Ethical and Privacy Issues in Big Data - Report Example

Ethical and privacy issues in big data ETHICAL AND PRIVACY ISSUES BIG DATA Introduction There is no universally accepted definition of big data. This is because people have not agreed particularly on the size, varieties and velocity that would define big data. However, according to Mateosian (2013), big data can refer to datasets that are characterized by a large size beyond that of the typical database that common software can capture, manage, store and analyse. Enormous datasets have stimulated the development of new technology for the storage of big data (Kognitio, 2014).the term big data has been defined as the generation of new technologies with architecture designed for economical extraction of large volumes of data, which will enable discovery, high-velocity capture and analysis. In this regard, big data is too big, and it moves too fast to fit in the structures of conventional databases. Therefore, big data structure technologies have been developed as an alternative way to process it. What are the Characteristics of Big Data?. As already noted, three elementscharacterizebig data: velocity, variety and volume.Many organizations regard the volume of big data as “big.”According to the references from various organizations, volume is a relative term. This is because some organizations may have data sizes in gigabytes, petabytes or terabytes, or even exabytes for big global enterprises (Matteson, 2013). It is important to note, however, the bigger volume data are continuously growing, as there are tendencies by firms to store all sorts of data (Matteson, 2013). For variety, it is believed that data can come from various sources including both external and internal. With the explosion of sensors, smart devices and social networks, data management is now very complex, as the data can come from a variety of sources (Matteson, 2013). What are the Origin and Importance of Big Data Considered? For some years, large organizations have been capturing data that are structured, using batch processes in order to place their summaries into traditional relational databases. However, in recent years, new low-costs technologies have emerged, resulting in improved data capture, data analysis and data storage. Organizations now do not worry about capturing information from many sources that include social media, blogs, video and audio files. The data may nonetheless be of various types. Technologies that produce highly optimized capabilities have been improved for different purposes depending on the nature of the business. The analyses, which are normally on a real-time basis, can now be done on the whole set rather than summarized elements of the conventional database. It is also important to note that the number of options for interpretations has also increased (Arellano, 2013). Big data databases can now be used in the practical deployment of data because the technologies have matured. Moreover, the underlying costs of managing data have been reduced dramatically. Nonetheless, use of big data has the potential of increasing the competitive advantage of the firm (Matteson, 2013). What are the Ethics and Privacy Issues of Big Data? The term ethics generally refers to fairness, social justice, participation, consent and agency. Ethical practices in any organization will allow stakeholders to participate in matters regarding how, where and why their data will be used. This will strengthen the organization and strengthening the community it serves (Oram, 2014).Ethics has been noted as one of the elements being overlooked in big data science. It is important to note that although both privacy and ethics are important, the latter is too narrow to express all of the concerns about the risks of the technologies. When designing a project, especially a community one, ethics has been given the top-most priority. It becomes the guiding principle on which other aspects of any project that the community will have to be involved will follow. The other principles are governance, socio cultural context, science, place and lastly technology. In this regard, developing strong ethical principles will be essential to ensure that the community’s data are not harmed. As has already been noted, having an ethical framework at its core will enhance the agency or organization. It is however important to note that ethical considerations need to be incorporated in any big data project from its onset when designing and assessing it. The principles for consideration in this case will have to include data informed consent, ownership, transparency, accountability, access and protection. Informed consent in this regard goes beyond merely informing people about the terms and services. They should be informed about whether the third party will have access to their data or not (Brans, 2013). What the Big Data Scientists and Managers Say Professionals working in the big data industry agree that there is need to be stronger on ethics within their industry. They urge that consumers should also be responsible about their privacy when giving out personal information. According to the findings carried out during the 2013 Joint Statistics Meeting Conference, in Montreal, a larger percentage of data scientists agreed that consumers should be responsible for their data; and88% indicated that this issue needs to be dealt with Richards, N. (2014).Four of five respondents (80%) said that there should be an ethical framework to stipulate how data should be collected and used. More than half confirmed that this issue had become part of their research. However, 28% said that the industry needs to begin implementing such standards. On sectors of major focus such as health care and life sciences, the data scientists noted that there is a much greater emphasis on ethics in such areas. According to Revolution Analytics (the company that conducted the research), it is not surprising to hear that from the