BIG DATA: Can Google Use Big Data to Create Personal Assistant?
Abstract
This paper will investigate the concept of Big Data and how this can be used by Google to create a personal assistant with more powerful features. Big data simply refers to the huge loads of data collected from the internet and other social media platforms such as Facebook, Twitter, Yahoo, Amazon, MySpace and several others. Innovations that employ big data to create personal assistants are not new in the technology sphere. Yet there are several problems with the use of Big Data such as information security which can affect the privacy and safety of the users and companies involved. Apple, Google, and Microsoft have all developed their personal assistants in the past. Siri, Google now and Cortana are personal assistants of Apple, Google, and Microsoft respectively. However, these companies have faced security breaches as well. This is where Big Data can help companies improve information security and prevent breaches.
The main objective of this article is to evaluate how Google can leverage the power of big data to design personal assistants that behave exactly like human beings. The paper also exploits one of the major issues faced by mainstream companies regarding the protection of their security and how the personal assistant chosen by Google can help with this issue. The personal assistants in use today are limited in capability and have little support for voice technologies. It is hoped that Google will change the way it collects big data to create personal assistants that track individual data using their accounts. The article will start by giving a broad introduction to big data that will explain the meaning of big data and how this data is collected. Next, the benefits of big data to Google as a company and other companies, in general, will be explored. The article will then investigate various risks associated with big data and the problems that Google face with its current personal assistant application. The article will then conclude by giving various recommendations that can be adopted by Google to create a state-of-the-art personal assistant.
Introduction
The term “Big” data has grown quite popular in the recent past. Generally, “Big Data” refers to a collection and storage of huge loads of data, a collection so huge that can only be processed by supercomputers and cloud networks. The data sizes go as large as one million gigabytes. In several industries globally, there has been a raging debate as to when the big data will arrive and the level of impact it will have on the organizations. These arguments tend to overlook the already big impacts being felt as a result of big data. The arrival of big data was not spontaneous, rather it has and will continue to progressively integrate into business processes with the largest impact felt over the long run. The practice of collecting a lot of data is not new and has been practiced over a long period of time. The manner in which the data is collected and the way it’s applied is what makes big data more unique and exciting. In the world of today, more than any time in the past, every content is being monitored and tracked- from audio, video, messages from mobile phones, CCTV cameras, etc. The world seems to be fully going the electronic way.
Big data opens a new channel for conceptualizing the world and making decisions. (Lohr). Experts suggest that data has been growing rapidly at a rate of 50 percent annually or more over the past few years. It’s not just about the growth, but new loads of data are created on a daily basis. For instance, currently, digital sensors are fitted in vehicles, industrial equipment, shipping crates and several other equipment. These sensors can detect and relay information relating to location, temperature, humidity, movement, etc. When linked to intelligence systems, we experience the rise of the “Internet of Things”. Not only is data becoming easily available but also more understandable to machines. Big data is mostly made up of data in the wild-unorganized stuff such images, words, and video. Sorting this data was a major challenge in the past. However, the recent years have seen the development of intelligent algorithms, integrated with increasingly high processing machines, which has enabled government institutions and private entities to connect the dots and extract insights in all this data. The extracted patterns enable companies to manage easily complex systems, improve the already existing systems, and easily forecast the future. It is worth noting that in the past decades, the responsibility of analyzing hordes of data and trying to make sense of them was bestowed upon the humans. (Lohr). With advancements in software and hardware technologies today, this responsibility has been assumed by the computers. To actualize this, information systems experts and scientists have creating systems with the cognitive and analytical competencies of humans, hence creating a paradigm of intelligence. This research aims to evaluate BIG data in general and how it can be harnessed by Google to create personal assistants that have better and more powerful capabilities than Siri. Generally, the research will explore big data and its benefits, challenges faced with big data, risks of big data, the shortcomings of the already existing personal assistants and how Google can apply big data to create personal assistant superior capabilities. (Lohr).
Big Data Benefits to Google
“Big Data” has become the slogan for the large hordes of information that can be extracted from interactions on the internet. With loads and loads of data being generated every single minute, the biggest question is how organizations can harness the benefits accrued from big data while also avoiding paralysis by analysis. In essence, data is generated from the activities of the end user and organizations are more concerned about what is being talked about them on various platforms such as Facebook, Twitter, MySpace, Amazon, and then leverage the information for marketing or for purposes of managing the reputation of the organization. In the current corporate world, organizations no longer use big data for experimental purposes. Several organizations have achieved massive improvements with the big data approach and are endeavoring to extend their efforts to include more data and tools. (A.McAfee).
