driving process (Bojarski et al. 2016). Though the objective is to offer features to aid in the car driving process, however, the implementations has faced some serious challenges and thus re-thinking the implementations considering safety and security of the travelers as well as the public on the road is in real demand. The positive aspect is that several well renowned companies have come forward to research, develop and implement a system to completely automate the self-driving process (Diels&Bos 2016). But the challenge is the final decider to ensure a logical flow of operations. This is better explained in the case study scenarios which are discussed below.

Some of the case studies to quote

1. The Google Self driving cars project

A project initiated under the brand name of Google with the objective to develop a solution that would serve the purpose for automated driving system for cars. The solution aims to implement a solution where the car will automatically drive to take the passengers to their destination, where they wish to go. While implementing the logic, the software team had to take the safety and security as a major consideration. Thus the speed of the cars needed to be considered keeping in mind the security of the passengers and obeying to the traffic rules. But while considering the situation as a case example, they came up with a set of ethical questions that bars continuing with further development and to come up with a solution will require a strong decider. The deciding factor is what will happen if a passenger in the car falls ill and require immediate medical attention.If we consider the first instance of controlling the speed of the car during auto driving mode, then, the security of the passenger will be at a stake because the passenger would require an immediate medical attention. This scenario is similar to what is called as decision interruption in software technology. (Speier 2003)

There are other similar case instances where the decision tree for planning the implementations cannot be completed. In order to come up with a logic a proper flow for the process needs to be planned using the decision tree and to do this, strict decisions needs to be adopted compromising few scenarios to complete the flow for the logic.

2. The Tesla Autopilot car instance

The car was launched with a marketing punch line as an Autopilot car. It came with major features like traffic avoiding cruise control, steering assist, auto control of door locks keeping the security concerns, and many other features. But the problem was in the marketing aspect where it was claimed as an Autopilot car with people presuming it to be a complete auto drive control. The accident that occurred with this car killed the driver. Though the real reasons cannot be interpreted but probably, the driver presumed that the car will drive by itautomatically and is a complete auto driver.

Though there had been other test runs performed by Volvo cars, and other such renowned car manufacturers who implemented the automated software’s of their own, however, none resulted in a complete success as there were cases of accidents reported (Pavlo et al. 2017). But above all, filling in the gaps to prepare a solid decision tree will help reinstate a complete safe automatic self driving capability for the cars.

The Future of Self Driving Cars

Above all, the future of self driving cars is a real challenge and would require more use of technology (Banerjee et al. 2017). Following are the technologies that can work wonders in devising a complete self driving system solution:

1. Using the Radar system – As radar uses radio waves; it helps determine the range, angular position and the speed of an object. This can be of great help in recognizing the distance and the speed of the nearby objects, however, it can detect objects that are within a particular range like 1000. Radar detection can be of great help for auto driven cars as the objective is to detect object that are within a particular range.

2. Laser detection technology – This can be a great contributor in detecting objects that are very nearby. This helps avoid sudden accidents if any comes in of a sudden during the auto pilot car journey. But the major challenge is the cost.

3. Implementation of Machine Learning and Artificial Intelligence – Artificial intelligence if applied, can do wonders and can be a great contributor in framing up a complete self driving solution for cars. It works on a logical sequence based on the factors of elimination whereby it automatically identifies the driving sequence as per the business logic fed in the automated system.

Apart from the above, there may be many other technologies that may evolve in due course or utilizing any other existing technologies that can be used in automation of the process (Nielsen&Haustein 2018). Though there are logical hindrances, but with usage of the technological equipments and utilizing its usability features those can be removed. This will definitely help frame a solid automated auto driver solution for cars.

Risks Involved

1. Risk for meeting with accidents is a major challenge as no technology is perfect. As machineries can fail or may malperform due to erroneous circumstances thus, it will be a risky implementation and can cause unascertainable circumstances. Even if everything goes on fine, any of the other cars accidentally hits the car even by a pinch of touch, the automated system may fail or even worse, the system may malfunction and can cause disaster (Kohl et al. 2018). Still we are hopeful that the equipments and tools installed in the car will be widely protected with hit proof covers and expect everything works well.

2. The craze of controlling cars by the younger generation will fade the popularity of the auto driven cars because that is not what these people prefer. They are mostly attracted with rash driving or varying the speed at regular intervals or maybe banging the dashboard of the automated car to add a spice to the music may turn risky.

3. Rules for traffic and signals vary from country to country and thus the regulations may be risky. Probably this kind of risk can be overcome by introducing customizable settings to match the business rules that vary from country to country (Shalev-Shwartz et al. 2017). This flexibility with maximum options should be enabled and the software should be versatile enough to adjust the settings in the solution. However, the implementations would be a real challenge and can only be said in near future.

4. The technology implementations will be very costly that will add up to the cost of the car and thus will be far from affordability range of common people. But, if both the cars are sold in both the ranges, with and without the auto driver facility, then the chances of accidents would definitely rise.

5. What will the drivers do? They will be jobless then if self driven cars replace the driven cars in the market (Darcy & Burke 2018). Hopefully they will get into another skillsets but still their living hood would be at stake.