data scientists. This is because they are the people who encounter sensitive information every day, and they are aware of how powerful certain data may be. The boss also asserted that in the wake of various scandals, such that of the United States National Security Agency (NSA), there is a need to improve on the ethical considerations of every firm (Kognitio, 2014). Ethical and Privacy Issues in Big Data One of the issues facing big data technologies and management is the pressing question of privacy and ethics. Even though big data analytics have enabled a change in the way data are collected, utilized and stored, questions are being raised on how firms are storing the massive amounts of data as they turn them into business insights and intelligence. Moreover, the technologies for that seem astounding, and no clear legal regulations have been developed to deal with the situation. These questions of information ethics, data privacy and data ownership greatly affect users and customers, but little has been done to address them. It is also important to note that the scope of and differences between data privacy and analytics are not well defined by most legislations. This is a matter of concern because as Laskowski (2014) notes, it is important that businesses put the privacy of their customers in consideration first, and then the analytics will follow. There is fear that employers have uneducated employees who are in touch with the data pot. As their accessibility increases, there is a fear that chances of mishandling sensitive data may result. Riglian (2014) has noted that the question is of concern because media outlets have published several reports on the innovative effects of harnessing big data. Some companies, although having not already informed the owners of the data, have formed a habit of collecting data from people without their notice and using the data to track them, which has raised ethical questions on the huge data stored by these companies. Moreover, privacy and ethical issues in big data collection have become very hot topics, even in the political arena, with the government being pressured to look into the concern. Further, there are instances that companies have been caught collecting data and selling them to other companies. Consequently, there are pressures mounting for legal consequences to be developed to counter such practices. The issue moreover has greatly affected consumers in Europe and Asia who fear sharing their personal information in a database. Gourlay(2014) reports that cultural limits have severed the situation for some Internet users. For the businesses themselves, fears are emerging about taking their data to the cloud. Financial managers of large companies have expressed their reservations regarding taking their financial results to the cloud as they adopt new technologies. This is because, as already noted, although it saves time and money, there is a fear of security and privacy disasters (Snider, 2012). Why code of Ethics and privacy are needed in big Data Management. Arellano (2013) asserts that although the Internet is there to change the happenings of everything, there should be a code of ethics to regulate big data management to avoid dangers such as cyber bullying. If these regulations become substantial, everybody will enjoy the benefits of the IT breakthrough. The other reason is that intelligence devices are being hooked on the Internet at an increasing rate, and most of them will be there for commercial purposes. Ethics are therefore needed to protect the identity of ordinary people (Arellano, 2013). According to Oram (2014) the number of hacker communities on the Internet is increasingly growing. This will increase technical assaults on any individual’s autonomy. Hence, there should be technologies in every organization that collects data to prevent hackers from assaulting an individual’s autonomy. Moreover, ethics are needed because there are dangers sowing to the amount of every individual’s available data on the Internet, which will continue to increase. For those who snoop the Internet to acquire data for analytics, the data may not be accurate or it may present a kind of prejudice. For instance, as Oram(2014) explains, if some people use data from social networking sites to make analytics it may be untrue simply because people are subject to incentives and hence temptation. Therefore, the data may be based on prejudice or lies. Hence, ethics will restrict companies in using individuals’ data for their analytics or selling. In this regard, for instance, people tag different photos online, and it would be wrong to attack an innocent person as the owner of the photo. To emphasize the reasons why ethics should be formulated to counter these threats, the analytics based on large amounts of data may be used to hide the individual’s traits from the group. Nevertheless, some results, as already noted, may not protect the whole group. Moreover, the law cannot enforce them since they hide an individual’s identity (Brans, 2013). Companies are now commercializing large amounts of the data they get from the public by selling the data, and it would be appropriate if measures could put a stop to that practice. However, the most grounding assertion is the preservation of human dignity where nobody is ready to interfere with the privacy of others. In this regard, the companies’ risks being abandoned if they do not place human values ahead of the analytics (Davenport &Dyche, 2013).Moreover, the analytics have been noted as being the main source of discrimination among customers. The other important consideration is that there should be ethics to ensure that big data manifests some transparency. In this regard, there should be clear disclosures on how the information gathered may be used so that the person who delivers it can consent or not. Things have become entirely wrong since the use of individual data is now being done in secret. Even though some of