In: Computer Science
How can businesses and organizations continue to respect legal and ethical concerns while still permitting the use of predictive analytics to drive business value? Identify and discuss some legal or ethical practices that businesses and organizations should consider when using predictive analytics.
Businesses and organizations can continue to respect legal and ethical concerns while still permitting the use of predictive analytics to drive business value by following the Government policies and other ethical policies in place like Fair Trade policy, Privacy policy, etc. The Businesses and Organization can set up internal rules and regulations to which all the employees in the company will adhere. For eg - No employee can use Predictive Analytics for his/her personal gain.
Some legal or ethical practices that businesses and organizations should consider when using predictive analytics are:
1) Privacy: The predictive analytics should not hamper the privacy of individuals and organisations whose data they have. Systems seem in conflict with employees’ right to solitude and their freedom from being watched or listened to as they work. No organisation should use such practises on their employees.
2) Diversity Biases: The predictive analytics may sometimes reveal that a people belonging to a particular ethnic group, religion or gender perform better in comparison to other diversity group . No organisation should discriminate with its employees on these grounds.
3) Legal Boundaries: Although HRM professionals should always ensure that they operate within the boundaries of the law, legal compliance does not seem sufficient when it comes to people analytics. Frequently, legal systems are unprepared to defend employees’ privacy against the potential invasions via the increasingly rigorous data collection systems .
4) Free and fair Competition: No organisation should enjoy a complete monopoly over a particular market. Big organisations should not indulge in practises which will lead to unfair competition.