Big data enables Google and other companies to have a better understanding of their user base. Because of big data, Google is able to measure and know more about its customers, and use the customer data to improve service delivery and performance. Take an analogy of the old retailing system. The traders in physical stores were able to track which goods were sold and which ones were not. In the case of a loyalty program, some of the purchases could be associated with specific customers. Once the trade was migrated to the online platform, there was a radical increase in customer understanding. Using analytical tools, the online retailers were able to track not only what the customer bought but also what they viewed, how they navigated through the system, how the promotions and product review influenced their buying decisions and the correlations across the individuals. (J. Ratkiewicz et al.,)
Google has continued to improve its customer experience using big data and analytics. The organization achieves this by using powerful data collection and analysis tools to analyze the activities of an online user. A careful analysis of data collected from the social media sites such as Facebook, Twitter, and Amazon, etc. gives the company insight into what the customers really need and eventually design solutions that meet these needs. All the data sources are used to understand the customer, and technology used to integrate them real-time for faster decision making. Research indicates that the big data in use today is more powerful than the past analytics tools. With big data, measurement and decision making are improved manifold. Consequently, the understanding of customer trends enables Google to make better forecasting. Big data forms the foundation of Google’s broader strategy on customer retention. With proper use of this data, Google is able to have access to information that it previously did not have. With augmented access to data from a variety of sources such as the social media, Google can better create marketing campaigns targeted at customers, better forecast demand for individual products, and conduct real-time advertising campaigns. Moreover, it is expected that new opportunities will be created by proper use of big data in Google and other organizations. (J. Ratkiewicz et al.,)
Big data Risks
Although the benefits of big data are immense, there are risks associated with this technological innovation. Just like other good technological advancements, big data has both its advantages and disadvantages. It gives organizations the opportunity to personalize their services, it accelerates business growth, and allows organizations to extract insights from big chunks of data. To begin with, the issues of privacy concerns have been raised by big data. Some people are not bothered about their privacy and use social media platforms carelessly thus giving other malicious users the opportunity misuse the information. For example, if a consumer wins some promotion, he/she will be required to provide some personal information. Some consumers who are oblivious of the terms and conditions may sue the company if they feel that their privacy has been breached on thus creating reputational damage to the company. (A.McAfee).Moreover, before using big data for marketing and research, personal information is usually removed from the data to make it anonymous. Nevertheless, the database can never achieve 100% anonymity as required. Customers who may have consented to their use of personal data with the assurance that the personal information will be kept anonymous may be oblivious of the fact that the identification process is possible.
One of the greatest strengths of big data is its ability to segment and cluster data. While this is a highly desirable feature when dealing with large volumes of data with high degree of variation, it could also be dangerous. Experts argue that customer segmentation can cause discrimination on the basis of religious background, political affiliations, gender, and age.
Big data also faces serious security challenges. Theft of data and personal information is widespread and a growing issue of concern. Statistics indicate that out of the six most damaging data thefts, five of these were executed in the last two years. The size of the data is directly correlated to the risk it faces from criminal elements. Hacking incidents in the past has seen several customers lose their credit card information and personal details. These black hat hackers exploit the weaknesses in big data to launch their attacks on the information platforms of the organization.
Problem faced in information technology
There is not a single electronic creation that is not free of faults. The world of information technology is truly revolutionary, but it has its issues and restrictions. Although IT allows people to make as the diversified and public use of their information, it also facilitates the need to secure private information. However there is a major issue related to the breach of security, and many companies are constantly insecure with regard to the safekeeping of information. The meaning of information security is the prevention and protection of information on any device or software from getting accessed unauthorized, being disclosed or disrupted, inspected, recorded or deleted. This is usually done by viruses or bugs on various software programs or sources which cause many problems to users because information is lost or hacked and misused due to a lack of protection. Information security can be guaranteed with the use of Big Data because it is one of the uses and applications designed by Big Data analytics regarding its ability to protect large volumes of information without glitches and problems in security. As a large amount of data is being processed and controlled in real-time, Big Data has the ability to safe-keep information and ensure its security. Companies have faced many problems with information security largely due to the lack of problem security and lapses in the need to control the inflow and outflow of data.
An example of such a company is Samsung, the major and foremost user of Android. A Dutch watchdog sued Samsung for the Android software carrying the ability to be hacked and its information highly unsecure for the users. Samsung had security vulnerabilities because it had the feature of being updated without being told and the users were under the risk of inviting a big into the phone without knowing. This meant that the information could be leaked in the phone, and this did happen many times. Many Samsung phones lost their data; either it was deleted by a virus that came with a software update or an installation through the Google Play store. This was very problematic and alarming for users as they were in need to keeping their data safe from prying eyes but not only was their data liable to hacking, it was also under the risk of being lost without being retrieved. The StageFright exploit was a major issue that was faced by Samsung and obviously android. This also caused Samsung, HTC, and other Android-run phones to lag behind in safety which meant their sales would suffer. The company getting sued was enough for their image to suffer negatively.