the applications of the data may affect everybody’s life, it is important that the individual consent on them (Davenport & Dyche, 2013). A Framework for Ensuring Ethics in Big Data Due to the fact that individuals are increasingly storing their data on the Internet, various stakeholders should come up with a comprehensive framework so that ethics are built for the digital future. The first pillar for this framework should be law. As technologists claim, various acts, such as the Fair Credit Reporting Act, should be passed to regulate effectively fraudulent credit reporting agencies because they have been studying individuals’ credit reports, calculating their scores and even selling the data to other businesses (Richards, 2014). Therefore, such measures should be extended to other essential areas. Moreover, it should also be noted that law alone might not be adequate to solve ethics problems in the digital world. Moreover, there should be measures in the laws that seek to counter unethical use of digital information for analytics that make conclusions by using race or its proxies to allocate prices and government services and benefits (Richards, 2014). The same should be applied against those who use the big data inferences to decide on investigative nature, lawsuits and college admissions. In fact, this should also be aimed at prohibiting imposition of criminal sentence to anybody (Richards, 2014). The society of scholars in relevant fields should come together when formulating the legislation to decide what sharing should be allowed and what should not. This will present a comprehensive framework that bases big data management on rules, taking legal, technological and ethical implications as the first step (Wen, 2012). The laws nevertheless should answer comprehensively questions such as who should own the big data and who is responsible for its privacy in the practices of managing the data. The law should also define the privacy issues that big business should be aware of when storing such data (Richards, 2014). Noticing that experts have not drawn the line between big data and the old data, there should be a clear definition of what big data is including its volume and variety and the appropriate technologies that should be employed in its management to ensure that privacy is assured (Richards, 2014). This will remove doubts on theoretical controversies on what big data is. Three features, velocity, volume and variety, have become useful landmarks that experts can use to determine the sizes of various data sets and the speeds at which they can be queried and acquired in a wide range of formats. Moreover, issues of proper collection, retention and organization are becoming commonplace, which raises the growing ethical implications of them. Ethical considerations on special data sets should be determined. The next step will be establishing social norms upon which everybody should act. The social norms will dictate how people should make use of other people’s data in digital forms to make decisions about them. These norms should be followed closely while considering the rights that those people have to understand and dispute those decisions. This is because, currently, there is ongoing debate about executives using the profiles of their employees to set working conditions and standards for them. Likewise, the government has been using the inferences drawn from those analytics in determining how to allocate its services and other benefits (Richards, 2014). This is just analogous to what happened during the industrial revolution when norms that determined the way the government of the day allocated resources and services were determined so that everybody in the state derives benefits. Software engineers and other engineers will have to have competency in data conservation. Individual users will also be put to task to ensure that they behave responsibly with their data. This should not mean that those alone would have to bear the burden of their data. There should be structures that encourage ethical considerations of data usage rather than merely giving incentives to consumers, so that they release their data as large as they can for little incentives (Wen, 2012). The framework will then have to build structures that will include in-house review boards and ethicists in both government and private entities that give themselves responsibilities for big data. It is important, although currently these proposals may appear farfetched; they are now becoming wide spread (Richards, 2014). It started with university scientists wishing to begin their experiments, submitting their projects to review boards for reanalysis and verification. In big corporations that store data, privacy officers have been employed to be in line with such ethics. In this regard, Google has instituted ethical review boards and ethicists-in-residence. More importantly, engineers should be encouraged to embrace the big data ethics idea (Wen, 2012). Next on this issue will be ensuring that each organization’s institute resilience measures. Resilience refers to the ability by any big data organization to absorb and deal effectively with unexpected shock. In this case, disturbances and hazards normally occur in the management of data, and, therefore, organizations should be prepared to cope with them. This should be taken into consideration, taking in mind the many cases where data have been tampered with (Brans, P. 2013). Drawbacks in Implementing Big Data Ethics The most notable circumstantial drawback is that the government has been mandated to collect data from any citizen without any limitations. Although the government is supposed to be the guardian of citizens, it has held a vast amount of data, whereby some companies that act under their jurisdictions can use them. The extension of the so-called lawful request is yet to be agreed upon clearly. Recently after the NSA scandal, there have been debates about the balance between the