Choice of Careers
During the selection of careers, three careers, which comprise graphic designer, data scientist, and computer engineer, topped the list. Some of the factors that determined my decision to choose the careers include the rewards accrued from each of the careers, the needs of contemporary societies, and the impact that emerging technologies have on the respective careers. Before selecting the careers, I had to look into the requirements of each of them and examine whether the rewards that they accrue could advance my abilities in fields of creativity, critical thinking, and knowledge acquisition. Consequently, I also considered the extent to which the careers could be useful in solving issues faced by present societies. According to the assertions of Gordon and Steele (2015), career choices need scrutiny on the benefits that they have on society. The issue of technology and its impact gained consideration because some careers may no longer be productive especially in the face of the changing times and technological advancements.
Fundamentally, during the rating and weighing, the career of graphic designer became one of the best in the list of the three careers. Graphic designing is dynamic and compels one to look for information and keep in touch with the latest technologies and software. Moreover, the career is very rewarding and has several benefits that are helpful in modern times. Its creative use of pictures, diagrams, and videos makes it appealing and easy to use in conveying the information to a given set of individuals. The second career is that of computer engineering. Computer engineering is a career that has several benefits and researchers state that these benefits will increase in the wake of technological advancements (Dumas, 2016). With an increasing number of computer and Smartphone users, the demand for computer engineers who have the relevant skills in electronic engineering, software, and integration will rise. Moreover, some computer engineers can open private enterprises in case of limited employment.
Data scientists are also very important because they help in converting structured and unstructured information into useful messages that can inform decisions made by organizations. With their skills in fields such as programming, statistics, and mathematics, these scientists look at information and convert them into relevant pieces that can be useful in propelling companies to higher levels about their competitors. One of the factors that lowered the position of the data scientist in the list of my career is its limitation in creating jobs. Provost and Fawcett (2013) explain that the scale of self-employed data scientists is minimal compared to that of graphic designers and computer engineers. The implication of the limitation is the fact that the majority of data scientists who fail to secure active employment in companies may not have the opportunity to optimally utilize their skills.
Evaluation Matrix
Emerging Technologies in Each Career
In the sector of graphic design, technological advancements have had a notable impact. The increasing number of people using smartphones, computers, and those in possession of televisions have propelled the demand for designed adverts, videos, and video games, as well as printed content in newspapers and magazines. Landa (2010) claims that technological advancements lead to the introduction of new graphic software that could render the skills of graphic designers obsolete in the absence of continued research. A combination of these emerging technological issues compels graphic designers to engage in regular research on trendy developments. In the field of computer engineering, there are numerous impacts triggered by emerging technologies.
Frequent introduction of new software and the rising demand to incorporate some computer programs into smaller gadgets such as the Smartphone make up some of the challenges introduced by emerging technologies. The new software advanced by users of computers and smartphones constantly challenge computer engineers. Therefore, computer engineers have to keep in touch with changes in technology (Dumas, 2016). On the other hand, the impact of emerging technologies is also apparent in the field of data science. The increasing use of smartphones and computers has led to numerous information availed on the online platform. It is important to explain that the new information needs translation and conversion into useful pieces that can solve issues in business, medical, and other sectors of the societies. Translation and conversion of the information need the expertise of data scientists. Therefore, scientists need to work extra hard to unearth the effective ways of dealing with the increasing information availed by individuals on platforms such as the internet.
Ethical Principles
With the impact of advancing technology, graphic designers, computer engineers, and data scientists need to be careful when undertaking their activities so that they remain within ethical boundaries. In the field of graphic design, ethical considerations include the production of information that is within the ethical boundaries, exercising honesty with clients, and sharing what is true. On the other hand, computer engineers need to ensure that they provide factual advice that helps clients enjoy using computer software. In the context of data science, the scientists need to assess the credibility of information shared and only use those that are factual (Provost & Fawcett, 2013). Notably, in some cases, information shared may not be true, a factor that calls for due diligence from the scientists so that the end-users do not suffer from misguided information.
References
Dumas, J. (2016). Computer architecture: Fundamentals and principles of computer design. Boca Raton, FL: CRC Press.
Gordon, V., & Steele, G. (2015). The undecided college student: An academic and career advising challenge. Springfield, MO: Charles C Thomas Publisher.
Landa, R. (2010). Graphic design solutions. New York, NY: Cengage Learning.
Provost, F., & Fawcett, T. (2013). Data science and its relationship to big data and data-driven decision making. Big Data, 1(1), 51-59.