Artificial Intelligence (AI) is a process to solving any kind of situation by providing a decision or to make an appropriate solution of that problem. The accuracy, intensity, character of the problem may be different may have some limitations to mitigate the situation. AI is the way of solving application where the presented knowledge and the permanence are the ultimately related term that enhances the productivity and used for the development of the organization. The support and control appliance of modeling, prediction, and equipment of the AI enhances the diverse realms. In the juncture of efficacies and modern encapsulate, there are certain development o products or things that are essential as well as keep the intact source of binding. There are some promising influences that are presented in a capable way so that limitation of the product can be maintained. In this case study, the long term goal is relevant and effective in the modern market. As the market is being globalized the taste and think tank of people has also been changes. There are certain criteria and desire, which people evolved in their mind, has been implanted by the assistance of modern technology. The project is almost an example of that modeling and infrastructure that has been introduced by the company.
The ethical dilemma is present in every organization. Ethics mismatch or not understand the work ethically is considered as the ethical proclamations that enhance the relationship with employees to their managers. The fairly endeavor of excellence is the organizational culture and capacity that imposed by the effort of commitment. AI provides the permanency and the make a framework with the employees to make better productions. The reliability and prolonged establishment of the process have certain criterion of equipments and state the leveling issue with it (Bostrom & Yudkowsky, 2014). The real specification is now overturned thus advantageous mannerism and model structure is the basic way to find out the realism of the fact. In this case study, the level of effort and energy that put into for the enhancement of modeling of the car has seen by the responsible undertake of the authority (Grover, Pea & Cooper, 2015). The learning process and the collective data from the earlier car supposed to maintain the better scenario of the car. The new car that has evolved has the certain special specification that another car has not have. The self-driving facility of the car is the invention and adapting for the facility the technological influence in the organization has opted their modeling structure (Bostrom, 2016). The influence of the car is impactful as the self-driving sensor has to detect certain challenges to carry forward. Company managers and all the employees have given their best to introduce the car thus the performing nature of the car be erect and proved to be the best.
AI mainly introduced and implemented in robotics, machine visions, automation programs, automation theorem proving, retrieval systems, engineering, data modeling and any intelligence work related with IT. The scope and technological advancement will forecast as the uncertainties are quite low in this section as the trusted pieces of equipment are dealt in. In this case, additional effectiveness is persisted as the car will be self-driven so the chances of involving accidents are there (Clarke, 2016). The company has to prove that fact that in any circumstances the car will not get involved in any accident as the car has so powerful device that can detect every adverse condition and prepare according to the situation (Deng, 2015). There are certain challenging interference and ethical allocations that integrating the ethics of the compliances. In this kind of car, customer safety is important as the elite class people will choose the car so it is mandatory to retain the safety policy of it.
Response from the effectiveness of AI is classified as the source is open and free thus social media platforms are the identified version of this practice. Actionable and ethical situation combination human intellectualism is being forecasted by that artificial intelligence digital response. Developed computer techniques and technologies are so impactful that real world challenges are not so challenging for the IT developers (Luxton, 2014). The social and economic effect by the technological enhancement is noticeable as the approached experimental growth provides systematic networking and coding decoding system to enhance the successful implementation of artificial intelligence.
The codes and values of Australian Computer Society Code is a part of the Australian Constitution. The members of that organization have taken certain steps over dignity, effectiveness, and honor (Anderson & Anderson, 2014). There is certain forms additional advancement like values which evaluates the codes and makes quality analysis over it.
In this case study, the Car Company and involved artificial intelligence have also maintained this code of ethics that ACS has implemented for the safety of technological aspects. The intentions of these codes are familiar with the professional conducts. The behavior and contentious issues are the concern factor that has to be mitigated by the effective implementation of those codes. These codes can also resolve the ethical dilemmatic situation in an organization (Shoham, 2014).