The use of Big Data, in this case, was the strengthening of the information security and helping Android get hold of its problem before users would suffer from the lack of secure use. One of the most basic helping tools that Big Data can introduce to the company is to add an ‘Agree to Terms and Conditions’ to the software updates on android and prevent users from enabling downloading without agreeing to them. This will prevent the Company from being blamed every time a security breach occurs, and the user will know that their data is safe because a download did not be on its own. Notifying them is also important. Another benefit of using Big Data in this context is the use of sanitizing data at the earliest points so that it is safe in the initial stages and not leaving it to be scanned right at the end. This is because information security is embedded in the world of IT and the use of the internet for this purpose can cause a virus to enter the system which could be embedded in the system. This is the reason why Android is ‘bugged’ constantly. Choosing these options will enable the users to become aware of what they are downloading in phones and Big Data will also help to ensure security. Moreover choosing a step-by-step scan will help analytics to find out information security risks in the earliest stages. (Goodendorf).
Next Generation Personal Assistants by Google
Research is constantly being done on the next generation personal assistants. Google aims to develop a personal assistant that will learn and act exactly like human beings. The organization plans to change the way it collects data so that data is organized according to individuals instead of big categories. Each mobile phone running Google operating system will have a unique personal assistant that is different from personal assistants on other user’s phones. Through this approach, Google will be looking forward to creating a more accurate personal assistant that tracks the actions of an individual user. For example, if a user whispers to the personal assistant that he/she is hungry, the personal assistant would not return the location of restaurants around. Instead, the personal assistant would inquire what the user wants to eat. If you say something that the personal assistant does not understand, it should be able to give you feedback like, “Sorry, I don’t know what that means.” The personal assistant just like a child will be expected to learn and comprehend things. If you tell Google Now or Siri that you are a fun of pizza, they would just get rid of this information with immediate effect as they don’t know how to go about it. However, the future personal assistant to be developed by Google is expected to analyze this information, contextualize it, create a knowledge chart about that particular user, and regularly apply the new knowledge learnt about the user to analyze the user in terms of what they want, what they prefer and the kind of information that is most relevant to them. The machine learning paradigm creates data for intelligent systems and other future personal assistants to learn from. At the initial stages, it may appear slower than other personal assistants such as Google now and Siri which majorly extract their data from Wikipedia, Bing, and other search engines. As time goes by, the personal assistant will learn much about the user and integrated the personal data with big data accessed over the internet to enable it to return more significant and accurate results than any personal assistant in use today. (A.McAfee).
Research indicates that human beings generate huge loads of data daily. An individual’s text messages, email correspondence, call history, web browsing history, etc. all forms of sources of huge data. Future personal assistant will harness this data to help it understand the user more closely and assist them to execute their daily tasks more effectively. The early versions of personal assistants which have been extensively used by many individuals are Siri from Apple Company, Google Now and Cortana from Microsoft. Each of the above has applications that that help individual to collect, store and manipulate a personal horde data. Google, for instance, gives users access to a wide array of free services such as email, calendar, storage drive, etc. by simply creating a Google account. Each activity performed on these services is captured and stored in an individual account inside the Google’s servers. Acting as a personal assistant, Big Data, in this case, will prevent the user from the biggest risk of being exploited by the use of a device or application. It will prevent unsafe use of software and inform of any kind of malware that the device could be at risk of.
Recommendations to Google
With competition intensifying from other industry players such as Apple and Microsoft, Google must go back to the drawing board to stay ahead of the competition in the big data market. Part of the strategy that Google can employ to craft personal assistants with superior features than those of the competitors is to create a personal assistant that is capable of learning as a child. The personal assistant will collect user information, contextualize it and store this information for future reference. Google should create a more personalized web search where user data is stored in their individual accounts for easier retrieval and decision making. Google also needs to empower the users by letting them know what risks they are at when they use certain apps or download without the option of agreement to terms and conditions. Moreover, Google should adopt a voice interface personal assistant as opposed to the current graphical user interface model. Experts reaffirm that “voice is the most natural form of interaction.” With the voice interface, even disabled members of the society would be able to use the machines thus it’s accommodative to all. If Google implements this, it would be guaranteed the lion’s share of the market of big data which would eventually translate into bigger profits for the company.
References
A.Tumasjan et al., in Proceedings of the 4th International AAAI Conference on Weblogs and Social Media, Atlanta, Georgia, 11 to 15 July 2010 (Association for Advancement of Artificial Intelligence, 2010), pp. 178.https://googleblog.blogspot.com/2012/06/find-out-what-people-are-searching-for.html
A.McAfee, E. Brynjolfsson, Harv. Bus. Rev.90, 2012Goodendorf, Lynn. Managing Big Data Privacy Concerns: Tactics for Proactive Enterprises. Search Security. n.d Web. 20 Mar 2016.
J. Ratkiewicz et al., in Proceedings of 5th International AAAI Conference on Weblogs and Social Media, San Francisco, CA, 7 to 11 August 2011 (AAAI, 2011)
Lohr, Steve. “The Age of Big Data.” The New York Times, Feb 11, 2012.
