Big data Outcome 3 Part 1

Week 7 (07/05)

This Blog will Cover The first Half of Outcome 3 which will go over my findings of  information which i have found interesting from the First Two topics of Limitations of predictive analytics and Implications of Big Data for individuals, Topics 14 and 15 respectively 

Topic 14

The Limitations of predictive analytics Uses Historical data, Statistical algorithms and machine learning Which they use from gathering all the data from the areas to predict possible future events by looking at the past and comparing sources to decide wither or not something might happen,  The limitations of predictive analytics can be split into 4 key areas 

1. Data quality and availability

As data sets get larger from harvesting data, the quality of the data and availability of the data  is important when using predictive analytics. As when collecting data from all a cross the internet the quality of the data can vary resulting in missing value or inconsistencies. 

2. model complexity and interpretability

Model complexity and interpretability ever increasing, it can make predictions complex and hard to understand and interpreter the  points making the prediction. Which makes it difficult for companies.

3.Temporal dynamics and changing patterns

With big data constantly generating new data sets with ever evolving information, predictive analytics so the increase of historical data increase but as the future is inherently uncertain the prediction can quickly become incorrect or outright not close to what real outcomes would be 

4. ethical considerations and privacy concerns

    The ethical considerations when using predictive analytics could raise ethical concerns as the data it uses to train on could incur bias and discrimination if the data it trains on is bias or a discriminatory in factor,  With predictive analytics there is always a concern about privacy is if a persons data is getting used without their consent.

Topic 15

Topic 15 is about Implications of Big Data for individuals which goes over privacy concerns of Big data analytics on an individual person and how it could effect them. Implications of Big Data for individuals can be split into 2 areas of concern for the person who's data is being analysed these points being Data collection and consent, Data profiling and discrimination.

Data collection and consent

With data constantly being generated by individuals every second, it could create significant privacy concerns if Users found out how much of their actions on the internet create data which is then harvested and put into data analytic predictions without their consent

Data profiling and discrimination

Big data can be trained to profile individuals based on their behaviour, preferences and other personal attributes. which if this analytics is being feed bias and discriminatory data sets it can cause the AI to unfairly profile individuals based off things like stereotyping which can lead to bias in important areas like employment or insurance. 

This page i found interesting  and goes futher in depth about Implications of big data on individuals

https://www.linkedin.com/pulse/implications-big-data-privacy-concerns-intelligentautomationcompany