government’s desire to access one’s information for national security and law enforcement reasons and with the right of a citizen to privacy. Therefore, in case there is an abuse of power by state security agencies, enforcement of the ethics framework may prove to be difficult. While there may be precise legislation, warrantless and real-time access of one’s information may lead to public backlash with the government’s handling of their private/ confidential data. This is entirely possible in most Western democracies such as the UK and USA. The recent moves in democracies like the UK have been compared to Iran or China where the questionable government access of individual’s data is not new (Richards, 2014). Moreover, if the government seeks to silence its critics, the ethical framework may be compromised and weakened. In the recent past, there have been such allegations in the Middle East, where social network data have been searched to silence those spreading revolutionary messages. Nonetheless, it has been noted that each nation may try to form its laws and those laws may be different from the laws of other nations. Some countries may have regulations; others may not, and this may make it difficult for international corporations to streamline their privacy policies (Richards, 2014).Another noted barrier has been the lack of ethical consideration by firms receiving individuals’ data. This does not only concern those ethics proposed in the framework for big data but also those found in social science experimentations. As it has been noted, ethical barriers for experimentation have become very low, and individuals stand unquestionably with offences of accessing personal data without their consent. Although the framework of ethics and privacy for big data management may exist, there may be a lack of relevant application of its principles, especially when it comes to social media (Richards, 2014). The other barrier emanates from the users themselves. They seem not to care about consumer ethics policy. It has been noted that, for instance, when friends upload photos on the Internet, they may normally be used to making inference about their close friends. This will include a consumer for instance, a Facebook user viewing wrongfully and appropriating others’ information. This will mean that the consumer ethics will be instituted first (Richards, 2014).The other barrier will be defining and determining what is actually ethical and at what scope. Ignorance of concepts by those involved has also been noted. This includes lack of knowledge for proper use of tools, expertise and the organization’s lack of well-designed plan to manage the situation. In this regard, Moran (2013) has argued that technical hurdles in the management of big data may become one of the major hurdles in its management. For instance, the inadequate technical capabilities among the operators, the small capacity of computer systems, poor/small data storage and communication networks may not guarantee proper management of the big data in an ethical way. He adds that if there will be no electronic infrastructures to enhance data storage, metadata mining tools, data analytics, data duration and powerful algorithms it may therefore be hard to institute the ethics. As it has already been noted, one of the constraints the big data question is facing is the technology that can store it. Oboler et al. (2012) indicated that technologies are being overwhelmed by the big data itself. This will be one of the biggest challenges the big data will be presenting. As analysts note, people will be confronted with the need for additional proxy servers and controllers, although they warn that the data may become less useful. There will be need for security controls so that data can be kept successfully. As analysts have noted, owing to the fact that the big data will be huge, there is an implication that security control system must also be huge. On talent constraint, Rouse (2011) has reported that shortage of talent may be a problem that will affect big data management. As the data increases, there will need to be people that have deeper expertise in knowledge in machine learning and statistics and analysts and managers who will be needed for insights from big data every time. In this case, the industry, as it will translate every big data will have to have data scientists (Ahalt& Kelly, 2013). The 2012 survey carried out by Informative Week realized that 40% of the respondent said that they were willing to increase their members of staff in the analytic and big data areas, which, in total was to be by 11%. According to the McKinsey study, there will be a shortage of those who do analytics and interpretation of data as by the year 2018. In the USA alone, it has been estimated that there will be a demand of up to 190,000 people with deep analytics skills (Schroek et al., 2012). Likewise, 1.5 million managers will be required so that effective decisions regarding the big data management can be reached. The management in this question will involve those professionals with different strong biases in different subjects. The same survey concurred with that done by The Big Data London, which found that 78% of the respondents believed that the acute data shortage was looming. Moreover, 70% of them felt that there was an emerging knowledge gap between the big data handlers and those commissioned projects. In another survey, done by the NewVanatge Partners, it was found that it is becoming increasingly difficult to find professionals with big data qualifications. 