In this case, the effect of ethical ACS codes is maintained with dignity and honesty. The car has not been launched unless all the satisfactory measures are not checked, that determines the ethical issues and provides importance to the customers. As asserted by Mellit and Kalogirou, (2014), the value and ideals of this act must provide the integrity and relevance to the client and employees. Code of ethics has specially treated for the professional conduct and behavior. The car which provides public interest as the self-driving mode can ease the life of the customers. The impact of the car is important as the security, utility and integrity are being sustained in this car. The quality of lifestyle will also get a boost as the imposed technologies are doing their role in an effective way (Ford & Richardson, 2013). Professional honesty is being observed in this car company and their employees that are the reason they are going to introduced their car after so many tests (Seo et al. 2015). On the other hand, they may not be the first one to launch the product but the clarity and effectiveness and controlling sensor they will provide will be the best in the market, so competitive advantages are sustained. The appropriate nature of implementing skills and proficiency in technology enhance the opportunity of business. The proposed work in this car has dealt with the respective self-sensor system that creating the next level of car driving without a driver (Nilsson, 2014). Professional development is there with the optimum skill and knowledge allowance, if it not possible then, evolvement in this car and the technological engagement with this will not possible, therefore with the dignity and matured professional standard is being maintained by the effectiveness of workplace (Fergus et al. 2015).
The system management of AI has improvised new creativity and new techniques for the business domain. High technical emphasizes and creativity has been noticed in this form of care. The engagement over machine learning, the critical arrangement of programs, creativity all these are accumulated technological aspect that has been made for the development spinning of the infrastructure (Azofra et al. 2014). The quality analysis and IT projects are done by the consulting modeling of the projects. In this case, car enhancement of extra modeling is emphasized so that accidental situations can be avoided. The company has chosen the best possible modeling and also feels the minimal amount of risk factor with it.
Conclusion
Therefore, the report can be concluded that adaptation of new strategies and implementation of those strategies in an innovative way can enhance artificial intelligence for an extent. However, those provided ACS codes by the Australians have made proper modeling of a learning process, technological outcomes and maintaining the technology. This is the reason this kind of self-driven cars is being introduced. The company has taken the initiative and highlighted the strong engagement with the project so that market competition has been set and their business scenario enhances.
References:
Anderson, M., & Anderson, S. L. (2014, July). GenEth: A General Ethical Dilemma Analyzer. In AAAI (pp. 253-261).
Azofra, D., Martínez, E., Jiménez, E., Blanco, J., & Saenz-Díez, J. C. (2014). Comparison of the influence of biomass, solar–thermal and small hydraulic power on the Spanish electricity prices by means of artificial intelligence techniques. Applied Energy, 121, 28-37.
Bostrom, N., & Yudkowsky, E. (2014). The ethics of artificial intelligence. The Cambridge handbook of artificial intelligence, 316-334.
Bostrom, N. (2016). Fundamental issues of artificial intelligence (Vol. 376). V. C. Müller (Ed.). Berlin: Springer.
Clarke, R. (2016). Big data, big risks. Information Systems Journal, 26(1), 77-90.
Deng, B. (2015). The Robot’s Dilemma. Nature, 523(7558), 24.
Fergus, P., Hignett, D., Hussain, A., Al-Jumeily, D., & Abdel-Aziz, K. (2015). Automatic epileptic seizure detection using scalp EEG and advanced artificial intelligence techniques. BioMed research international, 2015.
Ford, R. C., & Richardson, W. D. (2013). Ethical decision making: A review of the empirical literature. In Citation classics from the Journal of Business Ethics (pp. 19-44). Springer Netherlands.
Grover, S., Pea, R., & Cooper, S. (2015). Designing for deeper learning in a blended computer science course for middle school students. Computer Science Education, 25(2), 199-237.
Luxton, D. D. (2014). Artificial intelligence in psychological practice: Current and future applications and implications. Professional Psychology: Research and Practice, 45(5), 332-339.
Mellit, A., & Kalogirou, S. A. (2014). MPPT-based artificial intelligence techniques for photovoltaic systems and its implementation into field programmable gate array chips: Review of current status and future perspectives. Energy, 70, 1-21.
Nilsson, N. J. (2014). Principles of artificial intelligence. Morgan Kaufmann.
Seo, Y., Kim, S., Kisi, O., & Singh, V. P. (2015). Daily water level forecasting using wavelet decomposition and artificial intelligence techniques. Journal of Hydrology, 520, 224-243.
Shoham, Y. (2014). Artificial intelligence techniques in Prolog. Morgan Kaufmann.
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