Written by Richard K. (KIS‘22)
━━ Nov 27, 2020━━
Overview
Anyone who has used a smartphone in recent years will have experienced working with some form of artificial intelligence. On the other hand, big data is not something that consumers directly interact with or experience but it works more behind the scenes to make artificial intelligence possible. With science fiction movies like Terminator or Avengers: Infinity War gaining massive popularity in recent times, the curiosity about the real-life implications of artificial intelligence, or AI, and big data is at its peak. Of course, these movies far exaggerate the real state of these technologies and how they might function. Even in the real world, artificial intelligence is used coherently with big data to allow useful functions to be carried out.
Artificial Intelligence
So what exactly is artificial intelligence? Well, “AI” stands for Artificial Intelligence and it is used in many of our daily electronics today. It refers to machines and electronic devices being able to think or act as humans do and make decisions in scenarios that would normally require some thinking. Artificial Intelligence has been a common term for the last 10 years and people use the term “AI” very frequently. AI is used in a myriad of technologies nowadays in daily appliances and whatnot. For example, AI is used in our speakers, phones, refrigerators, TVs, and that's just the start. According to an article from CMO by adobe, 37% of organizations today have implemented AI in some form. Another mind-blowing statistic is that by 2021, 80% of emerging technology will have AI foundations. These stats put into context how massive a part AI plays in the world today.
Big Data
Big Data is actually a much newer concept that has risen to prominence in recent years. People do not know as much about Big Data and how it is a really big part of the future of the world. Big Data refers to a large amount of data collected over extended periods of time and research to fuel these decisions that artificial intelligence make. Collected data is fit into datasets and are provided to machines to learn from the experiences collected from empirical evidence and as a result, make proper human-like decisions. Types of Big Data include biometric data in hospitals or product consumption in online stores.
How do they work together in the modern world?
AI and Big Data work in close proximity to form patterns or features in data. This process is called deep learning (or machine learning) and it allows machines to function like humans. Deep learning is used effectively to make a revenue for many companies in the modern era. Google, Youtube, Facebook, and etc. all use Big Data and AI to collect data and use that data to appeal to our specific interests. This is a major marketing strategy used by many companies and some might say it violates consumers’ privacy. Big Data is stored in a database and remembered for long periods of time which is then used to constantly bombard their customers with things that they might like in the future. For example, you could be browsing for a watch on Amazon one day and when you go on Facebook the next day, there could be an advertisement for the exact watch you were interested in. Another good example would be the example of streaming services such as Netflix. Netflix would use data collected from users and the type of content they might stream to decide what type of content they might invest in to provide the users in the future. Another use of this technology would be using it to decide the type of content they would display to the user in the front of the screen. They collect data from previous streams and using such data, decide what other shows they might be interested in or want to watch. Using such a targeted marketing strategy, companies can focus their advertisements specifically for each customer that browses their website. In this way, customer retention and customer acquisition would be enhanced which would, as a result, increase revenue for companies.
Limitations
The combination of big data and artificial intelligence has stemmed from a relatively recent development. As such, there are still some limitations that come about from this collaboration as of now. One huge limitation is cost. To utilize big data properly and reduce latency when handling said data, high-performance data systems are required. These high-performance data systems make the handling of data much more efficient and are required as the datasets get bigger and bigger. However, as more high-performance data systems are required, the cost of handling such data get higher and higher, adding a financial strain to small companies that might want to utilize this technology in upcoming projects. Another limit as of now is the view people have on their data being collected by large companies to increase revenue. Collecting data to fuel datasets come with a consequence. Most times, a customer’s privacy is compromised when data is collected. Many people around the world do not feel comfortable when a company is able to collect their personal data to increase revenue. For this reason, collecting data is not as easy as it seems. A mutual understanding needs to be established in the future for big data and artificial intelligence to continue to work together.
Conclusion
Despite its limitations, the melding of big data and artificial intelligence clearly has a substantial role in the development of our future. It has gone through multiple years of research to get to this point, but much more research will be required to seamlessly incorporate this technology into our lives in the coming future. Regardless, the impact this partnership has had on society at this point is already colossal and will no doubt continue to overcome limitations to refine how artificial intelligence is utilized in the future.
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Credits:
Sinur, Jim. “AI & Big Data; Better Together.” Forbes, Forbes Magazine, 1 Oct. 2019, www.forbes.com/sites/cognitiveworld/2019/09/30/ai-big-data-better-together/#1032228960b3
Flovik, Vegard. “The Hidden Risk of AI and Big Data.” Medium, Towards Data Science, 1 Mar. 2020, towardsdatascience.com/the-hidden-risk-of-ai-and-big-data-3332d77dfa6.
“Redefining Big Data Analytics with AI.” Sisense, www.sisense.com/whitepapers/redefining-big-data-analytics-with-ai/.
Abramovich, Giselle. “15 Mind-Blowing Stats About Artificial Intelligence.” CMO.adobe.com, cmo.adobe.com/articles/2018/9/15-mindblowing-stats-about-artificial-intelligence-dmexco.html.
Rice, Mae. “17 Big Data Examples & Applications.” Built In, builtin.com/big-data/big-data-examples-applications.
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