Presenter : Pat
Date : June 9th, 2022
Part presented : Chapter 3.2 to 3.4, pages 143-161
Presentation
The presentation includes two main points in total. The first part is the introduction of data analytics and how it is perceived and used. Followed by how the data analytics are developed to use as a factor to drive the decision-making process in businesses. Then, discussions on the related topic were conducted.
In the first part, several keywords such as data mining, profiling, business intelligence, machine learning, statistical learning, and visual analytics were introduced to provide the basic idea for the audience to understand the following contents of the presentation. In short, Data analytics is the development of algorithms and heuristic methods to process and analyses large data sets. Google, for example, as they have to handle the big streams of unstructured data which is inputted into their operation on daily basis. They developed MapReduce, a programming framework for processing large data sets in a distributed fashion, and BigTable to manage a huge amount of data. In addition, Data Analytics is supported using Open-source software and Cloud Computing. Open-source software provided the open-source implementation, packages, and environment to be retrieved and used by a wider population. For instance, the use of R programming, an open-source environment for statistical analysis, is increasingly used as an alternative to commercial packages such as SPSS and SAS. Similarly, Cloud Computing offered the service model to facilitate data analytics by providing computational resources via a platform on which applications and services can be developed and hosted. Cloud computing reduces computing costs by enabling the service in which users are able to respond to customers’ needs and demands without much initial investment in IT infrastructure. Hence, lower barriers to Data analytics for start-ups and SMEs, and consequently facilitate the declination of data storage and processing. Referring to Our World in Data, the following graph illustrated the declination of storage costs from1957 to 2012.
The graph showed that the storage cost declines significantly over the year, this is because the development of data storage allowed the storage to cost less.
The second part highlights the use of Data Analytics in decision-making. By using Data Analytics as a tool in the business, the data is generated, collected and combined. Then, provides the insights and patterns of data which uses to support the decision-making process. A survey from Economist Intelligence Unit (2012), showed that almost 60% of business leaders use big data for decision support. Moreover, the output and productivity of firms that adopt data-driven decision-making are 5% to 6% higher than the expectation compared to other types of investments in information technology. There are three key functions that allowed data analytics to gain insights which are i.) the ability to extract information from unstructured data, ii.) information from real-time monitoring and tracking of the activities and iii.) the inference and prediction based on the users’ data using machine learning. With these abilities, the businesses which based on data analytics can swiftly adjust their strategy towards the changing trends which reflect on the real-time, patterns, and prediction of users’ data. One of the examples of using data to drive the decision is the Google driverless car. By using the collection of data from all the sensors connected to the car and data from the Google Street View such as landmarks, traffic signs and lights, etc., the car system makes the decision by itself requiring no human to perform the task. Even though, these developments help alleviate many human tasks. The autonomous system can also make mistakes from the limitation of data-driven decision-making. Another case that pointed out that human decision is still required in the important decision is the use of Algorithmic trading systems (ATS) which is the system that can autonomously decide what, when, and at what price to trade the stocks. In 2012, the Knight Capital Group lost around USD 440 million in less than an hour as the ATS behaved unexpectedly. This is because the system misinterpreted the decision from the data pools which is misleading.
Discussion
In the discussion part, three questions were raised as follows
- The use of ATS to trade stock is widely used in the USA. However, regardless of the case of Knight Capital Group, the fact that the trading system which relies on real-time analysis can retrieve more data compared to human decision-making is still standing. The question is to which extent do you willing to take this risk when it comes to the financial decision using autonomous data-driven decision-making.
In the discussion, some of us agree that they are willing to let the autonomous make the decision aiming to make some profit out of the investment. However, the risk that they are willing to take is limited to a small amount of fun, not all their savings.
- The use of machine learning for Inference and prediction allows the recommendation engines that power services such as Amazon, Spotify and Netflix to adjust the user interface to suit the user’s taste. However, is it viewed as a convenient or privacy violation?
In this question, apart from some of us stating that they do not mind the recommendations as it is convenient for them to enjoy the service, the question was raised that the term and conditions of the services are always too long to finish reading as if the companies intended to bored people so they would not read the term and condition. Then, hide some important content in plain sight with ambiguous words so they can use the information of the users. Hence, there should be a standard to cope with those kinds of things so the providers are forced to state clearly how they will handle our information.
- By allowing the machine to make the decision while constantly improving itself using big data will one Artificial Intelligence try to wipe out humanity someday in the near future?
The question is intended to encourage the members to make funny comments on it before ending the session. Information about the case that robots might eventually conquer the world was exchanged. For example, the discard of the ASIMO robot was mentioned to point out that the development of robots continues to grow. Moreover, with the new introduction of the robot that can express their feeling with the artificial face muscles and the articles saying robots can start to think by themselves to the point that resembles humans, it is impressive yet scary at the same time. Additionally, should we start to think about what will we do if something like so will actually happen?
Source
Data-Driven Innovation: Big Data for Growth and Well-Being report: https://www.oecd.org/sti/data-driven-innovation-9789264229358-en.htm
The historical cost of computer memory and storage: https://ourworldindata.org/grapher/historical-cost-of-computer-memory-and-storage?country=~OWID_WRL