5% believed that the same shortage was being felt with findings that qualified managers were needed for the management of the big data (Ahalt& Kelly, 2013). As it is being reported, immediate challenge on the issue will present quite a big problem regarding the management of the ethical framework of the big data. This matters because there will be a need to handle big data materials. In this regard, with the emerging importance of big data scientists, people will have strong skills in mathematics, with proficiency in the emerging data technology Data scientists must also have knowledge of the businesses they serve (Ahalt& Kelly, 2013). Removing Barriers in the Implementation of the Big Data Ethical Framework On bridging up the talent gap, it is important that big data management professionals educate themselves. This is important because better data management that has ethical consideration will become a competitive advantage in their business. In this regard, all employees that will be involved, such as big data scientists, analysts, senior executives and managers, will have to be proficient in the management of big data. The second stage will be educating the top managers about the big data management with the consideration of the ethical framework in mind. Moreover, apart from recruiting new talent, companies will be given the task to retain the current employees (Ahalt& Kelly, 2013). The next step should be the academics and researchers forming a council that will be mandated to look into issues of technology category on the perspective of political, ethical and legal issues. Currently, there is the National Science Foundation, which has been formed to look into the innovation projects. The council is scheduled meeting to come up with solutions that involve various experts, especially well-informed professors and researchers, in the field. This will be important for cities, agencies and universities. The big data councils are expected to stimulate dialogues and thoughts from the public and expert researchers. The research team will specifically think about what their consequences may be due to the big data implementation. This will make start-up enterprises and those that own major Internet properties take serious actions about data collection from consumers and customers. Moreover, technology vendors will also ensure big data analytics. This will therefore call for the engineers and executives to improve on their products to grow revenues while avoiding calamities that involve privacy and other thorny issues (Novet, 2013). Eaton(2013) reports that there have been other councils, such as the Council for Big Data, that have invited fellows in the field to imagine about the project they should execute to help the community understand and be able to adapt to the data-soaked age. The next important factor will be improving/being innovative in technology. As already noted, the big question facing the management of big data is technology. It has been reported that in some big corporations, big data is overwhelming (Schroek, et al., 2012). It has been noted that effective data management, whereby raw data are supposed to be transformed into useful information does not only depend on organizational capabilities but also on the use of the right technology. Best-in-class category companies would include dedicated business intelligence (BI) for formalizing the capture and analyses of the data. Leading companies will also use data that enable self-discovery to make business decisions. There are also query tools that will search the data to generate the clear picture of the business aspects. Nonetheless, the technology will be useful in the maintenance and improvement of the business data quality (Novet, 2013). Since some users of the big data might also be a concern, especially those who do not care about or are not responsible for the ethical considerations in big data, they will have to be enlightened on privacy policies and being responsible for their own private information (Tene & Polonetsky, 2013). Moreover, they will have to sign a pact for their boundaries while using Internet. Analysts also note that countries, through international organization, will have to come up with the generally accepted code of ethics and privacy for the big data guidelines. Customers will have to be told about the sort of data the company collects so that they understand that nothing comes free, as they are otherwise told. They should also be told that the data being collected might be deleted. If they want to engage in commercial selling of the customers’ information, they should open a private version of paid services (Moran, 2014).The other important thing will be ensuring simplicity in designing the data collecting and retrieval system. Conclusion In this regard any given data of either organisation or individual should give simple direction for privacy setting adjustments to help users determine what they should share and what they should not. The directions should be understandable and simple. This is because, as more information continues to accumulate in the organization, more criminals are scheming about how to steal it. The business should also define the types of information it really needs and those that it does not. There should also be a crisis strategy to take care of disastrous and hazardous cases in case they occur. In this regard, a very useful resilience framework should be in the organization. Others are having noted that DNA should be part of the privacy policy. This will ensure the needed transparency, security and simplicity, and customers will embrace the business. Firms should also hire chief data officers or chief privacy officers to be responsible for privacy and ethics concerning the data in the organization. References Ahalt, S., &Kelly, K. (2013).The big data talent gap.UNC Kenan-Flagler Business School. Amazon Publishers. New York City. Arellano, N.E. (2013).The need for big data ethics. IT World Canada. Retrieved fromhttp://www.itworldcanada.com/post/the-need-for-big-data-ethics Brans, P. (2013).Ethical questions around big data.CIO Insider. Retrieved fromhttp://www.cio.co.uk/insight/data-management/ethical-questions-around-big-data/ Eaton,K. (2013).Danah Boyd’s data &society program wants your help freeing the data. Fast Company. 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