Big Data

 Welcome back to another weekly blog! This week I am going to be talking about Big Data and how this presents several potential ethical and social challenges.

Big Data

This can be referred to as large and hard to manage volumes of data. This data can be either structured or unstructured. Big Data can be used to analyse insights to help improve decision making and also give businesses confidence when making strategic business moves. Big Data is so complex that its impossible to process using traditional methods. Since Big Data is so complex it requires new tools and technologies to help with managing the data. Within Big Data there are 5 main characteristics. These include volume, variety, velocity, value and veracity. I will now give you a brief description of these characteristics.

1.Volume: this refers to the amount of data that exists. Big Data has a huge volume therefore it has been given this name.

2.    2. Variety: this refers to the diversity of the data types collected from various sources.

3.    3.Velocity: this refers to how quickly the data is being generated and also how quickly data can move.

4.   4. Value: this refers to the value that data can provide. It also shows what organisations can do with the collected data.

5.    5. Veracity: this refers to the quality and accuracy of the data collected.

 

For further information on this please see below link:

https://www.google.com/search?q=5+vs+of+big+data&sca_esv=576459179&rlz=1C1JZEV_en-gbIE921IE921&tbm=vid&source=lnms&sa=X&ved=2ahUKEwj7osb6gZGCAxUDW0EAHcaCCAUQ_AUoAnoECAMQBA&biw=1280&bih=595&dpr=1.5#fpstate=ive&vld=cid:cbbea279,vid:jl0UnQS_qbc,st:0

 

Ethical challenges:

An example of an ethical challenge is big data and the healthcare system. Big Data is hoped to improve the impact of the delivery of healthcare services. The main ethical challenges with this include respecting the patient’s autonomy and achieving equity.

When respecting the patient’s autonomy informed consent must be obtained. The patients must understand the risks and purpose of the research. Since Big Data is so different to traditional methods the biggest concern is that the research requirements regarding consent still properly respect the patient’s autonomy. It is also very important to protect the patient’s privacy and confidentially. This can be very challenging in todays digitalised world.

2.     When achieving equity Big Data can be a challenge since the research focuses in on one group of people based on race, ethnicity etc. Since these findings relate to one single group the information would not relate to a different group. This could be harmful in healthcare as a treatment that may work for one group of people may not work for others and cause side effects.

 

Social challenges:  

An example of a social challenge is the Big Data divide between companies and customers. This relates to the asymmetric relationship between those who collect, store and mine the large amounts of data and those who are the target of data collecting e.g. consumers. This causes a structural divide for those without technical means to access and analyse the data. From an ethical view this Big Data divide challenge is a combination of violating the value of equality and violating the autonomy of those who are the objects of data collection.

Another example of a social challenge is Big Data and discrimination. Data bias could lead to discrimination and unfairness in machine learning. The main two forms of discrimination are disparate impact and disparate treatment. Disparate impacts refers to the consequences of decision making on certain groups, there is no intention for this to happen but it causes a challenge of discrimination. Disparate treatment refers to classifying someone in a prohibited way. This involves the intent to discriminate.