6. The technology hackers won’t spare and can have complete control over all the cars that are using the same software that has been hacked. Hacking is an unethical process to get control over any of the systems when any of the coding or hardware drivers related flaws are identified by them. Even if anyone has a grudge against any individual or a company, they can hack the system, if it can be and can complete create a disaster by controlling the car to a trap or lead to its destroy.

7. The cars can even be very easily stolen if the password system to unlock the doors and regulating the system of the car is hacked and cracked. Though every measures are taken in developing a software solution but yes, there will be hidden loops no matter what it is. Hopefully, a proper security testing of the software solution and implementing logical honeypots in the network that operates can help. Other filtration techniques may be safeguarding the database and by replicating other similar anti hacking steps for protection and security.

The benefits for implementing auto drive facility

1. The system will never get drunk and thus the risk for uncontrolled driving will be nullified and all the accidents due to this cause will not happen (Camlica 2016). Majority of the cause of the accidents occur due to this reason.

2. Drowsiness due to long drive leads to majority of the accidents. Referring back to a popular proverb “To Err is human”. No human is without errors. Thus, an automated system is of much demand and it is evident that majority of the accidents will not occur any more due to drowsiness factor.

3. An automated system will never get distracted while driving. This happens specially with the younger generations where they enjoy the moment of driving while doing an outing with friends or colleagues. The mood and their enjoyment conditions often leads to major accidents especially on the highway roads.

4. It is said that humans can at the most concentrate on any work for a maximum time span of 8 seconds at a time. This also leads to majority of the road accidents that can result in huge losses as well.

5. Wrong driving also leads to majority of the accidents on road. This specially happens when the driver is not very proned to drive on the highway roads and wrongfully assess the speed of the other car coming from the opposite end. Though self driven cars are also not trustable at the current stage, however, hoping that the technology will further improve and implementations will nullify the incidences of road accidents as machines work as per instructions and if the instructions and the detection process is implemented as flawless then definitely the self driven cars technology will be totally in control. Good news is that, there have been immense contributions, whereby, the implementations are planned to detect the drivers behavior by using encoders. (Camlica 2016)

Conclusion on Ethical Decisions in Software Development

Technology is definitely a blessing if it is properly applied else, it may lead to a complete distraction. Application of technologies to cars for implementing self driven features demands appropriate development and implementation. Security has always been a real challenge to the advancement of technology. As the world progresses with technology and many of the modern machineries are mostly automatic, thinking of those systems a few years back was a dream to us, however, with the advancement of technology, it became possible.

Taking this aspect in consideration, trust on the technology will never fade for us. We know that we will continuously evolve new technologies and will definitely win the race. So, hoping that some day or the other, affordable self driven cars would surely be in place and will be an efficient replacement to manual driving methods.

References for Ethical Decisions in Software Development

Banerjee, T., Bose, S., Chakraborty, A., Samadder, T., Kumar, B. and Rana, T.K., 2017, August. Self driving cars: A peep into the future. In 2017 8th Annual Industrial Automation and Electromechanical Engineering Conference (IEMECON) (pp. 33-38).

Boddington, P., 2017. Towards a code of ethics for artificial intelligence. Springer International Publishing.

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.

Darcy, S. and Burke, P.F., 2018. On the road again: The barriers and benefits of automobility for people with disability. Transportation research part A: policy and practice, 107, pp.229-245.

Davis, M., 2017. Engineering ethics. Routledge.

De Los Reyes Jr, G., Kim, T.W. and Weaver, G.R., 2017. Teaching ethics in business schools: A conversation on disciplinary differences, academic provincialism, and the case for integrated pedagogy. Academy of Management Learning & Education, 16(2), pp.314-336.

Diels, C. and Bos, J.E., 2016. Self-driving carsickness. Applied ergonomics, 53, pp.374-382.

Halinen, A. and Jokela, P., 2016. Exploring ethics in business networks: Propositions for future research. In Extending the Business Network Approach (pp. 333-356). Palgrave Macmillan, London.

Jia, J. and Xin, J., 2018, May. Integration of ethics issues into software engineering management education. In Proceedings of ACM Turing Celebration Conference-China (pp. 33-38).

Kohl, C., Knigge, M., Baader, G., Böhm, M. and Krcmar, H., 2018. Anticipating acceptance of emerging technologies using twitter: the case of self-driving cars. Journal of Business Economics, 88(5), pp.617-642.

McNamara, A., Smith, J. and Murphy-Hill, E., 2018, October. Does ACM’s code of ethics change ethical decision making in software development?. In Proceedings of the 2018 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (pp. 729-733).

Nielsen, T.A.S. and Haustein, S., 2018. On sceptics and enthusiasts: What are the expectations towards self-driving cars?. Transport policy, 66, pp.49-55.

Pavlo, A., Angulo, G., Arulraj, J., Lin, H., Lin, J., Ma, L., Menon, P., Mowry, T.C., Perron, M., Quah, I. and Santurkar, S., 2017, January. Self-Driving Database Management Systems. In CIDR (Vol. 4, p. 1).

Shalev-Shwartz, S., Shammah, S. and Shashua, A., 2017. On a formal model of safe and scalable self-driving cars. arXiv preprint arXiv:1708.06374.

Spiekermann, S. and Winkler, T., 2020. Value-based Engineering for Ethics by Design. arXiv preprint arXiv:2004.13676.

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